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What Is Funnel Analysis? Definition, Examples, and Tools

Use funnel analysis to identify key events along the customer journey and improve metrics like acquisition and conversion.

Not all prospects will become customers, and not all customers will immediately find the value of your product. Funnel analysis can help you pinpoint key events along the customer journey so you can conduct tests, improve the user experience, and increase conversions.

What Is Funnel Analysis?

Funnel analysis is a method used to analyze the sequence of events leading up to a point of conversion. Events within the funnel take place inside products, mobile apps, websites, emails, or other digital touchpoints. Funnel analysis lets product and marketing managers understand user behaviors and the obstacles encountered throughout the customer journey.

As users travel this digital path, they will probably encounter experiences that prevent them from reaching the desired outcome. You can improve the points of friction to encourage users to travel further down the funnel by zooming in on each step.

According to TechCrunch , “From leads all the way through to engagement, conversion and retention, understanding each step and making even small optimizations at any stage will have down-funnel implications.”

As an example, let’s say you’re trying to convert free trial prospects into paid subscribers. Your funnel might look like this:

• Step 1: Prospects open an email and discover an offer for a free trial.
• Step 2: They click on a CTA button to redeem the free trial.
• Step 3: Prospects create an account and use your product for free.
• Step 4: Prospects convert to paid customers after the free trial expires.

Many distractions or barriers can happen in between each of these steps, and there are likely patterns of behavior that can tip you off to what’s working and what’s not. Perhaps prospects are dropping off at step 3 because of a multi-device activation required to create an account?

Maybe you discover that if you can usher prospects past step 3, you have a stronger chance of conversion. Without funnel analysis, you’ll miss these opportunities to delight customers and drive business outcomes.

• Funnel analysis is a method used to visualize, measure, and understand key user behaviors throughout the customer journey.
• As customer habits and patterns shift, you’ll need to be able to monitor those differences ASAP. Funnel analysis alerts you when something isn’t right, so you can keep users on their path to conversion.
• Funnel analysis is nearly indiTakeawaysspensable when it comes to product improvement, personalization, and creating smooth customer journeys.

The Importance and Benefits of Funnel Analysis for Your Product

At its core, funnel analysis is important because it allows you to monitor user actions and behaviors. This is critical because those behaviors reveal the intention and motivation of your customers.

Funnels are not just used in sales or marketing to create prospects, they are also important for customer retention . Once you know what your customers want, you can inject that value into each step of the customer journey.

Although every business has unique goals, funnel analysis can be used to:

• Improve conversion. Conversion funnel analysis can support a lot of outcomes or specific goals. The final step for a user might be clicking a “Sign Up” button or downloading a PDF. Funnel analysis enables you to find out what’s preventing users from reaching the end destination. Each stage of the funnel poses opportunities for a smoother, more personalized journey to the end of the funnel.
• Streamline the funnel . Your company probably supports multiple points of digital interaction , such as websites, mobile apps, email, or dashboards. Each one has a funnel of its own, but together, they represent one overall customer journey funnel Funnel analysis can provide a macro perspective on how each of those funnels links together.
• Merge marketing and product teams . Oftentimes, marketing teams are focused on converting prospects into customers, while product teams are primarily focused on retaining those customers. Funnel analysis presents an opportunity for both teams to cross-pollinate data and insights. If prospects respond positively to a certain aspect of the marketing funnel, they may stick around if they find that same value in the product funnel.

4 Ways to Use Funnel Analytics

Funnel analytics presents many different ways to extract insights from the data you collect. How you interpret funnel data and leverage it to achieve goals is native to your business and industry.

• Conversion: This is the default mode of analyzing your funnel. It measures the number of users who have converted through each step of your funnel. Depending on the platform, this data can be visualized through a chart or bar graph. The results of this method should immediately alert you if there’s a problem. If there’s a severe drop-off of users during one step of the funnel, you’ll know where to center your efforts.

• Conversion over time: Conversion over time lets you see conversion rates for users who enter the funnel on a certain date. Users don’t necessarily have to complete the funnel to appear in your analysis. This is useful when it comes to understanding how your funnel operates through different times of the year, like holidays or special events.

• Time to convert: An important factor in analyzing a funnel is time. How long should it take for each user to click through each step? These user tendencies can confirm that your funnel sequence is operating as designed. For instance, someone shopping on a quick-service restaurant app should convert faster than someone shopping on a tax service app. By breaking conversion down by hours, days, weeks, and months, you can alter the flow of your funnel in a way that’s meaningful to your business.

• Frequency: How many times do users perform an action or behavior before they move on to the next step in the funnel? By measuring frequency, you can see exactly what your users are doing (and how often) throughout the funnel. Understanding the frequency of events can help you make changes to specific funnel steps to encourage higher conversion.

Oftentimes, problems in your funnel need to be approached from a unique angle or perspective. Funnel analytics provides a launchpad to start asking the right questions . Once you’re familiar with basic analysis methods, you can find innovative ways to overcome challenges.

Tools for Conducting Funnel Analysis

Analytics platforms are nearly indispensable for businesses that offer digital products and services. Without the right tech stack, it becomes extremely challenging to measure and improve things like conversion.

There are many options available when it comes to choosing a funnel analysis tool. The best tool for you is dependent on your product, industry, and current tech stack.

Amplitude’s Digital Analytics Platform offers a unified suite of products that gives you an in-depth understanding of how customers experience all of your digital touchpoints. Amplitude’s funnel analysis product is built for websites and products, giving a more holistic perspective on data.

Any event or user behavior can be measured and tracked, not just page views or sessions. When conducting funnel analysis in Amplitude, you can order the events of your funnel, segment behavioral cohorts, and set specific conversion windows.

To meet the needs of companies across every industry, Amplitude’s funnel analysis chart is flexible and customizable, making it an ideal option for multiple teams or stakeholders. Easily leave notes for teammates or quickly share a link to a funnel view.

Other funnel analysis tools

Other tools you can use for funnel analysis include:

• Adobe’s funnel analysis product
• Google Analytics

Learn more about each of these tools on a review site like G2.

Real-World Examples of Funnel Analytics

Many companies are taking advantage of funnel analysis because understanding the customer journey is critical to building successful products . The power of funnel analysis comes from its utility—although it’s only one tool, it can be used to solve a host of various challenges. Below are two funnel analysis examples, so you can have a better idea of what’s possible.

Patreon Increases Subscriber Conversions with Funnel Analysis

Patreon provides creators, artists, and entrepreneurs with the opportunity to earn a living through donations. Users can “pledge” donations to creators on Patreon’s platform, and when creators win, Patreon wins. Patreon faced a conversion challenge—they needed to find new ways to incentivize monthly subscriptions to creator content.

Patreon discovered an opportunity to improve the pledge flow funnel through Amplitude’s funnel analysis chart. Patreon tested a new feature called “blurred posts” to encourage more users to click through the pledge flow. These blurred posts concealed a portion of creator content, enticing users to delve deeper into the pledge flow funnel and ultimately subscribe. The result? Patreon was able to double pledge conversions on creator pages.

Mindbody Uses Funnel Analysis to Drive Conversion with New Features

Mindbody is a digital application that connects customers with fitness experts. Users can book classes, track fitness progress, and find local deals. Using Amplitude’s funnel analysis tool, Mindbody tested a new app feature, the “Activity Dashboard,” to find out how it would influence the conversion rate of booked classes.

Mindbody created behavioral cohorts—groups of users categorized by behavior—to conduct their analysis. Cohorts were segmented into two groups: those who interacted with the Activity Dashboard and those who did not.

After comparing the two groups in the funnel analysis chart, they noticed a huge lift in conversions. The group that used the Activity Dashboard booked 24% more classes per week. Based on this success, Mindbody placed the new feature in the navigation bar to make it more noticeable.

• Build and Analyze a Funnel Analysis Chart Video , Amplitude
• Funnel Analysis and Its Use Cases Live Session , Amplitude
• In freemium marketing, product analytics are the difference between conversion and confusion , TechCrunch
• Don’t Throw Your Customers–And Your Business–Down The Funnel , Forbes
• Optimize Your Marketing Funnel With These Three Questions , Forbes
• Designing Customer Journeys for the Post-Pandemic World , Harvard Business Review

About the Author

More best practices.

Funnel Analysis: What It Is, benefits and insights to maximize conversions

Not every prospect will become a customer. However, low conversion rates could indicate you have a “leaky” marketing funnel. Prospects are dropping off at various customer journey stages before they convert.

The good news is that you can plug the leaks in your funnel and recover more sales. How? By conducting a funnel analysis—a method that reveals bottlenecks in the customer journey. 

In this in-depth guide, we’ll cover:

What funnel analysis is and the benefits of conducting

Different ways you can use a funnel analysis

How to get useful insights and steps to getting started

What is funnel analysis?

Funnel analysis is a method used in marketing and analytics to understand and optimize the steps that users or customers take during their journey toward a specific goal or conversion. The term "funnel" refers to the sequential stages that users go through, starting from the initial awareness stage to the final conversion or desired action.

What's the purpose of funnel analysis?

The primary purpose of funnel analysis is to identify and address bottlenecks or areas of improvement within the conversion process. By tracking and analyzing user behavior at each stage, businesses can gain insights into where users drop off, lose interest or face obstacles that prevent them from progressing further. This information helps businesses optimize their marketing strategies, user experience and conversion rates

For example, let’s say conversion rates for your signup pages are below the average rate of 4.3% . (Note that the average conversion rate is different for different industries, and you should know the benchmark rate for your own industry, the rate you want to beat). 

Analyzing how users progress from one stage in the funnel to the next can help you understand why your conversion rate might be low. Maybe users can’t enter their email addresses due to a technical issue, or the page isn’t optimized for mobile devices. These issues can cause users to drop off, but without a funnel analysis, it’s hard to know for sure.  

What are the benefits of a funnel analysis?

All digital customer journeys can benefit from funnel analysis. Some funnels are 3-4 steps, while others are much longer. For instance it could be a simple conversion funnel to go to a website, watch a short video and fill out a contact form. Or a funnel could involve more decision points, like a purchase. See below for an example.

A visitor takes the following steps:

Step 1: Goes to the website

Step 2: Clicks to a product page

Step 3: Adds that product to the shopping cart

Step 4: Clicks to the purchase checkout page

Step 5: Fills out the purchase form

Step 6: Completes the purchase

Conducting a funnel analysis allows you to:

Find drop off and friction points

Funnel analysis allows you to pinpoint specific stages where users are dropping off or experiencing difficulties. No matter whether it’s signing up for a trial period, requesting a demo or putting items in a shopping cart. Knowing when and where (and why) potential customers are leaving your website is critical data. By analyzing these bottlenecks, you can identify the reasons behind the drop-offs, such as confusing navigation, lengthy forms or technical issues. This insight enables you to optimize those stages and improve overall conversion rates .

Optimize user experiences

Understanding the user journey through funnel analysis helps you gain insight into how users interact with your website or mobile application. By analyzing user behavior, you can identify pain points, user preferences and areas where improvements can be made to enhance the overall user experience. This information can guide design changes, content improvements and feature enhancements.

Reveal technical errors

Drop-offs happen for many reasons, but one you may not know about until funnel analysis is technical errors in one or more steps. For example, if you’re getting a big drop-off at the last step, it could be that the link is broken or is directed to the wrong page. Or if users are backtracking in the funnel flow to the prior step, that indicates an issue.

Identifying and addressing these issues should be a top priority, especially since 72% of consumers say that poor site or app performance is the most frustrating issue online.

Make iterative improvements and data-led decisions

Funnel analysis provides a data-driven approach to decision making. By continuously analyzing, understanding and optimizing the user journey, you can make informed decisions based on real user data rather than assumptions. This iterative improvement process helps you make data-driven decisions to enhance user engagement, increase conversions and achieve your business goals.

Understand visitor demographics

Another important benefit of funnel analysis is surfacing who your potential buyers and customers are. Analyzing the sales funnel through the demographics lens can elicit powerful data to segment your audience into personas or different audiences. You can learn who your highest-converting customers are, create a different decision flow for certain segments or make other enhancements that leverage insights about specific groups of visitors.

Refine your messaging

A funnel analysis can help determine how well your messaging resonates with your audience. For example, if prospects are dropping off in the evaluation stage, adjusting your message to better convey the value of your product could increase engagement. Examples include testing new headlines, revising your call-to-actions (CTAs), or optimizing your forms .

Validate your designs

Over three-fourths of consumers (77%) say their top priority when transacting online is quickly accomplishing what they set out to do. Analyzing how users flow through your funnel and interact with your platform can help your product team evaluate how intuitive it is. It can also provide insights into the impact of new design changes on user behavior.

7 ways to use a funnel analysis

Customers who leave your funnel obviously won’t convert. And research shows that 54% of consumers will stop using a brand after a single bad experience. The average churn rate —the percentage of customers who stop doing business with a company—across all industries for software businesses is 4.1%. Customers who leave your funnel obviously won’t convert.

( Image Source )

Funnel analysis is a powerful tool with diverse applications. Here’s how to use a funnel analysis to both minimize churn and optimize the customer journey.

1. Increase conversion rates: Analyzing digital funnels can help find answers to get more conversions and reduce churn. It could be that you reduce or eliminate pop-ups along the way, show pricing upfront in the shopping cart, cut a step altogether or otherwise refine the flow. These all add up to an overall better experience for potential customers.

2. Optimize the customer journey: Conducting analysis for all of your website or app funnels can shape decision-making throughout the customer journey . Taking a holistic view, you can use this analysis to optimize each step of the user experience and make it easier for users to engage and convert at each touchpoint.

3. Measure marketing effectiveness: By analyzing how users move through your funnel, you can determine which marketing campaigns are most effective for driving conversions. This can help you optimize your marketing efforts and allocate your resources more effectively.

4. Identify trends in user behavior: Funnel analysis can help you evaluate trends in your visitors’ behavior, such as fluctuations in the conversion rate, or how much time users spend navigating through each funnel step. These insights can help you make data-driven decisions about your website or app's design and functionality.

5. Monitor performance over time: By tracking your funnel over time, you can monitor your website or app's performance and identify areas where it may be underperforming. According to Forbes, 47% of users will leave a website that takes more than 2 seconds to load, and a mobile site no more than 3 seconds. seconds.

And it’s not just time performance—61% of users expect to find what they’re looking for in under 5 seconds , so navigability certainly matters. Understanding whether users are dropping out out of your funnel due to performance issues can help you make proactive changes to improve your conversion rate and overall user experience.

6. Monitor user behaviors across different devices: An estimated 76% of US adults reported using a smartphone to shop online , while 69% have used a desktop and 28% have used a tablet. A funnel analysis can help you understand how the user experience varies across different devices, enabling you to optimize your strategies accordingly.

7. Guide your A/B testing efforts: A/B testing shows your users two versions of a web page and compares the results. The version that converts more users “wins” the test. Conducting a funnel analysis can help you develop a hypothesis and test different strategies to move more prospects to the next stage.

How to choose the right tool for completing a funnel analysis

The real power of funnel analytics lies beyond displaying the number of users progressing through a predefined flow. Google Analytics for instance can show the drop-off count at each step, but it doesn't provide the underlying reasons. Advanced tools, such as digital experience intelligence, provide the insights required to identify the root causes of problems and the additional context required to prioritize based on impact. Access to this level of insight enables faster issue resolution.

Here are some key features to look for:

Session replay captures the entire interaction the visitor went through on your website. Session replay is critical in identifying bugs, user struggles and UX design flaws. You can pinpoint sections to see clicks, keyboard entries, mouse movements and other actions. For mobile users, you can review their every tap, scroll, pinch and more.

Keep a look out for advanced functions where funnel creation is possible from within the session replay window itself.

Heatmaps are a well-established and popular web analytics tool. They provide a visual representation of the visitors’ activity and engagement on a website. There are many types of heatmaps. The most common ones are scroll maps, click maps and move maps. There are also mobile heatmaps to get a drill-down visual view of app activity.

Struggle analysis lets you identify friction points in different customer journey stages. It can alert you of potential issues like rage clicks, which often indicate errors like bugs, broken elements, and dead links.

Voice of the Silent (VoS) is another key feature to look for in a funnel analysis tool. It uses machine learning and natural language processing to help you understand how your users actually feel—something that’s not easy to gauge, considering that just 4% of users leave survey feedback .

VoS turns interactions across all sessions into quantifiable feedback, giving you a clearer picture of user sentiment. You can find, prioritize and fix sources of friction users experience without asking a single survey question.

Other advanced capabilities that enhance digital analytics insights:

Tagless data capture automatically tags every digital interaction, saving time and resources

Anomaly detection: Allows you to receive notifications if any behaviors deviate from normal patterns.

Retrospective analysis: By utilizing a tool with retrospective analysis, users can effectively explore and analyze data to gain valuable insights into past occurrences. No more waiting for your funnel to gather data--view the data from that specific funnel the second you hit publish

Revenue impact analysis provides a view as to the financial impact abandonment is having on your business

Browser and device analysis provides the context you need when investigating the cause of issues leading to funnel abandonment

Integration with third-party solutions boosts insights and relevance from your analytics

Privacy and compliance features to protect sensitive data and increase security

How to get useful insights from funnel analysis

You’ve set up your funnels, they’ve been live for a certain amount of time and it’s time to evaluate how they perform for engagement and conversion. Funnel analysis will give you the insights to start making improvements. You’ll be asking questions like:

How many users completed each step of the funnel and did they finish?

Was there a pattern in visitor drop-off behavior?

How long does the funnel take to get through?

Is this data that would benefit from A/B testing to further evaluate results?

This is where advanced digital analytics show their strength, saving time and effort while delivering actionable insights. Beyond drilling down into the data, you can quickly interpret user behavior , identify the root cause of struggles and errors, prioritize improvements by their business impact or segment specific audiences to learn more about their behaviors. Altogether, these features help you come to data-driven decisions for a better user experience–redefining what success looks like.

Here are some common examples of how using heatmaps or interaction maps, session replays and other digital analytics insights can lead to decreased abandonment and increased engagement and conversion:

Removing steps in the funnel

Change the order and location of key messages and CTAs

Swap large amounts of text with a shorter copy

Add pop-up windows or hovers for explanatory text

Change a form field from required to optional

Expand ad campaigns to increase funnel entry points

Real-world examples of using a funnel analysis

Below, we’ll examine how two companies conducted a funnel analysis to optimize customer journeys and generate more conversions.

Recovering more than £200,000 in revenue per quarter

Sainsury’s is a major retail corporation in the UK. The company discovered that 47.7% of its customers were dropping off at the checkout page, but it wasn’t clear why.

Conducting a funnel analysis revealed a technical issue. Customers couldn’t click an option to buy and collect a product in-store, causing many to simply exit the app.

After identifying and fixing the issue, Sainsbury’s recovered over £200,000 in lost revenue per quarter . Not only that, they were able to reduce costs and certainly improve the user experience.

Getting online bookings back on track with the help of funnel analysis and session replays

Classic Vacations is a luxury wholesaler of vacation rentals.

Agencies use their tools to book travel packages from resorts around the world. However, the product team noticed revenue was down 86% weekly. Their first step was identifying where users struggled in the checkout process.

Viewing session replays showed that users were stuck in the “Show property details” step. Details about vacation properties weren’t displaying properly, so agencies couldn’t complete their bookings. After identifying and fixing the issue, Classic Vacations was able to bring bookings back on track .

Getting started with funnel analysis

Follow these steps to get started with funnel analysis.

Define your strategy and goals: Clearly define the objectives you want to achieve with your website or mobile application. Identify the key actions or conversions that align with your business objectives. For example, it could be completing a purchase, signing up for a newsletter or filling out a form. Your funnel strategy will, of course, be driven by your industry, specific business goals and marketing tactics. But there are some common funnel requirements for all digital journeys that narrow the scope as you map out your funnel. Here is a sampling of questions that may be asked:

What do you want your visitor to do at the end of the conversion funnel?

What are the funnel metrics you’re tracking? (volume, churn, conversions, etc.)

Is it a B2B play nurturing for the long haul or fast B2C, like a travel purchase?

What audience segment is for this funnel? (prospect, new customer, returning customer)

Is the funnel nurturing leads in the sales pipeline?

Does this visitor need more education before making a purchase?

Does the visitor need social proof as part of the conversion journey?

…and many more.

Map out your funnels: Identify the critical user journeys or flows that lead to your defined goals. Break down these journeys into stages or steps, starting from the initial interaction to the final conversion. Each stage represents a milestone in the user's journey, such as a landing page visit, product selection or checkout process.

Set up tracking: Implement a robust analytics system to track user behavior at each stage of the funnel. Use event tracking, page view tracking or other relevant tracking methods to capture user actions and interactions. Ensure that the tracking is accurately implemented and aligned with your defined goals and funnel stages.

Analyze user behavior: Collect and analyze data from your tracking system to gain insights into user behavior within the funnel. Examine the conversion rates at each stage, identify drop-off points and understand user flow throughout the journey. Look for patterns, trends and areas of improvement.

Identify bottlenecks and optimization opportunities: Based on your analysis, identify stages in the funnel where users are dropping off or experiencing difficulties. Investigate the potential causes, such as usability issues, confusing navigation or technical errors. Use this information to optimize those stages and improve overall conversion rates.

Iterate and test: Continuously monitor and analyze the performance of your funnels. Implement A/B testing, user feedback or usability testing to validate improvements and iterate on your optimization efforts. Make data-driven decisions to enhance the user experience and maximize conversions.

Measure and refine: Regularly track and measure the performance of your funnels. Use key metrics such as conversion rates, drop-off rates and average time spent to evaluate the effectiveness of your optimizations. Refine your funnels based on the data and insights gathered, aiming for continuous improvement.

Pro tip: Use funnel alerts to stay informed about conversion rate changes. Act swiftly during issues and learn from positive improvements.

Any business can benefit from a funnel analysis, which can uncover potential bottlenecks in the customer journey, and what’s serving you well. Of course, you need the right tools to help you understand how users move through your funnel.

Glassbox’s digital experience intelligence (DXI) shows how users interact with your product. It automatically captures 100% of all digital events across your site and app, giving you the data you need to make data-driven decisions.

In addition to funnel analysis, you can read more here about all the ways you can achieve digital experience excellence.

Funnel analysis maps out and analyzes the journey your visitors go through on your website or app to understand which parts of the funnel are working well or need improvements. These insights can be used to optimize the funnel to increase traffic, convert visitors and retain customers.

What are the benefits of funnel analysis?

There are many benefits to conducting funnel analysis. Some major ones include:

Finding areas of friction and abandonment in the funnel to correct them

Uncovering hidden technical issues that you were unaware of

Understanding your audience personas and segments so you can better address their needs

How can funnel analysis be used as part of your digital strategy?

Funnel analysis can be used to:

Help increase conversion rates and reduce churn

Optimize the customer journey to make it easier to engage each step of the way

Measure marketing effectiveness to see which campaigns drive conversions

Identify behavior trends such as conversion rate fluctuations, time spent on pages, etc.

Monitor performance over time to track areas that are underperforming or working well

Asim Zaheer

Former Chief Marketing Officer, Glassbox

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The funnel technique in qualitative user research.

July 24, 2022 2022-07-24

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The funnel technique has been around since qualitative interviews emerged as a research method. This technique involves asking broad  open-ended questions  before gradually introducing more narrowly-scoped open-ended questions, as well as  closed questions . 

In This Article:

Why is it called the funnel technique, the funnel technique in user interviews, the funnel technique in qualitative usability tests.

This idea of  starting broad before getting more specific  is valuable in other types of studies besides user interviews. This technique can help you organize:

• Interview questions
• Followup questions
• Usability tasks
• Research in a multimethod study

This article discusses how the funnel technique can be used in  user interviews  and in  moderated usability tests . 

A funnel is broad at the top and narrow at the bottom, which makes it easy to pour a substance (for example, oil or rice) into a container with a narrow opening (for example, a bottle or jar). 

Similarly, the funnel technique in user research involves moving from broad to narrow — in other words, from general to specific. The funnel is a fitting metaphor because a user interview or usability-test session should start with broad, exploratory questions or tasks before introducing specific, narrowly scoped questions or tasks. 

The purpose of the funnel technique is to avoid influencing user behavior or perceptions as much as possible. When we ask specific questions or give specific tasks too early in a research session, we risk introducing bias and missing important data.

An  interview guide  for a user interview will usually consist of 5–8  open-ended questions  that get participants to share relevant stories or experiences. These are followed by followup questions, which can be open-ended or closed.

An interview should start with broad, open-ended questions like  Tell me about the last time you ordered movie tickets .

Starting with broad open-ended questions:

• Gets the participant comfortable with talking
• Allows the participant to begin sharing stories
• Generates lots of new, unanticipated information
• Avoids the researcher  priming  the participant

After the participant responds, the interviewer should ask open-ended followup questions (known as  probing questions ) to dig into areas of the participant’s response that the researcher wants to learn more about. These include questions like:

• Can you expand on that?
• What do you mean by that?
• How do you feel about that?
• Why do you think that?

The interviewer may also want to gather additional information and details that the participant omitted, by introducing closed questions, such as: 

• When did you see this movie?
• Did you go alone?
• How long was the movie?

For each main question prepared in the interview guide,  the interviewer is moving from broad open-ended questions to closed questions . With each new question in the guide, the funneling process repeats.

When we make use of the funnel technique, we allow space for us to  learn new things before gathering detail.  This approach to interviewing is the best way to build rapport and learn what users really think without priming them.

In qualitative usability testing, funneling can be used in: 

• Creating and ordering tasks
• Devising the sequence of followup questions after a participant completes a task

Funneling Tasks

The same process of moving from broad to specific can apply to constructing and ordering tasks for a qualitative usability test. Broad exploratory tasks — which allow us to learn how people do things on their own — should be given before specific, directed tasks that ask users to find or do something that they might not otherwise do.

Another metaphor for the funnel technique is a mouse in a maze. Imagine a researcher in a lab wants to see if a mouse can find a piece of cheese in a large maze. They might start off by giving the mouse the entire maze and seeing whether it finds the cheese. After some time, if the mouse hasn’t arrived at the cheese, they could slowly start closing off incorrect pathways, increasing the chances that the mouse will find the cheese.

In this metaphor, the mouse is the participant, and the cheese is the aspect of the design that we’re interested in studying. It’s better to first see if our participants get there on their own, but we might have to nudge them a bit.

If we started with task 3, and moved in the reverse order, we would prime participants on how to behave in task 1 and task 2. It’s likely that we would miss out on learning how they would do things on their own without prompting. Funneling tasks, by starting with broad exploratory tasks before introducing directed tasks, ensures you get valid data about behavior.

The funnel technique is the idea behind  stepped tasks . Stepped tasks are multistep tasks that start broad and then provide more specific instructions as necessary. 

For example, let’s imagine that we’re interested in studying the  comparison feature  on an ecommerce site. 

If we get to Task 4.2 in the stepped task example above, we might conclude that there are some discoverability or desirability issues with the feature. However, providing this level of specificity would allow us to make those conclusions while also getting a chance to see if there are any interaction-design problems with the feature itself.

Funneling in Followup Questions

In  qualitative usability tests , the facilitator will make use of the funnel technique when asking followup questions. For example, we might ask the following questions after the participant has finished a task:

In the above example, we are starting with broad, open-ended questions before narrowing the scope to specific, open-ended questions that relate to a UI element that we want more feedback on. 

We shouldn’t start with Question 3 and move in the reverse direction, because it’s always better if participants volunteer information unprompted. We’re hoping the participant will organically provide feedback without our specific direction, because unsolicited feedback is more likely to be the participant’s true opinion. Asking participants for feedback on specific elements can be risky — there’s always a chance that the participant will simply make up an opinion for the researcher. For example, if the participant said the filters were really helpful in response to question 1, we can be more confident that they really think so than if they gave us a similar response to question 3.

The funnel technique can be used when administering questions or tasks in user interviews or usability tests. Start with broad open-ended questions or tasks before introducing more specific questions or tasks. This approach helps to ensure that you don’t miss out on important information and you avoid prompting or priming participants too early.

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Kate Moran · 2 min

How to master the seven-step problem-solving process

In this episode of the McKinsey Podcast , Simon London speaks with Charles Conn, CEO of venture-capital firm Oxford Sciences Innovation, and McKinsey senior partner Hugo Sarrazin about the complexities of different problem-solving strategies.

Podcast transcript

Simon London: Hello, and welcome to this episode of the McKinsey Podcast , with me, Simon London. What’s the number-one skill you need to succeed professionally? Salesmanship, perhaps? Or a facility with statistics? Or maybe the ability to communicate crisply and clearly? Many would argue that at the very top of the list comes problem solving: that is, the ability to think through and come up with an optimal course of action to address any complex challenge—in business, in public policy, or indeed in life.

Looked at this way, it’s no surprise that McKinsey takes problem solving very seriously, testing for it during the recruiting process and then honing it, in McKinsey consultants, through immersion in a structured seven-step method. To discuss the art of problem solving, I sat down in California with McKinsey senior partner Hugo Sarrazin and also with Charles Conn. Charles is a former McKinsey partner, entrepreneur, executive, and coauthor of the book Bulletproof Problem Solving: The One Skill That Changes Everything [John Wiley & Sons, 2018].

Charles and Hugo, welcome to the podcast. Thank you for being here.

Hugo Sarrazin: Our pleasure.

Charles Conn: It’s terrific to be here.

Simon London: Problem solving is a really interesting piece of terminology. It could mean so many different things. I have a son who’s a teenage climber. They talk about solving problems. Climbing is problem solving. Charles, when you talk about problem solving, what are you talking about?

Charles Conn: For me, problem solving is the answer to the question “What should I do?” It’s interesting when there’s uncertainty and complexity, and when it’s meaningful because there are consequences. Your son’s climbing is a perfect example. There are consequences, and it’s complicated, and there’s uncertainty—can he make that grab? I think we can apply that same frame almost at any level. You can think about questions like “What town would I like to live in?” or “Should I put solar panels on my roof?”

You might think that’s a funny thing to apply problem solving to, but in my mind it’s not fundamentally different from business problem solving, which answers the question “What should my strategy be?” Or problem solving at the policy level: “How do we combat climate change?” “Should I support the local school bond?” I think these are all part and parcel of the same type of question, “What should I do?”

I’m a big fan of structured problem solving. By following steps, we can more clearly understand what problem it is we’re solving, what are the components of the problem that we’re solving, which components are the most important ones for us to pay attention to, which analytic techniques we should apply to those, and how we can synthesize what we’ve learned back into a compelling story. That’s all it is, at its heart.

I think sometimes when people think about seven steps, they assume that there’s a rigidity to this. That’s not it at all. It’s actually to give you the scope for creativity, which often doesn’t exist when your problem solving is muddled.

Simon London: You were just talking about the seven-step process. That’s what’s written down in the book, but it’s a very McKinsey process as well. Without getting too deep into the weeds, let’s go through the steps, one by one. You were just talking about problem definition as being a particularly important thing to get right first. That’s the first step. Hugo, tell us about that.

Hugo Sarrazin: It is surprising how often people jump past this step and make a bunch of assumptions. The most powerful thing is to step back and ask the basic questions—“What are we trying to solve? What are the constraints that exist? What are the dependencies?” Let’s make those explicit and really push the thinking and defining. At McKinsey, we spend an enormous amount of time in writing that little statement, and the statement, if you’re a logic purist, is great. You debate. “Is it an ‘or’? Is it an ‘and’? What’s the action verb?” Because all these specific words help you get to the heart of what matters.

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Simon London: So this is a concise problem statement.

Hugo Sarrazin: Yeah. It’s not like “Can we grow in Japan?” That’s interesting, but it is “What, specifically, are we trying to uncover in the growth of a product in Japan? Or a segment in Japan? Or a channel in Japan?” When you spend an enormous amount of time, in the first meeting of the different stakeholders, debating this and having different people put forward what they think the problem definition is, you realize that people have completely different views of why they’re here. That, to me, is the most important step.

Charles Conn: I would agree with that. For me, the problem context is critical. When we understand “What are the forces acting upon your decision maker? How quickly is the answer needed? With what precision is the answer needed? Are there areas that are off limits or areas where we would particularly like to find our solution? Is the decision maker open to exploring other areas?” then you not only become more efficient, and move toward what we call the critical path in problem solving, but you also make it so much more likely that you’re not going to waste your time or your decision maker’s time.

How often do especially bright young people run off with half of the idea about what the problem is and start collecting data and start building models—only to discover that they’ve really gone off half-cocked.

Hugo Sarrazin: Yeah.

Charles Conn: And in the wrong direction.

Simon London: OK. So step one—and there is a real art and a structure to it—is define the problem. Step two, Charles?

Charles Conn: My favorite step is step two, which is to use logic trees to disaggregate the problem. Every problem we’re solving has some complexity and some uncertainty in it. The only way that we can really get our team working on the problem is to take the problem apart into logical pieces.

What we find, of course, is that the way to disaggregate the problem often gives you an insight into the answer to the problem quite quickly. I love to do two or three different cuts at it, each one giving a bit of a different insight into what might be going wrong. By doing sensible disaggregations, using logic trees, we can figure out which parts of the problem we should be looking at, and we can assign those different parts to team members.

Simon London: What’s a good example of a logic tree on a sort of ratable problem?

Charles Conn: Maybe the easiest one is the classic profit tree. Almost in every business that I would take a look at, I would start with a profit or return-on-assets tree. In its simplest form, you have the components of revenue, which are price and quantity, and the components of cost, which are cost and quantity. Each of those can be broken out. Cost can be broken into variable cost and fixed cost. The components of price can be broken into what your pricing scheme is. That simple tree often provides insight into what’s going on in a business or what the difference is between that business and the competitors.

If we add the leg, which is “What’s the asset base or investment element?”—so profit divided by assets—then we can ask the question “Is the business using its investments sensibly?” whether that’s in stores or in manufacturing or in transportation assets. I hope we can see just how simple this is, even though we’re describing it in words.

When I went to work with Gordon Moore at the Moore Foundation, the problem that he asked us to look at was “How can we save Pacific salmon?” Now, that sounds like an impossible question, but it was amenable to precisely the same type of disaggregation and allowed us to organize what became a 15-year effort to improve the likelihood of good outcomes for Pacific salmon.

Simon London: Now, is there a danger that your logic tree can be impossibly large? This, I think, brings us onto the third step in the process, which is that you have to prioritize.

Charles Conn: Absolutely. The third step, which we also emphasize, along with good problem definition, is rigorous prioritization—we ask the questions “How important is this lever or this branch of the tree in the overall outcome that we seek to achieve? How much can I move that lever?” Obviously, we try and focus our efforts on ones that have a big impact on the problem and the ones that we have the ability to change. With salmon, ocean conditions turned out to be a big lever, but not one that we could adjust. We focused our attention on fish habitats and fish-harvesting practices, which were big levers that we could affect.

People spend a lot of time arguing about branches that are either not important or that none of us can change. We see it in the public square. When we deal with questions at the policy level—“Should you support the death penalty?” “How do we affect climate change?” “How can we uncover the causes and address homelessness?”—it’s even more important that we’re focusing on levers that are big and movable.

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Simon London: Let’s move swiftly on to step four. You’ve defined your problem, you disaggregate it, you prioritize where you want to analyze—what you want to really look at hard. Then you got to the work plan. Now, what does that mean in practice?

Hugo Sarrazin: Depending on what you’ve prioritized, there are many things you could do. It could be breaking the work among the team members so that people have a clear piece of the work to do. It could be defining the specific analyses that need to get done and executed, and being clear on time lines. There’s always a level-one answer, there’s a level-two answer, there’s a level-three answer. Without being too flippant, I can solve any problem during a good dinner with wine. It won’t have a whole lot of backing.

Simon London: Not going to have a lot of depth to it.

Hugo Sarrazin: No, but it may be useful as a starting point. If the stakes are not that high, that could be OK. If it’s really high stakes, you may need level three and have the whole model validated in three different ways. You need to find a work plan that reflects the level of precision, the time frame you have, and the stakeholders you need to bring along in the exercise.

Charles Conn: I love the way you’ve described that, because, again, some people think of problem solving as a linear thing, but of course what’s critical is that it’s iterative. As you say, you can solve the problem in one day or even one hour.

Charles Conn: We encourage our teams everywhere to do that. We call it the one-day answer or the one-hour answer. In work planning, we’re always iterating. Every time you see a 50-page work plan that stretches out to three months, you know it’s wrong. It will be outmoded very quickly by that learning process that you described. Iterative problem solving is a critical part of this. Sometimes, people think work planning sounds dull, but it isn’t. It’s how we know what’s expected of us and when we need to deliver it and how we’re progressing toward the answer. It’s also the place where we can deal with biases. Bias is a feature of every human decision-making process. If we design our team interactions intelligently, we can avoid the worst sort of biases.

Simon London: Here we’re talking about cognitive biases primarily, right? It’s not that I’m biased against you because of your accent or something. These are the cognitive biases that behavioral sciences have shown we all carry around, things like anchoring, overoptimism—these kinds of things.

Both: Yeah.

Charles Conn: Availability bias is the one that I’m always alert to. You think you’ve seen the problem before, and therefore what’s available is your previous conception of it—and we have to be most careful about that. In any human setting, we also have to be careful about biases that are based on hierarchies, sometimes called sunflower bias. I’m sure, Hugo, with your teams, you make sure that the youngest team members speak first. Not the oldest team members, because it’s easy for people to look at who’s senior and alter their own creative approaches.

Hugo Sarrazin: It’s helpful, at that moment—if someone is asserting a point of view—to ask the question “This was true in what context?” You’re trying to apply something that worked in one context to a different one. That can be deadly if the context has changed, and that’s why organizations struggle to change. You promote all these people because they did something that worked well in the past, and then there’s a disruption in the industry, and they keep doing what got them promoted even though the context has changed.

Simon London: Right. Right.

Hugo Sarrazin: So it’s the same thing in problem solving.

Charles Conn: And it’s why diversity in our teams is so important. It’s one of the best things about the world that we’re in now. We’re likely to have people from different socioeconomic, ethnic, and national backgrounds, each of whom sees problems from a slightly different perspective. It is therefore much more likely that the team will uncover a truly creative and clever approach to problem solving.

Simon London: Let’s move on to step five. You’ve done your work plan. Now you’ve actually got to do the analysis. The thing that strikes me here is that the range of tools that we have at our disposal now, of course, is just huge, particularly with advances in computation, advanced analytics. There’s so many things that you can apply here. Just talk about the analysis stage. How do you pick the right tools?

Charles Conn: For me, the most important thing is that we start with simple heuristics and explanatory statistics before we go off and use the big-gun tools. We need to understand the shape and scope of our problem before we start applying these massive and complex analytical approaches.

Simon London: Would you agree with that?

Hugo Sarrazin: I agree. I think there are so many wonderful heuristics. You need to start there before you go deep into the modeling exercise. There’s an interesting dynamic that’s happening, though. In some cases, for some types of problems, it is even better to set yourself up to maximize your learning. Your problem-solving methodology is test and learn, test and learn, test and learn, and iterate. That is a heuristic in itself, the A/B testing that is used in many parts of the world. So that’s a problem-solving methodology. It’s nothing different. It just uses technology and feedback loops in a fast way. The other one is exploratory data analysis. When you’re dealing with a large-scale problem, and there’s so much data, I can get to the heuristics that Charles was talking about through very clever visualization of data.

You test with your data. You need to set up an environment to do so, but don’t get caught up in neural-network modeling immediately. You’re testing, you’re checking—“Is the data right? Is it sound? Does it make sense?”—before you launch too far.

Simon London: You do hear these ideas—that if you have a big enough data set and enough algorithms, they’re going to find things that you just wouldn’t have spotted, find solutions that maybe you wouldn’t have thought of. Does machine learning sort of revolutionize the problem-solving process? Or are these actually just other tools in the toolbox for structured problem solving?

Charles Conn: It can be revolutionary. There are some areas in which the pattern recognition of large data sets and good algorithms can help us see things that we otherwise couldn’t see. But I do think it’s terribly important we don’t think that this particular technique is a substitute for superb problem solving, starting with good problem definition. Many people use machine learning without understanding algorithms that themselves can have biases built into them. Just as 20 years ago, when we were doing statistical analysis, we knew that we needed good model definition, we still need a good understanding of our algorithms and really good problem definition before we launch off into big data sets and unknown algorithms.

Simon London: Step six. You’ve done your analysis.

Charles Conn: I take six and seven together, and this is the place where young problem solvers often make a mistake. They’ve got their analysis, and they assume that’s the answer, and of course it isn’t the answer. The ability to synthesize the pieces that came out of the analysis and begin to weave those into a story that helps people answer the question “What should I do?” This is back to where we started. If we can’t synthesize, and we can’t tell a story, then our decision maker can’t find the answer to “What should I do?”

Simon London: But, again, these final steps are about motivating people to action, right?

Charles Conn: Yeah.

Simon London: I am slightly torn about the nomenclature of problem solving because it’s on paper, right? Until you motivate people to action, you actually haven’t solved anything.

Charles Conn: I love this question because I think decision-making theory, without a bias to action, is a waste of time. Everything in how I approach this is to help people take action that makes the world better.

Simon London: Hence, these are absolutely critical steps. If you don’t do this well, you’ve just got a bunch of analysis.

Charles Conn: We end up in exactly the same place where we started, which is people speaking across each other, past each other in the public square, rather than actually working together, shoulder to shoulder, to crack these important problems.

Simon London: In the real world, we have a lot of uncertainty—arguably, increasing uncertainty. How do good problem solvers deal with that?

Hugo Sarrazin: At every step of the process. In the problem definition, when you’re defining the context, you need to understand those sources of uncertainty and whether they’re important or not important. It becomes important in the definition of the tree.

You need to think carefully about the branches of the tree that are more certain and less certain as you define them. They don’t have equal weight just because they’ve got equal space on the page. Then, when you’re prioritizing, your prioritization approach may put more emphasis on things that have low probability but huge impact—or, vice versa, may put a lot of priority on things that are very likely and, hopefully, have a reasonable impact. You can introduce that along the way. When you come back to the synthesis, you just need to be nuanced about what you’re understanding, the likelihood.

Often, people lack humility in the way they make their recommendations: “This is the answer.” They’re very precise, and I think we would all be well-served to say, “This is a likely answer under the following sets of conditions” and then make the level of uncertainty clearer, if that is appropriate. It doesn’t mean you’re always in the gray zone; it doesn’t mean you don’t have a point of view. It just means that you can be explicit about the certainty of your answer when you make that recommendation.

Simon London: So it sounds like there is an underlying principle: “Acknowledge and embrace the uncertainty. Don’t pretend that it isn’t there. Be very clear about what the uncertainties are up front, and then build that into every step of the process.”

Hugo Sarrazin: Every step of the process.

Simon London: Yeah. We have just walked through a particular structured methodology for problem solving. But, of course, this is not the only structured methodology for problem solving. One that is also very well-known is design thinking, which comes at things very differently. So, Hugo, I know you have worked with a lot of designers. Just give us a very quick summary. Design thinking—what is it, and how does it relate?

Hugo Sarrazin: It starts with an incredible amount of empathy for the user and uses that to define the problem. It does pause and go out in the wild and spend an enormous amount of time seeing how people interact with objects, seeing the experience they’re getting, seeing the pain points or joy—and uses that to infer and define the problem.

Simon London: Problem definition, but out in the world.

Hugo Sarrazin: With an enormous amount of empathy. There’s a huge emphasis on empathy. Traditional, more classic problem solving is you define the problem based on an understanding of the situation. This one almost presupposes that we don’t know the problem until we go see it. The second thing is you need to come up with multiple scenarios or answers or ideas or concepts, and there’s a lot of divergent thinking initially. That’s slightly different, versus the prioritization, but not for long. Eventually, you need to kind of say, “OK, I’m going to converge again.” Then you go and you bring things back to the customer and get feedback and iterate. Then you rinse and repeat, rinse and repeat. There’s a lot of tactile building, along the way, of prototypes and things like that. It’s very iterative.

Simon London: So, Charles, are these complements or are these alternatives?

Charles Conn: I think they’re entirely complementary, and I think Hugo’s description is perfect. When we do problem definition well in classic problem solving, we are demonstrating the kind of empathy, at the very beginning of our problem, that design thinking asks us to approach. When we ideate—and that’s very similar to the disaggregation, prioritization, and work-planning steps—we do precisely the same thing, and often we use contrasting teams, so that we do have divergent thinking. The best teams allow divergent thinking to bump them off whatever their initial biases in problem solving are. For me, design thinking gives us a constant reminder of creativity, empathy, and the tactile nature of problem solving, but it’s absolutely complementary, not alternative.

Simon London: I think, in a world of cross-functional teams, an interesting question is do people with design-thinking backgrounds really work well together with classical problem solvers? How do you make that chemistry happen?

Hugo Sarrazin: Yeah, it is not easy when people have spent an enormous amount of time seeped in design thinking or user-centric design, whichever word you want to use. If the person who’s applying classic problem-solving methodology is very rigid and mechanical in the way they’re doing it, there could be an enormous amount of tension. If there’s not clarity in the role and not clarity in the process, I think having the two together can be, sometimes, problematic.

The second thing that happens often is that the artifacts the two methodologies try to gravitate toward can be different. Classic problem solving often gravitates toward a model; design thinking migrates toward a prototype. Rather than writing a big deck with all my supporting evidence, they’ll bring an example, a thing, and that feels different. Then you spend your time differently to achieve those two end products, so that’s another source of friction.

Now, I still think it can be an incredibly powerful thing to have the two—if there are the right people with the right mind-set, if there is a team that is explicit about the roles, if we’re clear about the kind of outcomes we are attempting to bring forward. There’s an enormous amount of collaborativeness and respect.

Simon London: But they have to respect each other’s methodology and be prepared to flex, maybe, a little bit, in how this process is going to work.

Hugo Sarrazin: Absolutely.

Simon London: The other area where, it strikes me, there could be a little bit of a different sort of friction is this whole concept of the day-one answer, which is what we were just talking about in classical problem solving. Now, you know that this is probably not going to be your final answer, but that’s how you begin to structure the problem. Whereas I would imagine your design thinkers—no, they’re going off to do their ethnographic research and get out into the field, potentially for a long time, before they come back with at least an initial hypothesis.

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Hugo Sarrazin: That is a great callout, and that’s another difference. Designers typically will like to soak into the situation and avoid converging too quickly. There’s optionality and exploring different options. There’s a strong belief that keeps the solution space wide enough that you can come up with more radical ideas. If there’s a large design team or many designers on the team, and you come on Friday and say, “What’s our week-one answer?” they’re going to struggle. They’re not going to be comfortable, naturally, to give that answer. It doesn’t mean they don’t have an answer; it’s just not where they are in their thinking process.

Simon London: I think we are, sadly, out of time for today. But Charles and Hugo, thank you so much.

Charles Conn: It was a pleasure to be here, Simon.

Hugo Sarrazin: It was a pleasure. Thank you.

Simon London: And thanks, as always, to you, our listeners, for tuning into this episode of the McKinsey Podcast . If you want to learn more about problem solving, you can find the book, Bulletproof Problem Solving: The One Skill That Changes Everything , online or order it through your local bookstore. To learn more about McKinsey, you can of course find us at McKinsey.com.

Charles Conn is CEO of Oxford Sciences Innovation and an alumnus of McKinsey’s Sydney office. Hugo Sarrazin is a senior partner in the Silicon Valley office, where Simon London, a member of McKinsey Publishing, is also based.

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What is Full Funnel Marketing?

In today’s busy and ever-evolving world, if you want your brand to succeed, you’ve got to stay ahead of the curve.

This is why many brands in just as many industries have turned to full funnel marketing strategies to better meet the diverse needs and behaviors of their target audience.

And it’s not just a passing trend, either. Full funnel marketing is a strategy that adapts to your customer’s changing fancies and allows your brand to engage, nurture, and convert leads more effectively than ever before!

So, if you’re ready to start your very own funnel campaign, then we’re here to cheer you on and help you get started.

Today’s blog is your comprehensive guide to understanding the full funnel marketing strategy!

Let’s dive in.

First off, full-funnel marketing is a holistic marketing approach that aims to target and engage your potential customers at every stage of their buying journey, from initial awareness to your cheerful brand advocate.

It works by adjusting your content marketing strategies in order to create and deliver engaging, relevant, and personalized content or customers experiences that guide your prospects through the entire marketing and sales funnel, nurturing them towards conversion and, ultimately, into loyal and happy brand advocates.

Done correctly, a full funnel approach helps your brand to better engage with and build lasting relationships with your audience!

The Marketing Funnel

So, what stages make up the marketing funnel?

The marketing funnel is usually split up into three different stages, depending on what phase of the user journey your potential customer is currently in:

Here are those stages now:

Stage 1. Top of Funnel (ToFu)

The top of the funnel is the largest stage, the awareness stage of the buyer’s journey, where your potential customers first become aware of a problem or a need.

Sometimes they’ll discover this need all on their own and sometimes they’ll need a gentle nudge from your content to help bring it to their attention. Once they discover that need, though, they’ve entered your funnel.

Your main focus at this stage should be aimed at educating these new prospects about the pain point or problem they’re having and how it’s something that has a solution.

Examples of ToFu Content

To better educate your audience about their need, try using some of the following content examples below:

• Digital Ads — Start your full-funnel marketing strategy with pay-per-click (PPC) ads on platforms like Google and social media. These targeted ads allow you to introduce potential customers to your brand as they actively search for solutions to their problems. Use metrics like search history, online behavior, and demographics to capture their attention.
• Blog Posts — Blog posts are a handy tool for building brand awareness and educating your potential customers. Use them to help your audience understand their challenges and offer potential solutions in an engaging and easy-to-read format. This content type can serve as an informative and entertaining introduction to your brand.
• Videos / How-Tos — Engage your audience with captivating videos and how-to content. Video marketing is extremely effective at capturing potential customers' attention, making them aware of your brand, and positioning your products or services as a future solution.
• Social Media Posts — Harness the power of social media to get your brand in front of your potential customers. Share engaging social media posts with your followers or reach out to prospects through a paid ad campaign. This approach not only increases your brand visibility but also provides an easy way for prospects to engage by liking or following your page.
• Infographics — Create visually appealing infographics to showcase solutions to common pain points. These graphics are easily shareable and help convey complex ideas in a visual and easy-to-understand format. They are a great way to pique the interest of potential clients.

Understanding how your ToFu content is performing is essential for optimizing your strategy and guiding more prospects through the rest of the funnel.

It’s important to get this stage right, so keep an eye on the following KPIs to gauge the effectiveness of your content:

• Website Traffic — The number of visitors to your website indicates the overall awareness of your brand and the effectiveness of your top-of-the-funnel content and strategies.
• Unique Visitors — This metric helps you understand how many different individuals are visiting your website,giving you insight into the size of your potential audience.
• Page Views — Monitoring page views shows which content is resonating with your audience and which topics generate the most interest.
• Click-Through Rate (CTR) — CTR measures the percentage of people who clicked on a link or ad. It helps with assessing the effectiveness of your call to action (CTA) and ad copy.
• Social Media Engagement — Track likes, shares, comments, and follows on your social media posts to gauge audience interaction and brand visibility.
• Bounce Rate — A high bounce rate may indicate that your landing page or content isn't effectively engaging visitors. Reducing bounce rates is a priority for ToFu marketing.
• Ad Impressions — For PPC campaigns, ad impressions show how many times your ads were displayed, indicating brand exposure.
• Social Media Follower Growth — The growth of your social media followers is a direct measure of increased brand awareness.
• Email Subscription Rate — Monitoring the number of email subscribers you gain from top-funnel content provides a valuable source for lead nurturing.
• Content Downloads — Track the number of downloads for content offers like eBooks, guides, and whitepapers, since this reveals how many prospects are interested in your educational resources.
• Referral Traffic — Measure the volume of traffic coming from external sources, which shows you how effectively you're leveraging referrals and partnerships.
• Lead Generation Rate — The rate at which you're converting website visitors into leads. This is a key KPI for ToFu effectiveness.
• Conversion Rate on Forms — If you use forms to capture leads, track the percentage of visitors who complete them.
• Brand Mentions — Monitor how often your brand is mentioned online. This can indicate growing awareness.
• Social Media Click-Through Rate — For social media ads, CTR provides insights into how effectively your ads are driving users to your website.
• Content Shareability — Assess how easily your top-funnel content can be shared on social media platforms.
• Ad Click-Through Rate — Specifically for PPC campaigns, this metric shows how well your ads encourage users to click and learn more.
• Inbound Links — Track how many other websites are linking to your content, improving your SEO and brand visibility.
• SEO Rankings — Monitor your search engine rankings for relevant keywords to evaluate your brand's visibility in organic search.
• Time on Page — Measure how long visitors stay on your pages to assess engagement levels with your content.

Stage 2. Middle of Funnel (MoFu)

The middle of the funnel is the consideration stage of the buyer’s journey, the stage where your prospects have identified their problem and are now actively looking for a solution.

The middle of the funnel is a smaller stage as your prospects begin to narrow down. 

At this stage, your main focus should be on giving your prospects valuable information about your products and services, positioning them as a solution to your potential customer’s problem they discovered in Stage 1. 

Examples of MoFu Content

Here are some great ways to educate your clients and give them the resources they need to help them make an informed decision:

• White Papers — White papers are in-depth documents that are ideal for explaining complex products or services. They offer valuable insights and comprehensive information to help potential customers make informed decisions about your offerings.
• Case Studies — Showcase success stories from previous customers who have already benefited from your products or services. Case studies provide real-world examples of problem-solving, customer satisfaction, and the positive outcomes a customer can expect post-purchase.
• Product Guides / Specs — Product guides or specifications are essential for potential customers researching your offerings. They provide detailed information, particularly relevant for tech products, enabling prospects to make well-informed purchasing decisions.
• Video / How-Tos — Videos and how-to guides play a crucial role in the middle of the funnel. They offer an engaging and more in-depth explanation of your products or services. Include comparisons with competitors to help your potential customers grasp the unique value your brand provides.

As your prospects narrow down and transition from the awareness stage to the consideration stage, it’s vital that you track how well you nurture these leads. Those prospects are considering your brand, so keep a close eye on the following conversions to help you get them to the next stage:

• Conversion Rate — The percentage of MoFu prospects who take a specific action, such as downloading a resource, signing up for a webinar, or requesting a demo. This indicates your content’s ability to persuade potential customers to engage with your brand.
• Click-Through Rate (CTR) — The ratio of clicks on your CTA to the total number of prospects in the MoFu. This measures the appeal of your CTAs and the level of interest generated by your content.
• Marketing Qualified Leads (MQLs) — The number of prospects in the MoFu who meet specific criteria, indicating they are more likely to become customers. MQLs help you identify potential customers showing interest and readiness to engage with sales.
• Email Engagement Metrics — Watch metrics like open rates, click-through rates, and unsubscribe rates for emails targeting MoFu prospects. Knowing these metrics help you evaluate the effectiveness of your email marketing campaign in nurturing potential customers.
• Webinar or Event Registrations — The number of MoFu prospects who register for webinars, events, or online seminars. This number reflects the level of interest in deeper, educational content.
• Lead Scoring Changes — Changes in lead scores that indicate prospects' movement through the middle of the funnel. This helps track prospects' evolving engagement and interest levels.
• Content Engagement Metrics — Metrics such as time spent on specific content, number of pages viewed, and interactions with downloadable resources can help assess the effectiveness of your content in keeping your prospects engaged.
• Marketing Automation Metrics — Metrics specific to marketing automation platforms, such as workflow completion rates, personalization effectiveness, and A/B test results measure how well your marketing automation is nurturing and engaging MoFu prospects.
• Social Media Engagement — Metrics like likes, shares, and comments on MoFu-focused social media content can indicate the impact of social media efforts on engaging potential customers.
• Survey Responses —Number of MoFu prospects who complete surveys or feedback forms. Survey responses pull double duty as they both gather valuable insights from your prospects and measure their willingness to provide that feedback.

Bottom of Funnel (BoFu)

At the decision stage, your prospects know their problem, have the information they need, and are ready to make a purchase decision.

This is what you’ve been waiting for! The goal here should be to give your prospects information that helps them choose your products and services as a solution over your competitors.

Examples of BoFu Content

Show your prospects why they should choose your products or services over your competitors with the right content that showcases your unique value!

Here are some ways to do that:

• Product Demonstrations — Offering in-depth product demonstrations can help your prospect get a closer look at how your product or service works. This can be a powerful tool for decision-making!
• Customer Testimonials — Showcase success stories from happy customers. These testimonials can provide social proof and reassure prospects that others have benefited from your offerings.
• Free Trials or Demos — Provide prospects with the opportunity to try out your product or service before they commit to a purchase. This helps build trust and confidence.
• Consultations — Offer free consultations to understand the prospect's needs and guide them toward the most suitable solution. It's a personalized approach to help you close the deal.
• Pricing Information — Provide transparent pricing information so that prospects can make informed decisions about whether your product or service fits their budget.
• Comparison Guides — Offer content that compares your offerings to those of your competitors, highlighting the advantages of choosing your brand.
• Case Studies — Show how your product or service has solved specific problems for other customers. These real-world examples make for highly convincing content.
• FAQs — Address common questions and concerns that prospects may have, reducing any uncertainties they might have about your offerings.
• Guarantees or Warranties — Clearly outline any guarantees or warranties that come with your product or service to ease any lingering doubts.
• Special Offers — Present any limited-time offers, discounts, or incentives to encourage prospects to make a purchase.
• Closing the Sale — Provide clear and compelling CTAs that encourage prospects to take the final step, such as "Buy Now" or "Get Started."

This is the stage where your prospect converts into a customer. Fine-tuning your strategies to more effectively get your prospects to the finish line is key here.

Here are the KPIs you should keep an eye on:

• Conversion Rate — Measure the percentage of prospects who take the desired action, such as making a purchase or requesting a demo.
• Sales Revenue — Track the total revenue generated from bottom-of-the-funnel conversions.
• Customer Acquisition Cost (CAC) — Calculate the cost associated with acquiring a new customer, including marketing and sales expenses.
• Customer Lifetime Value (CLV) — Determine the total value a customer is expected to bring to your business over their entire relationship with you.
• Purchase Frequency — Monitor how often customers make repeat purchases or engage with your business.
• Customer Retention Rate — Measure the percentage of customers who continue to do business with you over time.
• Churn Rate — Track the rate at which customers stop using your product or service.
• Average Deal Size — Calculate the average value of deals closed at the bottom of the funnel.
• Lead-to-Customer Conversion Rate — Evaluate the percentage of leads that progress to become paying customers.
• Return on Investment (ROI) — Assess the financial return on your marketing and sales efforts.
• Upsell and Cross-Sell Rate — Analyze the success of upselling or cross-selling additional products or services to existing customers.
• Customer Satisfaction — Measure the level of satisfaction among customers who have converted and provide feedback to make improvements.
• Referral Rate — Track the number of referrals generated by satisfied customers.
• Net Promoter Score (NPS) — Gauge the willingness of customers to recommend your business to others.
• Repeat Purchase Rate — Calculate the percentage of customers who make multiple purchases.

Bonus: Post-Conversion

After converting, the journey doesn’t end!

You should still continue to engage your customers post-conversion to foster a long-lasting relationship and encourage repeat purchases and brand advocacy.

Content here should focus on post-purchase support, customer service, gathering feedback, and encouraging loyalty, referrals, or upsells.

Examples of Post-Conversion Content

Since your prospect has made the leap and converted into a customer, your content here should focus on retention and keeping your customer happy and satisfied.

Here’s how you can do it:

• Satisfaction Surveys — Demonstrate your commitment to customer satisfaction by regularly seeking feedback through surveys. This proactive approach not only maintains communication but also refines your services to better address your audience's needs.
• Exclusive Offers — Make your customers feel valued and special by extending exclusive offers or presenting opportunities for upselling and cross-selling. These tailored promotions can encourage repeat purchases and reinforce customer loyalty.
• Product Guides — Equip your customers with the knowledge they need to make the most of your products or services. Providing comprehensive product guides ensures your customers have the support they require and reinforces your commitment to their success.

Post-Conversion KPIs

To gauge the effectiveness of your post-conversion content, keep an eye on the following KPIs:

• Customer Satisfaction — Measure customer happiness and gather feedback to assess the quality of their post-purchase experience.
• Customer Retention Rate — Calculate the percentage of customers who continue to do business with you after their initial purchase.
• Net Promoter Score (NPS) — Assess the likelihood of your customers recommending your brand to others, indicating their level of satisfaction and loyalty.
• Repeat Purchase Rate — Track how many customers make additional purchases after their initial conversion.
• Referral Rate — Monitor the number of new customers acquired through referrals from your existing customer base.
• Upsell and Cross-sell Rate — Evaluate the success of upselling and cross-selling efforts to existing customers.
• Customer Lifetime Value (CLV) — Calculate the long-term value of a customer relationship to assess their financial contribution to your business.

How to Create a Full Funnel Strategy in 6 Steps

If you’re convinced that a full funnel approach is the way to go (and you should be!) then here are the steps that you can take to create a winning full funnel strategy for your next campaign.

Step 1: Set Your Goals

Before you start anything, you’ll want to set some goals. Having clear and measurable goals is essential for providing direction and motivation for you and your team.

So, what is it that you want this campaign to achieve at each stage of the funnel? What is the desired action that your funnel is leading to?

Be sure that whatever goals you choose, they’re realistic and aligned with your overall business objectives!

Step 2: Choose your KPIs

Once you decide on your goals, you’ll need to know how to best track your progress as you and your team work toward those goals.

Select the KPIs that align best with the goals you’re working on. Each campaign and brand are different, but typically the KPIs to track for a marketing campaign are things like conversion rates, click-through rates, customer retention rates, and amount of revenue generated.

Refer to the KPIs listed above for more info!

Step 3: Map the User Journey

You’ve got your goals and you’ve got the KPIs you’ll be using to measure them, so now it’s time to map out the user journey !

The stages of the customer journey aren’t always linear, but they typically go like this:

• Awareness (Your First Hello) — At this stage, your lead has just become aware of your brand. Maybe they clicked on a well-placed ad, or perhaps they stumbled upon your website or discovered your products or services on social media.
• Consideration (Getting to Know Each Other) — In this stage, your prospect starts to dig deeper. They’ll start examining determining factors like customer service and pricing and start scouring your reviews and comparing your offerings to your competitors’.
• Conversion (It’s a Match!) — Your prospect has finished comparing and researching and chooses you by taking the desired action. Hooray!
• Advocacy (Happily Ever After) — After converting, your customer still relies on you for support and future purchases! Providing a positive post-purchase experience is the key to transforming your customer into a loyal brand advocate who happily shares your content on social media, talks you up to family and friends, leaves glowing reviews, and even sends you user-generated content!

So, what is it that your customers need from you at each stage of their journey? To help you better understand your customers, it’s very helpful to have your marketing and sales team lay out user personas.

If you’re not quite sure what a user persona is or how to create one, then check out our recent user persona blog for a step-by-step guide!

Step 4: Create Compelling Content

Now that you know what your potential customer is looking for, you’ll need to create compelling content that is designed to engage them at each stage of their journey.

Have your creative team whip up educational, informative, and, yes, entertaining content that is tailor-made for each consideration stage.

It’s helpful at this stage (and the next) to segment your audience as well. Splitting up your market by demographic, source of visit, behavior, etc. makes it easier to know the type of content that works best and the messaging that resonates most effectively.

And don’t forget that your team doesn’t have to be solely responsible for content creation! 

Encourage your users in the advocacy stage to create that user-generated content for your socials, landing page, and website!

Step 5: Choose the Right Marketing Channels

Once you have some sweet, sweet content, you’ll need to take another look at your user personas to decide what distribution channels would be most effective in reaching your audience.

Does your audience hang out on TikTok? Do they scroll through LinkedIn and Facebook during their lunch break? Do they enjoy reading blogs? Are YouTube videos the way to go?

Whatever it is, choose the distribution channels that work best and make sure that your content and messaging are consistent across them all.

Step 6: Monitor Your Performance

Once your campaign has launched, don’t waste time! Get to monitoring your performance as soon as you can.

Keeping track of your chosen KPIs will give you a clear picture of how your campaign is performing and whether certain aspects are having the desired effect.  And if something isn’t performing as well as you’d like, no worries! 

Whether it’s subject lines , content, timing, or CTAs, simply adjust as needed to optimize your campaign and achieve your goals.

Benefits of Using a Full Funnel Strategy

Implementing a full funnel strategy ensures that your prospects receive the right content and information at the right time.

By aligning your marketing efforts across the entire funnel, instead of a scattershot approach, you can more effectively guide your customers through your marketing funnel, drive conversions, and foster long-term customer relationships. 

Here are some additional benefits:

• Increased Sales and Revenue — By addressing customers at all stages of the funnel, you have more opportunities to convert prospects into paying customers, resulting in increased sales and revenue.
• Improved Customer Engagement  — Engaging customers with relevant content throughout their journey fosters stronger connections and brand loyalty.
• Better Targeting  — Full-funnel strategies allow for more precise targeting, as you tailor content to where customers are in the buying process.
• Enhanced Customer Experience  — Providing the right information at the right time improves the overall customer experience and satisfaction.
• Reduced Wasted Resources  — By targeting only those who are genuinely interested in your products or services, you can avoid wasting resources on unqualified leads.
• Data-Driven Decision-Making  — Full-funnel marketing generates valuable data and insights, helping you make informed decisions to optimize your strategy.
• Improved Marketing ROI — By efficiently guiding prospects through the funnel, you can achieve a higher return on investment (ROI) for your marketing efforts.
• Competitive Advantage  — Implementing a full-funnel strategy can set your business apart from competitors who focus solely on one part of the funnel.
• Better Sales Alignment — Sales teams benefit from better-qualified leads and a smoother handoff from marketing, resulting in improved sales processes.
• Long-Term Customer Relationships — Full-funnel marketing isn't just about conversions; it's about building lasting relationships with customers, which can lead to repeat business and referrals.

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Introducing Your Full Funnel Experts

If after reading through this list, you’ve come away with the idea that a full funnel marketing strategy is just what your brand needs, then that’s great.

If you’ve also come away with the idea that creating content and implementing these strategies will take a wider skill set and more manpower than your brand can give, then that’s okay too!

Because we have a solution.

Partnering with Designity is a cost-effective way to plan and launch a full funnel marketing strategy to help your brand grow!

Designity will pair you with an experienced Creative Director who will act as project manager and your single point of contact. They’re ready and willing to learn about your brand and your goals and help you plan a winning strategy for 2024.

And with the guidance of your Creative Director and a talent pool made up of the top 3% of US-based creative talent, you’ll soon have top-notch copywriters, designers, web developers, digital marketers, animators, and more completing the engaging content to help your strategy succeed!

Why not have a look at our portfolio and see if our style vibes with your brand? When you’re ready, book a demo call today.

Give us a test drive with a 2-week, no-obligation trial and see if Designity isn’t just the full funnel marketing partner that your brand is looking for.

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Funnel Analysis: What it is & How to Conduct One

Using funnel analysis, companies can identify untapped possibilities to enhance conversion rates. It helps them detect the abandonment areas on their sites and discover ways to maximize their traffic.

Analyzing and improving the marketing funnel can help you comprehend the efficacy of your marketing efforts and plans for client acquisition and retention.

This enables you to determine where visitors are leaving your site, allowing you to make improvements and increase conversion rates. This blog will demonstrate the conducting procedure. But first, you may think, what is it exactly?

What is Funnel Analysis?

In funnel analysis, the actions of users are visualized and mapped. With the help of a funnel, you can see the different stages of the customer’s journey. You can track how people get to each part of the funnel and where they leave.

Because they enable companies to learn what hinders users from achieving the aim of their website, funnels are an effective piece of marketing solution. 

You will also be able to watch visitors’ interactions with your website as they navigate it, as well as observe how many people exit at each point of the sales funnels. 

This will allow you to locate issues and determine how to improve the customer experience .

How to Conduct Funnel Analysis

Now that you are familiar with funnel analysis, the next topic we will cover is the procedure that must be followed to carry it out.

Map the ideal purchasing procedure.

The funnel map should be the first step in your funnel analysis.

To identify areas for improvement, you must plan out all the stages and variables that will be monitored. Before converting, how would you want customers to navigate the research and decision-making steps?

Or, how does your sales staff locate and cultivate clients through email prospecting?

Customer journey maps to aid in defining the objectives of a campaign. They may also give you vital information to understand how prospects and consumers connect with your brand and how they behave.

KPIs should be monitored.

Once you’ve identified your ideal purchasing path, you should begin tracking the Key Performance Indicators and success metrics. However, let’s rewind a little. How do you choose your key performance indicators?

The following are typical KPIs to track:

• Lead development
• Lead churning
• Time to convert
• Sales process metrics
• Customer lifetime value

There are just a handful of sales funnel metrics you need to monitor.

Tracking your funnel’s KPIs is vital for analyzing the pipeline’s overall health and resolving issues. Once you’ve identified the KPIs crucial to your firm’s success, assess if you’re meeting those objectives.

Understanding customer behavior.

Using user behavior analytics, you can track how people interact with your brand. You want to comprehend user encounters and determine pain spots.

Get as much pertinent information as possible to better comprehend user behavior. The information offered by technologies such as Google Analytics, for instance, may provide you with significant insights on how to build your website, depending on your visitors’ actions.

This information may be combined with CRM-collected data points. For instance, you can monitor recipients opening your email and visiting your website.

Try to acquire as much relevant information as possible from eligible data points. The more information you can get, the more probable it is that you will be able to spot issues and create solutions that reduce marketing funnel leaks.

Identify issues at each step of the funnel.

Integrating the insights acquired from tracking your KPI for each funnel level with relevant information may spot issues at each funnel stage. Then, give a numerical number to each issue you’ve identified.

A “to-do” list may be created by prioritizing things in order of priority. This is the list generated by your funnel analysis.

Then, you may examine the gaps in your funnel, determine the reason, and remedy the problem.

By examining and assessing the significant drop-off points throughout your funnel, your total conversion rate should increase. Keep in mind that this is an evolving procedure. Make adjustments, evaluate the outcomes, and then take necessary action.

Make use of the funnel comparison.

When doing a funnel analysis, you may take the extra step of comparing your funnel to a rival. A funnel comparison might give insight into how competitors or individuals with a comparable funnel to yours are attempting to produce conversions.

A comparison of funnels may reveal several valuable pieces of information. However, it is doubtful that you would get significant information on the exchange rate at every funnel level.

Funnel analysis to figure out why you’re losing conversions is effective. It assists you in determining when your website visitors leave so that you may concentrate your efforts in the most effective way possible.

Suppose your conversion rate is poor or your visitor count is meager. In that case, something is wrong with your funnel, and you should start improving it now. It would be best if you tracked various funnel metrics to see how effectively it’s functioning for this objective.

We defined funnel analysis and demonstrated how to do it in this blog.

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What is Funnel Analysis?

• Tomi Mester
• April 14, 2016

Funnel analysis is a powerful analytics method that shows visually the conversion between the most important steps of the user journey. It helps you understand what percent of your users stay with you or churn at a given step. Thus every online business can take advantage of it.

A simple funnel visualization looks like this:

There are several parts in your business where you can apply this method. But without any doubt, these are the three most typical funnel analysis types:

• Onboarding funnel analysis
• Sales funnel analysis
• Marketing funnel analysis

But how does that work in practice?

What are the biggest questions and roadblocks when you create your first funnel?

How could you extract actionable insights from it?

How can you create it for yourself?

In this article I collected all my best practices for you.

What is funnel analysis good for? When should you use it?

Funnel analysis is typically useful if you want to map out a linear user journey .

As I explained, it is about going through and calculating the conversion between the different steps – to understand how many users reached a certain point of a given process.

The complexity can differ from project to project:

1) It can be a simpler thing.

Like filling out a registration form…

2) But you can also map out more complex processes.

Like the onboarding process of that note-taking app that I showed you in the introduction.

3) And you can measure your whole product end-to-end…

From the first landing page visit to the point of purchase and further…

In each case the keyword is linearity.

With funnel analysis you try to model processes where users can reach their goal via a relatively straightforward path.

Take a simple funnel analysis example of an e-commerce business. In this case, the typical customer journey looks like:

• STEP #1: Visiting the landing page.
• STEP #2: Browsing through the products.
• STEP #3: Visiting a specific product.
• STEP #4: Adding the specific product to the cart.
• STEP #5: Filling out the purchase form.
• STEP #6: Confirming the order.
• STEP #7: Payment.
• STEP #8: Visiting the “Thank you for your purchase” page.

This is a classic sales funnel. It’s linear, right?

But wait! The customer journey is never this straightforward… How can I apply funnel analysis then?

One thing is very important to understand:

Funnel analysis maps out the experience of the users and you measure their development .

Looking back at the previous e-commerce sales funnel example: It’s quite common that users browse many different products at step #2 and step #3 before they go to step #4. Regardless, you have to count these multiple product page visits as one.

Always think in “level-ups!”

If someone added a product to the cart, she reached step #4, and the goal will then be to get the user to step #5. If someone adds 80 products to her cart, you only count it as one at step #4.

Funnel analysis is not for measuring the average number of purchased products (there are other analytics methods for that) but the development of your users.

This thinking process applies for SaaS (software-as-a-service) startups and for mobile apps, too – not just for e-commerce businesses.

A simple funnel analysis framework that you can quickly apply at your online business

When you get started with funnel analysis in your business I recommend following this model:

It’s called the AARRR model (invented by Dave McClure) and with simple modifications it applies to most online businesses.

It says that a user goes through these typical five steps when using your product or service:

• STEP 1. They land on your website (Acquisition)
• STEP 2. They start using your product (Activation)
• STEP 3. They return to the website/product (Retention)
• STEP 4. They make a purchase (Revenue)
• STEP 5. They refer the page to friends (Referral).

Well, of course, you will need some common sense to translate this to your business. Maybe you won’t have all the steps or the exact order of them might differ. But I trust you there. Use common sense and translate this so it works for you.

Note: this model will help you kick off your first funnel analysis project. Later on, when more data flows in and when you become more expert on the topic, you can refine your funnel by calculating correlations between the steps. As you get more and more data-driven, your funnel will be more data-driven as well – so you can replace common sense with facts. But let’s get back to that later.

How to create your first funnel analysis?

Step #1: define the steps of your funnel.

For ease of understanding, I would suggest coming up with 4 to 8 funnel steps. If you have a lot more, you risk getting lost in the data; if you have a lot less, well… then you don’t have a funnel. 🙂

Note: you can always create micro-funnels. For example, you run marketing funnel analysis across your whole website in which one step is registration. Then the process of registration can have a separated sub-funnel. This logically will be built into your main funnel, but when it comes to funnel visualization, it’s worth separating them, so you don’t get distracted.

Step #2: Pick the tool you’ll use!

If you are a regular reader of my blog, you know that I prefer tools that you build yourself (in Python or SQL) over using third-party tools (e.g. Google Analytics).

But I have to admit, in the beginning, when you don’t have that many resources, these smart tools can be handy – especially when you are just kicking off your first analytics projects.

Here are a few tools that have built-in funnel analytics features:

• Google Analytics (e.g. using goal settings, or enhanced ecommerce settings)
• Hotjar (it’s originally for creating website heatmaps but they also have built-in funnel metrics)
• Mixpanel (note that I personally have had very bad experiences with Mixpanel, so I can’t strictly recommend it.)

As your business’ data maturity grows, sooner or later you will realize that these third-party tools are not the best for the job. (For many reasons – here ‘s an article about that.) That’s the point where most companies decide to build their own tools – and their first self-implemented funnel analysis.

Note: You can easily write the code for it in SQL, Python or bash and you can create your funnel visualization in Tableau or in Google Data Studio . (We do exactly that in one of the tasks in my 6-week Junior Data Scientist course .)

Step #3: Time for funnel visualization…

Once you are done with all of the above, choose the simplest and easiest to understand funnel visualization. So NOT this:

And not this:

And, only if it’s a must, then this:

The simplest and the best funnel visualization is the classy bar chart.

Yes: nothing fancy.

It’s no accident that I picked this as an example above.

I highly recommend using bar charts and nothing else for visualizing funnels!

How can you get actionable insights from funnel analyses?

This is a key question.

Each online research and data analysis is done so you can make changes and improvements to create a better user experience!

But how can you get actionable insights from funnel analyses?

There are 3 major ways.

#1 The first one is the so-called “bottle-neck-check”.

Here you are looking for where most of your users churn. If you see that during registration everyone provides her name, email address and password, but almost everyone disappears at captcha, then you can suspect that there is a problem there (e.g. captcha is not readable).

But of course, the decision is never that simple. There are steps where you actually expect your users to churn. E.g. entering bank card details during check-out comes always with a big drop. So you should not search for the “bottleneck” where most users disappear in absolute numbers, but where the churn is the highest relative to your expectations . (Your expectations could be based on many things. You can use “common sense,” but using market benchmarks or historical data is more recommended).

#2 Another metric I like to take a look at is the time-delay between the different funnel steps.

How much time it takes for someone to add a product to her cart, starting from the first visit on the landing page… This could tell you a lot about your product and your communication as well.

E.g. for a customer of yours, deciding to purchase a $1000 smartphone will never be as quick as buying a $5 toothbrush. But if you provide enough information (good communication, good product images), you will help your users to make better decisions faster.

#3 The third recommended funnel analysis method is segmentation.

If you can find user-segments who are more successful (have better conversion numbers) at certain steps than others, then you instantly have great insights into who to target in the future, as well as into why other users may have gotten stuck at certain steps.

For example, if a jewellery e-commerce store sees that from their audience men buy jewelry for women with a very high conversion rate and women are shopping around but never buy anything: then it may be worthwhile to think about changing their target audience and message to something like “dear husbands, buy your partners some jewelry…”

Funnel analysis example at a startup (expert’s opinion)

Andras Balogh shared some expert opinions with me on how they are doing marketing funnel analysis and onboarding at Prezi. Here’s a short portion of the full interview:

“But what can you do with your funnel?

Definitely not starting to heal the top of the funnel so more people can come in through there. It’s not necessarily the best solution if you begin to fill the largest hole between two steps, either. I think the best option is if we begin our work at the bottom of the funnel. Because if you begin to pack users to the top of the funnel (e.g. with Google AdWords or Facebook Ads), those will churn anyway. And those you load to the top and drop out will never come back. That’s a wasted user.

So it’s best to spend your time on those you know love your product and have tried many of your products. Let’s see what can help them and heal the bottom of the funnel for them. You don’t want to work with those who come and just take a peek at your product. So you gradually fix your funnel upwards, and when it has reached a certain “thickness” where you say “okay, this works,” then you can start working with larger marketing costs and bringing in more users.”

Okay, this was it: Everything you need to know to get started with funnel analysis.

Let me summarize it!

• Funnel analysis is a great tool to measure the user journey, the conversion and the development of your users – step by step.
• When you set one up, define 4-8 steps and create a funnel visualization that’s easy to understand!
• Extract insights! Check at which step most people churn, and which segment is the strongest!
• If you want to learn more about how to become a data scientist, take my 50-minute video course: How to Become a Data Scientist.  (It’s free!)
• Also check out my 6-week online course: The Junior Data Scientist’s First Month video course.

Cheers, Tomi Mester

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Demand Gen: Growth Unleashed.

Funnel Analysis: How to Spot and Resolve Drop-Off Points

Ron Sela / Last updated: September 21, 2023

Funnel analysis  gives businesses crucial insights into the customer journey and sales process. It pinpoints where potential customers are dropping off, allowing them to identify issues and optimize activities.

Breaking down the sales funnel brings transparency to what is and isn’t working at each phase. With it, businesses better understand areas requiring more resources or adjustment.

Basically, you need something that sheds light on hard-to-track efforts like brand awareness by providing estimates of total leads vs. website visits vs. conversions, for instance.

A thorough funnel analysis empowers data-driven decision-making by quantifying cause-and-effect relationships. It maximizes funnel health and sales effectiveness through informed strategy adjustments.

Don’t know where to start? You’re in the right place. We’ll guide you through the basics, why it matters, and how to set up and analyze your own funnel. Dive in, and let’s get started.

Table of Contents

Key Takeaways

• Funnel analysis provides businesses with invaluable insights into customer behavior and the effectiveness of marketing and sales strategies. By pinpointing drop-off points and tracking user interactions, businesses can identify areas for improvement and optimize their activities.
• Through funnel analysis, businesses can make informed decisions backed by concrete data rather than relying on gut feelings or assumptions. This approach enables them to adjust marketing strategies, allocate resources effectively, and focus on areas with the most potential for improvement.
• Implementing funnel analysis allows businesses to continuously improve their performance, boost conversion rates, and increase revenue. By identifying successes and failures, adapting strategies, and optimizing the customer journey, businesses can foster growth and maintain a competitive edge in the market.

What is Funnel Analysis

Funnel analysis is a systematic approach businesses use to dissect and optimize the customer journey through various stages, from initial awareness to conversion.

It involves tracking and analyzing customer behavior at each sales funnel stage to gain insights into marketing and sales strategies that work best.

In the context of a sales funnel , potential customers enter the wide end, and as they progress through each stage, the funnel narrows, leaving only the most engaged prospects at the narrow end, who then become customers.

Conversion funnel analysis is the system of tracking these stages and identifying where prospects drop out. It can help you determine bottlenecks in your sales qualification process and find areas for improvement.

Various funnel analysis tools are available that can help you in this process. These tools can track the user journey, measure conversion rates at each stage, and give insights into user behavior.

We will tackle this in a bit. Meanwhile, let’s take a closer look at why doing a simple funnel analysis is crucial.

Why Funnel Analysis Matters

Even if your sales and conversion processes seem to be going smoothly, it’s essential to regularly measure and analyze your funnel performance. This becomes even more important if you’re facing struggles.

Identifying Drop-Off Points

Funnel analysis is vital for identifying drop-off points in your customer journey or sales process. These are critical junctures where potential customers or leads abandon their journey.

By pinpointing these drop-off points, businesses gain crucial insights into what might hinder conversions.

For instance, if you observe a significant drop in the number of users moving from the “Interest” stage to the “Consideration” stage in your online sales funnel, it could indicate that your product descriptions or pricing strategies need improvement.

Identifying these bottlenecks allows you to focus on the areas requiring immediate attention and optimization.

Analyzing Customer Behavior

Marketing funnel analysis provides a detailed understanding of customer behavior at each stage of the funnel. This means tracking users’ interactions with your website, app, or marketing campaigns.

It reveals which pages they visit, how long they spend on each page, where they drop off, and which actions they take before converting.

This data is invaluable for tailoring your marketing strategies and content to align with user preferences and expectations.

For example, if you discover that a significant portion of users abandon their shopping carts during checkout, you can investigate the reasons behind it.

It could be because of unexpected shipping costs or a complex checkout form. Then, you can make the necessary improvements.

Improving Conversion Rates

One of the most direct benefits of funnel analysis is its potential to boost conversion rates.

Businesses can implement data-driven optimizations by identifying drop-off points and understanding customer behavior.

This might involve refining marketing messages, streamlining the checkout process, offering personalized recommendations, or handling common objections .

The result is a smoother and more efficient customer journey that encourages more users to progress through the funnel and convert.

Even small improvements at various stages of the funnel can substantially impact overall conversion rates, which, in turn, can significantly increase revenue and profitability.

Enhancing Customer Experience

Funnel analysis is closely tied to improving the overall customer experience. Identifying and resolving pain points in the customer journey creates a more positive and satisfying experience for your audience.

This, in turn, fosters customer loyalty and increases the likelihood of repeat business.

For example, if you analyze customer behavior and discover that users often get stuck or confused during the customer onboarding process of your software, you can redesign the onboarding flow to be more user-friendly.

It will reduce frustration and improve the experience for new users.

Boosting ROI and Revenue

Ultimately, funnel analysis is a valuable tool for boosting return on investment (ROI) and revenue.

By optimizing your funnel and increasing conversion rates , you can create more revenue from your existing traffic and marketing efforts.

Additionally, you can minimize wasted spending by reallocating resources to focus on the most effective strategies and campaigns, further enhancing ROI.

The data-driven insights from funnel analysis enable businesses to make informed decisions about where to invest their marketing budget, resulting in more efficient and profitable marketing ops .

Next, let’s look into the important role of data collection and tools in optimizing conversion funnels.

Data Collection and Tools

You’ve understood why funnel analysis is crucial. Now, let’s talk about data collection and tools.

Think about the different sources where you can collect data for your funnel analysis and the key metrics you need to track. There’s also a variety of tools and software available you might want to consider.

Data Sources for Funnel Analysis

To conduct a thorough funnel analysis, you must pull data from various sources. These data sources for funnel analysis are crucial to understanding your customer journey comprehensively.

• Website Analytics:  Website analytics tools like Google Analytics are a primary data source for funnel analysis. They provide detailed information about user behavior on your website, including traffic sources, page views, bounce rates, and conversion tracking. This data helps you understand how users engage with your website and where they drop off in the funnel.
• Customer Relationship Management (CRM) Systems:  CRMs store valuable customer data, such as contact information, purchase history, and interactions with your sales team. Integrating CRM data with funnel analysis allows you to track how leads progress from discovery call  to conversion and beyond, providing insights into the effectiveness of your sales efforts.
• Email Marketing Platforms:  If email marketing is a part of your funnel strategy, email platforms like MailChimp or Constant Contact offer data on email open rates, click-through rates, and conversion tracking. This data helps evaluate the performance of email campaigns at different stages of the funnel.
• E-commerce Platforms:  For businesses with online stores, e-commerce platforms like Shopify or WooCommerce provide data on product views, add-to-cart actions, and purchase history. This data is crucial for analyzing the effectiveness of product pages and checkout processes in the funnel.
• Social Media Analytics:  Social media platforms like Facebook Insights and Twitter Analytics offer data on engagement, click-through rates, and conversions from social media campaigns. This data helps assess the impact of social media efforts on funnel progression.

Key Metrics to Track

Here are the key metrics anyone should track for effective funnel analysis.

• Conversion Rate:  The most critical metric in funnel analysis, the conversion rate, measures the percentage of users who complete a desired action (e.g., making a purchase) out of the total number of users who entered the funnel.
• Bounce Rate:  Bounce rate indicates the percentage of users who land on a page and then leave the website without taking any further action. A high bounce rate at any stage of the funnel could signal a problem that needs attention.
• Exit Rate:  Exit rate tracks the percentage of users who leave your website or a specific page after viewing it. This metric can reveal where users are dropping off within the funnel.
• Average Session Duration:  This metric shows how long, on average, users spend on your website or specific pages. It helps gauge user engagement and can highlight areas where users are spending more or less time.
• Click-Through Rate (CTR):  CTR measures the percentage of users who click on a specific link or call-to-action (CTA). Tracking CTR can help assess the effectiveness of your CTAs and content in moving users through the funnel.

Funnel Analysis Tools and Software

You can use dozens of funnel analysis tools and software to understand your customer’s journey better and improve conversion rates. You’re not limited to a single option.

With the right tool, you can dig deeper into the customer funnel, identify bottlenecks, and optimize your strategies.

Consider these top tools:

• Google Analytics:  Google Analytics is a powerful, widely-used tool that provides comprehensive website analytics. It offers features for setting up and tracking custom sales funnels, allowing you to visualize and analyze user journeys on your site.
• Mixpanel:  Mixpanel is a user analytics platform that specializes in event tracking. It’s valuable for businesses wanting to study user behavior and cohort analysis, making it useful for understanding how users move through a funnel.
• Kissmetrics:  Kissmetrics is another user analytics tool focused on tracking customer behavior. It provides insights into user engagement, conversions, and retention, making it suitable for optimizing funnel performance.
• HubSpot:  HubSpot is a comprehensive inbound marketing and CRM platform that offers funnel-tracking features. It allows you to create and analyze marketing and sales funnels, integrating data from various sources.
• Custom Solutions:  Some businesses opt for custom-built funnel analysis solutions tailored to their needs. These can be built using programming languages like Python or R and may involve data from various sources integrated using APIs. Custom solutions provide flexibility and control over data analysis but may require more development resources.

Data collection and the choice of tools are critical aspects of funnel analysis. They enable businesses to gain deep insights into customer behavior, optimize their funnels, and make data-driven decisions that drive conversions and revenue.

Setting Up Funnel Tracking

So, how do you go about setting up funnel tracking? First, you’ll need to define your funnel stages clearly. After that, it’s all about implementing those tracking codes and then testing and debugging to ensure everything runs smoothly.

Defining Your Funnel

You’ll need to identify each stage in your sales process before you can accurately define your funnel.

Understanding the customer journey and the key touchpoints is vital. It’s not merely about making a sale. It’s about nurturing a relationship with your customer.

Consider these three points:

• Identify your customer’s journey: Understand the steps your customer goes through from awareness to purchase.
• Define your stages: Break down your sales process into actionable stages. This could be awareness, interest, decision, and action.
• Set your goals: For each stage, set measurable goals. This could be increasing awareness by 20% or improving conversion rates.

A map user flow also helps. Visualize how users should ideally move through the funnel. In doing so, you’ll have a well-defined sales funnel to help you track progress, identify bottlenecks, and drive growth.

Implementing Tracking Codes

Tracking codes, often called pixels, let you see how users interact with your site. They’re like the unseen detectives of your online business.

You’ll see where traffic is coming from, what’s engaging your visitors, and where they’re leaving.

Don’t worry if you’re not tech-savvy. Many tools can help you set up tracking codes easily.

Here’s a process:

• Install Analytics Tools:  If you’re using tools like Google Analytics or Mixpanel, make sure the tracking codes are correctly installed on your website or app. This involves adding code snippets to your website’s HTML or using tag management systems.
• Event Tracking:  Set up event tracking for each stage of your funnel. This involves configuring your analytics tool to monitor specific user actions, such as button clicks or form submissions. For instance, you can track when users click the “Add to Cart” button or submit a lead generation form.
• UTM Parameters:  Use UTM parameters in your marketing links to track the sources of traffic and campaign effectiveness. UTM parameters are tags appended to URLs, providing detailed insights into the origin of your website visitors .
• E-commerce Tracking:  If applicable, enable e-commerce tracking to monitor revenue, transaction data, and product performance. E-commerce tracking is vital for businesses selling products or services online.

Testing and Debugging

Make sure you’re regularly testing and debugging your funnel tracking to ensure it’s accurately capturing your customer’s journey.

Regular check-ups are essential. It’s like keeping an eye on your health. You wouldn’t neglect a routine check-up, would you?

Here are three key steps to ensure your funnel tracking is up to scratch:

• Test the Funnel:  After implementing tracking codes, thoroughly test your funnel to ensure that events and conversions are tracked accurately. Go through the funnel yourself, clicking on various elements, and completing conversion actions.
• Use Debugging Tools:  Many analytics platforms offer debugging tools that help identify tracking issues. These tools often provide real-time data on user interactions, allowing you to see if events are being recorded correctly.
• Cross-Browser and Cross-Device Testing:  Test your funnel across different browsers (e.g., Chrome, Firefox, Safari) and devices (desktop, mobile, tablet) to ensure that tracking works consistently for all users.
• Data Validation:  Regularly validate your funnel data to ensure accuracy. Compare the data in your analytics platform with other sources of truth, such as CRM or sales data, to identify discrepancies.

Establishing robust funnel tracking is a systematic process that demands careful planning, implementation, and regular testing. This iterative process of understanding your customer’s journey, implementing precise tracking mechanisms, and validating the data regularly is a clear roadmap to your business’ growth.

Interpreting Funnel Analysis Results

Interpreting funnel analysis results is a critical phase in the data-driven decision-making process for businesses. This is where the process concludes.

Making Informed Decisions

Making informed decisions based on funnel analysis results means using the insights extracted from the data to guide your strategies and actions.

These decisions are rooted in evidence and provide a clear path forward for optimizing the customer journey.

In essence, funnel analysis empowers businesses to move away from gut feelings and assumptions, ensuring that every decision is backed by concrete data, ultimately leading to more effective and efficient operations.

Adjusting Marketing Strategies

Adjusting marketing strategies based on funnel analysis results means tailoring your campaigns, content, and outreach to address your audience’s specific needs and behaviors.

Adapting your strategies ensures that you remain relevant and effective in a dynamic market environment.

If funnel analysis reveals that a particular marketing channel is driving more conversions, consider reallocating resources to that channel. Conversely, if a campaign is underperforming, you can make adjustments or discontinue it.

This adaptability is essential for optimizing your marketing spend and focusing efforts where they yield the best results.

Identifying Successes and Failures

Identifying successes and failures in funnel analysis results involves recognizing what works well in your funnel and what needs improvement.

Acknowledging successes and failures is essential for continuous improvement and learning from past experiences.

Celebrate your successes and build upon them. If a specific marketing campaign or strategy consistently drives high conversions, analyze what elements contribute to its success and replicate those tactics in other areas.

On the flip side, if you identify areas of failure, view them as opportunities for growth. Determine the root causes of these failures and implement changes to address them.

This proactive approach ensures that your funnel evolves and becomes more effective over time.

Marketing funnel analysis is indispensable for businesses. It offers a structured approach to understanding customer behavior, optimizing conversion processes, and enhancing overall performance. As we’ve explored, funnel analysis empowers organizations to identify bottlenecks, calculate conversion rates, segment audiences , conduct A/B testing, and utilize visual tools for in-depth insights. By implementing funnel analysis, businesses can make data-driven decisions that boost ROI and revenue and foster a superior customer experience . As technology and user preferences evolve, the importance of funnel analysis remains steadfast, encouraging organizations to harness the power of data and embark on a journey of continuous improvement in their pursuit of success.

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About Ron Sela

Ron is a marketing advisor to technology-driven businesses. He has 15 years of digital marketing experience and an MBA from the University of Florida. Ron helps companies grow their revenue by developing and executing integrated marketing plans that align with their business goals. He has a proven track record of success in helping companies achieve their growth objectives.

What is Funnel Analysis?

Funnel basics.

A funnel is an arbitrarily defined user flow that measures the drop off from step to step. Arbitrary because you can create a funnel out of any sequences of events you would like to analyze. For example, a signup funnel would include all the steps between the landing page and signup complete; a checkout funnel would represent all steps between product view and purchase complete.

Those are well known but there are many others that a company can create. An engagement funnel perhaps or [another type of funnel]. The important point is that the funnel be representative of a known or rationally-hypothesized sequential user flow.

Why is it important?

As mentioned earlier, the core of funnel analysis is actionable conversion measurement. Actionable meaning that you can readily identify the most basic steps contributing to drop off. Measuring a single conversion rate between distance steps is neither informative nor immediately actionable.

This is an important endeavor for any business seeking to optimize. You may have a great product, with revenue flowing in but a design flaw in your signup process is deterring would-be customers from joining and purchasing. Engaging in funnel analysis would quickly identify this bottleneck and allow a company to fix the issue.

Closed-Path vs. Open-Path

There are two types of funnels: one in which a user progresses through a closed-flow path and the other an open-flow. A closed-flow path is where a user has no option but to follow the steps sequentially. Signing up is a good example: users start at the landing page and have no choice but to proceed to Page 1 then Page 2 and so forth until they finish. In this example, the funnel would be simple and linear:

Landing Page → Page 1 → Page 2 → Sign Up Complete

An open-flow path exists when there are many parallel steps between the beginning and end of the funnel that users can take. Take an engagement funnel. In this case, signing up would be the first step and making a purchase the last. In between, a user can embark on a multitude of paths: some users might view the product page, read some testimonials and then make a purchase. Some may simply view the product page before purchasing. While yet others may view the product page, read testimonials, view a coupon and only then decide to purchase. How would you create the funnel?

Sign Up → Product View → Testimonials → Purchase

Sign up → product view → purchase, sign up → product view → testimonials → comparison page → purchase, multi-dimensional funnels.

This is where multi-dimensional funnels come in handy. A powerful but seldom offered tool, they allow for the visualization of parallel user paths while retaining the simplicity characteristic of their linear counterparts. Using them would allow you to see all the paths users take to reach a goal, in this case a purchase. In one fell swoop, you’d be able to identify, for example, that users who viewed testimonials were more likely to purchase than those who didn’t. And those who viewed a testimonial and then a coupon had the highest purchase conversion rate. Granted, it’s possible to perform this analysis using simple linear funnels but the process would be very time-consuming, especially with alot of parallel paths.

Creating Your Funnel

When creating your funnel, the most important thing to do is identify the basic intermediary steps. Missing one out may mask a poor (well) performing conversion or assign blame (or praise) to the wrong element. For closed paths, the steps should be relatively easy to ascertain. Open paths, however, require a bit more investigation. The key point is to hypothesize steps that are causally relevant to users reaching the goal.

Once you have created your funnel and are able to see the conversions, it is time to begin optimizing. The best place to focus your efforts are usually at the top of the funnel; improving the conversion upstream will usually increase the volume subsequent events.

Getting Started With Funnel Analysis

To get started, you'll need an analytics tool that has robust funnel capabilities like Indicative .

Problem-Solving Theory: The Task-Centred Model

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• Blanca M. Ramos 5 &
• Randall L. Stetson 6  

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This chapter examines the task-centred model to illustrate the application of problem-solving theory for social work intervention. First, it provides a brief description of the problem-solving model. Its historical development and key principles and concepts are presented. Next, the chapter offers a general overview of the crisis intervention model. The task-centred model and crisis intervention share principles and methods drawn from problem-solving theory. The remainder of the chapter focuses on the task-centred model. It reviews its historical background, viability as a framework for social work generalist practice, as well as its applicability with diverse client populations and across cultural settings. The structured steps that guide task-centred implementation throughout the helping process are described. A brief critical review of the model’s strengths and limitations is provided. The chapter concludes with a brief summary and some closing thoughts.

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Ramos, B.M., Stetson, R.L. (2022). Problem-Solving Theory: The Task-Centred Model. In: Hölscher, D., Hugman, R., McAuliffe, D. (eds) Social Work Theory and Ethics. Social Work. Springer, Singapore. https://doi.org/10.1007/978-981-16-3059-0_9-1

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Idea Funnel Unleashed: Mastering the Art of Creative Ideation

6 minutes read

Embark on a journey of innovation as we unveil the concept of the Idea Funnel. This clever method of ideation promises to revolutionize the way you generate and refine ideas. The 'Idea Funnel' guides your creative thinking through a structured process that not only improves productivity, but also ensures the quality of your concepts. In this guide, we'll delve into the significance of the Idea Funnel, exploring its relevance, benefits and the key role it plays in the creative field.

Introduction to Idea Funnel

Delve into the core of Idea Funnel, a dynamic process that serves as a catalyst for elevating the quality of your ideas. The essence lies in its ability to refine and enhance creative concepts systematically. By channeling thoughts through a structured approach, Idea Funnel brings a sense of order to the often chaotic realm of ideation. This method transforms the creative landscape, offering a strategic pathway to nurture and develop innovative ideas.

Embrace the systematic approach of Idea Funnel, where every stage is a deliberate step towards refining ideas. This methodology not only organizes the ideation journey but also ensures a more fruitful outcome. From the initial spark of creativity to the final, polished concept, the Idea Funnel acts as a guide, directing the flow of ideas with precision.

When to Use the Idea Funnel Approach

In the dynamic landscape of ideation, understanding when to deploy the Idea Funnel methodology is key to unlocking its transformative potential. From brainstorming sessions to project launches and more, mastering the creative funnel method can enhance a variety of scenarios in creative work.

• Brainstorming Sessions: In the initial stages, when creativity is at its peak, the funnel provides a systematic framework to capture, organize, and prioritize ideas. This ensures that the brainstorming process remains dynamic yet focused, guiding the team towards innovative solutions.
• Project Kick-offs: When embarking on a new project, initiating it with the Idea Funnel approach sets the tone for a well-orchestrated creative journey. The initial phase of a project is crucial, and the funnel helps in outlining goals, defining objectives, and generating a pool of diverse ideas.
• Complex Problem-Solving: In scenarios requiring intricate problem-solving, the Idea Funnel proves to be a valuable tool. Whether faced with challenges in product development or seeking innovative solutions to business issues, the structured approach of the funnel ensures a comprehensive exploration of ideas. 
• Team Collaboration Initiatives: Team collaboration is at the heart of many successful projects, and the Idea Funnel is an ideal companion in such endeavors. When multiple minds are involved, the funnel aids in consolidating diverse perspectives into a cohesive strategy. 

Understanding the opportune moments to leverage the Idea Funnel methodology transforms it from a creative technique to a strategic asset. Whether in the spontaneous burst of brainstorming or the structured initiation of a new project, the Idea Funnel adapts to the unique demands of each scenario, guiding creative endeavors towards excellence.

Benefits and Importance of Idea Funnel

Explore the myriad advantages that Idea Funnel offers, demonstrating its pivotal role in enhancing individual and team-based creative processes.

• Collaborative Synergy: Idea Funnel creates a collaborative hub where team members contribute, refine, and unify diverse perspectives. This collaborative synergy not only enhances idea quality but also fosters a sense of shared ownership among team members.
• Strategic Ideation: The systematic structure of the funnel guides ideation, ensuring a focused journey from conception to refinement. Categorizing and prioritizing ideas at each stage accelerates the process and guarantees alignment with overarching goals.
• Innovation Acceleration: Idea Funnel speeds up innovation by encouraging constant refinement and evolution of ideas. The iterative process stimulates creative thinking beyond conventional boundaries, leading to the exploration of novel solutions.
• Proactive Risk Mitigation: The structured approach helps identify and address potential risks early in the ideation process. By systematically evaluating ideas and considering different scenarios, teams can anticipate challenges, making informed decisions and ensuring a more successful creative journey.
• Continuous Improvement: The iterative nature of the Idea Funnel fosters a culture of continuous improvement. Concepts undergo refinement at each stage, leading to the development of more polished, innovative, and effective ideas.

Understanding the diverse benefits and importance of Idea Funnel goes beyond a mere creative technique—it becomes a strategic investment in maximizing collaborative potential, fostering innovation, and ensuring the success of creative endeavors for both individuals and teams.

Crafting an Idea Funnel with Boardmix

The intricacies of crafting a dynamic Idea Funnel underscore the need for a user-friendly tool that seamlessly aligns with the creative process. Boardmix emerges as the ideal companion, offering a versatile platform that caters to the nuanced requirements of an Idea Funnel. 

Boardmix excels in offering a structured environment that supports the fluidity of ideation. Its intuitive interface ensures a seamless transition through different stages, from ideation to refinement and finalization. Have a quick glance at the following steps for making the Idea Funnel in Boardmix!

Step 1: Login Boardmix

Register or log in to your own Boardmix space! Learn about Boardmix's user-friendly interface, including boards, cards, and collaboration tools.

Step 2: Creating Your Board

Initiate the process by crafting a dedicated board. Name it according to your theme or project. A tidy board sets the stage for effective idea development.

Step 3: Adding Columns for Stages

Strategically use columns to represent different ideation stages, such as "Brainstorming" and "Finalization." These columns guide ideas through their evolution.

Step 4: Customizing Table

Create table within each column to represent ideas. Customize them with attachments, comments, and details. These table document the ideation journey comprehensively.

Step 5: Export and Sharing

Boardmix enables effortless export and sharing of your Idea Funnel. Share the board with stakeholders or export it for further analysis and presentation.

Boardmix transforms creative ideas into a structured Idea Funnel. With its user-friendly interface and versatile features, Boardmix empowers individuals and teams to craft, refine, and collaborate on ideas seamlessly. Follow these simple steps to harness Boardmix's potential, creating an Idea Funnel that enhances creativity and maximizes the impact of your ideation process.

Tips and Strategies for Effective Idea Funnel

Embarking on the journey of Idea Funnel requires a strategic approach to maximize creativity and innovation. Here are essential tips and strategies to streamline your ideation process and transform ideas into impactful solutions.

Define Clear Objectives

Clearly articulate the objectives of your Idea Funnel. Whether solving a problem or achieving a specific goal, having a well-defined purpose ensures that the generated ideas are purposeful and aligned.

Diversify Ideation Techniques

Embrace diverse ideation techniques to stimulate creativity. Combine brainstorming, mind mapping, and lateral thinking exercises to explore ideas from different perspectives. This diversity enriches the pool of concepts.

Prioritize and Categorize

Prioritize ideas based on feasibility, impact, or relevance. Categorize them into distinct stages, such as "Initial Concepts," "Refinement," and "Final Selection." This systematic approach ensures a focused and organized progression.

Encourage Collaboration

Foster a collaborative environment by involving team members throughout the ideation process. Leverage collaborative tools like Boardmix to facilitate real-time contribution, refinement, and collective building of ideas.

Embrace Iterative Refinement

Emphasize the iterative nature of Idea Funnel. Regularly revisit and refine ideas as they progress through different stages. Iteration enhances idea quality and promotes continuous improvement.

Use Constraints Creatively

Turn constraints into opportunities for creative problem-solving. Constraints, be they budgetary, time-related, or resource-based, can stimulate innovative thinking and lead to unconventional yet effective solutions.

These six tips and strategies form a foundational framework for effective Idea Funnel. By implementing these principles, you can channel creativity strategically, refine ideas systematically, and ensure that your ideation process is both impactful and efficient. Leverage Boardmix 's features to create a dynamic visual representation of your Idea Funnel, ensuring a more efficient and impactful ideation process.

Join Boardmix to collaborate with your team.

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Lean Events and Training / Events / Intro to Problem-Solving

Intro to Problem-Solving

Learn a proven, systematic approach to resolving business and work process problems..

Online – On-Demand, Self-Paced

Why you should attend

Learn a proven, systematic approach to resolving business and work process problems, including how to overcome the shortcomings of most problem-solving efforts: not understanding the situation and jumping to conclusions.

$249, Users have access for 12 months

Register now on our eLearning platform

In this in-depth , self-paced learning experience, you’ll learn how to use A3 thinking and the plan-do-check-act (PDCA) improvement cycle — essential lean problem-solving practices that are effective at any level from the front line to the executive suite .

Too often, people jump to implement a “solution” to “fix” a problem only to see it recur and the firefighting cycle repeat. Learning and implementing the A3 thinking and PDCA improvement cycle will ensure you fully grasp the problem situation, identify the root cause, and try and test countermeasures, establishing a perpetual system for clearing obstacles keeping you or your team from achieving — or beating — your performance objectives.  

Throughout this experience, narrated by John Shook, Toyota’s first American manager in Japan, Senior Advisor of the Lean Enterprise Institute, and Chairman of the Lean Global Network, you’ll follow a case example that illustrates and breaks down each step of the problem-solving approach into their simple, easily understood parts. You’ll engage with hands-on activities, videos, multimedia, PowerPoint presentations, articles, and book excerpts, including the best-selling Managing to Learn .

In addition, you will deepen your understanding of lean problem-solving concepts by applying this new way of thinking to a problem you’re currently wrestling with, using downloadable “tools,” such as the Problem Breakdown Analysis and Guided Gemba   exercises and an A3 template.

This learning experience will enhance your ability to resolve work process problems — to get back on track after failing to achieve the standard targets or to achieve a higher performance target — a skill that is critical to every position in every industry , whether in a lean – thinking organization or not. As part of a lean journey, the experience will help you master an essential element of lean thinking and practice .

Who Will Benefit?  

• Individuals who aim to enhance their career prospects by improving their problem-solving skills by adopting the A3 problem-solving process and the PDCA improvement cycle
• Lean practitioners who feel they must fill in learning gaps or refresh their A3 problem-solving and PDCA knowledge and skills
• Leaders, from mid-level managers to top executives, who are trying to level up their team’s knowledge of and adopt lean problem-solving processes as their standard approach, including continuous-improvement and human-resource leaders 

What Will I Learn?  

Upon completion, you will be able to: 

• Build a foundational understanding of problem types and problem-solving.   
• Identify the four types of problems.  
• Resolve business challenges by using the scientific-method-based PDCA-based improvement cycle.
• Apply A3 thinking to solve problems.
• Clearly define problems, beginning with grasping the situation by gathering facts at the gemba.
• Break down general, vague problems into specific, actionable ones that you can solve at the root cause.  

What Else Should I Know?

Get a head start or supplement your online learning. This ebook highlights and explains what you need to know about using this powerful lean practice to gain its most impactful benefits:  

Also, though no prerequisite training or reading is required, having familiarity with lean management basics will be helpful. We recommend the following books:

This learning experience is based on the tested and proven methodology created for LEI’s popular Managing to Learn workbook , authored by John Shook , Toyota’s first American manager in Japan, Senior Advisor of the Lean Enterprise Institute, and Chairman of the Lean Global Network.  

You might also find the book Four Types of Problems helpful in enhancing your problem-solving capabilities. The book explains how most business problems fall into four categories and describes the thought processes, management cadences, and improvement methods t hat will resolve each type.  

Time Estimates Per Unit*

*Actual times may vary.

Download the Intro to Problem-Solving Concept Map and share it with your manager.

Senior Advisor, Lean Enterprise Institute

John Shook learned about lean management while working for Toyota for 11 years in Japan and the U.S., helping it transfer production, engineering, and management systems from Japan to NUMMI and other operations around the world. While at Toyota’s headquarters, he became the company’s first American kacho (manager) in Japan. In the U.S., Shook joined […]

Need to level set your team’s lean knowledge and skills? Choose the Lean Fundamentals Enterprise Subscription and gain unlimited access for everyone in your organization to three foundational lean learning experiences for three months.

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Gen AI Has Already Taken the World by Storm. Just Wait Until It Gets a Quantum Boost

W hen Lawrence Gasman was looking for a PhD topic back in the 1970s, computing labs were already abuzz with smart people proposing clever studies in artificial intelligence . “But the problem was we had nothing to run them on,” he says. “The processors needed just didn’t exist.”

It took half a century for computing power to catch up with AI’s potential. Today, thanks to hi-powered chips such as GPUs from California-based Nvidia, generative artificial intelligence, or gen AI, is revolutionizing the way we work, study, and consume entertainment, empowering people to create bespoke articles, images, videos, and music in the blink of an eye. The technology has spawned a bevy of competing consumer apps offering enhanced voice recognition, graphic design, and even coding.

Now AI stands poised to get another boost from a radical new form of computing: quantum . “Quantum could potentially do some really remarkable things with AI,” says Gasman, founder of Inside Quantum Technology.

Rather than relying on traditional computing’s binary “bits”—switches denoted as 1s and 0s—quantum use multivariant “qubits” that exist in some percentage of both states simultaneously, akin to a coin spinning in midair. The result is exponentially boosted computing power as well as an enhanced ability to intuitively mimic natural processes that rarely conform to a binary form.

Whereas gen AI’s consumer-targeted applications have made its impact more widespread and immediate, quantum is more geared towards industry, meaning several recent milestones have slipped under the radar. However, they stand to potentially turbocharge the AI revolution.

“Generative AI is one of the best things that has happened to quantum computing,” says Raj Hazra, CEO of Colorado-based quantum start-up Quantinuum. “And quantum computing is one of the best things to happen to the advance of generative AI. They are two perfect partners.”

Ultimately, AI relies on the ability to crunch huge stacks of information, which is where quantum excels. In December, IBM unveiled its latest processor, dubbed Heron , which boasts 133 qubits, the firm’s best ever error reduction and the ability to be linked together within its first modular quantum computer, System Two. In addition, IBM unveiled another chip, Condor, which has 1,121 superconducting qubits arranged in a honeycomb pattern. They’re advances that mean “now we’re entering what I like to call ‘quantum utility,’ where quantum is getting used as a tool,” Jay Gambetta, vice-president of IBM Quantum, tells TIME.

Since qubits are incredibly delicate subatomic particles, they don’t always behave in the same way, meaning quantum relies both on increasing the overall number of qubits to “check” their calculations as well as boosting the fidelity of each individual. Different technologies used to create a quantum effect prioritize different sides of this equation, making direct comparisons very tricky and enhancing the arcane nature of the technology .

IBM uses superconducting qubits, which require cooling to almost absolute zero to mitigate thermal noise, preserve quantum coherence, and minimize environmental interactions. However, Quantinuum uses alternative “trapped-ion” technology that holds ions (charged atoms) in a vacuum using magnetic fields. This technology doesn’t require cooling, though is thought to be more difficult to scale. However, Quantinuum in April claimed it had achieved 99.9% fidelity of its qubits.

“The trapped ion approach is miles ahead of everybody else,” says Hazra. Gambetta, in turn, argues the superconducting quantum has advantages for scaling, speed of quantum interactions, and leveraging existing semiconductor and microwave technology to make advances quicker.

For impartial observers, the jury is still out since the raft of competing, non-linear metrics render it impossible to tell who’s actually ahead in this race . “They are very different approaches, both are showing promise,” says Scott Likens, global AI and innovation technology lead for the PwC business consultancy. “We still don’t see a clear winner, but it’s exciting.”

Where Gambetta and Hazra agree is that quantum has the potential to mesh with AI to produce truly awesome hybrid results. “I would love to see quantum for AI and AI for quantum,” says Gambetta. “The synergies between them, and the advancement in general in technology, makes a lot of sense.”

Hazra concurs, saying “generative AI needs the power of quantum computing to make fundamental advances.” For Hazra, the Fourth Industrial Revolution will be led by generative AI but underpinned by the power of quantum computing. “The workload of AI and the computing infrastructure of quantum computing are both necessary.”

It’s a view shared across the Pacific in China, where investments in quantum are estimated at around $25 billion, dwarfing the rest of the world. China’s top quantum expert, Prof. Pan Jianwei, has developed a Jiuzhang quantum computer that he claims can perform certain kinds of AI-related calculations some 180 million times faster than the world’s top supercomputer.

In a paper published in the peer-reviewed Physical Review Letters journal last May, Jiuzhang processed over 2,000 samples of two common AI-related algorithms—Monte Carlo and simulated annealing—which would take the world’s fastest classical supercomputer five years, in under a second. In October, Pan unveiled Jiuzhang 3.0, which he claims was 10 quadrillion times faster in solving certain problems than a classical supercomputer.

Jiuzhang utilizes yet a third form of quantum technology—light or photons—and Pan is widely lauded as China’s king of quantum. A physics professor at the University of Science and Technology of China, Pan in 2016 launched Micius, the world’s first quantum communication satellite, which beamed entangled photons between earth a year later for the world’s first quantum-secured video call.

Micius is considered quantum’s “Sputnik” moment, prompting American policymakers to funnel hundreds of millions of dollars into quantum information science via the National Quantum Initiative . Bills such as the Innovation and Competition Act of 2021 have provided $1.5 billion for communications research, including quantum technology. The Biden Administration’s proposed 2024 budget includes $25 billion for “emerging technologies” including AI and quantum. Ultimately, quantum’s awesome computing power will soon render all existing cryptography obsolete, presenting a security migraine for governments and corporations everywhere.

Quantum’s potential to turbocharge AI also applies to the simmering technology competition between the world’s superpowers. In 2021, the U.S. Commerce Department added eight Chinese quantum computing organizations to its Entity List, claiming they “support the military modernization of the People’s Liberation Army” and adopt American technologies to develop “counter-stealth and counter-submarine applications, and the ability to break encryption.”

These restrictions dovetail with a raft of measures targeting China’s AI ambitions, including last year blocking Nvida from selling AI chips to Chinese firms. The question is whether competition between the world’s top two economies stymies overall progress on AI and quantum—or pushes each nation to accelerate these technologies. The answer could have far-reaching consequences.

“AI can accelerate quantum computing, and quantum computing can accelerate AI,” Google CEO Sundar Pichai told the MIT Technology Review in 2019. “And collectively, I think it’s what we would need to, down the line, solve some of the most intractable problems we face, like climate change.”

Still, both the U.S. and China must overcome the same hurdle: talent. While only a few universities around the world offer quantum physics or mechanics, dedicated courses on quantum computing are even rarer, let alone expertise on the various specialties within. “Typically, the most valuable and scarcest resource becomes the basis of your competitive advantage,” says Hazra. “And right now in quantum it’s people with that knowledge.”

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Write to Charlie Campbell at [email protected]