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May 24, 2024

Customer research: Methods for better products and happier customers

Learn key types of customer research, how it stands apart from UX and market research, and how to nail it in just five steps.

Armin Tanovic

Only by knowing your customers' pain points, values, and motivations inside and out can you create a product customers actually want to use. In fact, it’s a lack of proper research that former business owners cite as one of the main reasons for startup failure —highlighting just how important customer research is for success.

In this article, we look at exactly what’s meant by customer research, and why it’s vital for your organization’s success. We also run through five steps for conducting customer research, so you can start planning your research initiatives today.

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What’s the difference between customer research, customer experience research, and market research?

Customer research, customer experience research, and market research may all sound like the same thing, but while overlap exists, each of these terms has its own meaning.

This article’s focus, customer research, is the process of learning your customers’ pain points, motivations, preferences, and needs . It helps you develop an in-depth understanding of your customers—who they are, what their needs and struggles are—so you can create user personas for them, reflect on the customer journey, and tailor your product or user experience to their unique expectations.

Here’s how customer experience research and market research are different from customer research:

• Customer experience research: Looks at all the touchpoints throughout the buyer journey, and helps improve customer experience through insights and customer experience KPIs , such as customer satisfaction scores
• Market research: Collects information on the wider market landscape, including potential customers, industry trends, market needs, and product gaps

Customer research is specifically concerned with who your customers are , while customer experience research is about how they interact with your product. Market research is easier to differentiate, focusing on the market itself, rather than customers.

Why is customer research important?

Customer research is important as it gives your company the insights necessary to tailor your products and services to buyers’ preferences. By thoroughly understanding your customers, you can steer major product decision-making in the right direction, create better products, and fulfill business goals.

Customer research also helps your business attract new customers: over 80% of buyers state they're more inclined to do business with an organization that delivers tailored brand experiences. Alongside this, it helps your business get more referrals—with 70% of buyers more likely to recommend a brand that offers personalized experiences.

When should you conduct customer research?

Customer research is beneficial at various stages of product development . From planning new products and services to personalizing your marketing strategy, here’s some times to conduct customer research:

• When creating buyer personas: By thoroughly understanding buyers, you can create comprehensive user personas with demographics, brand perceptions, behaviors, and pain points
• When you aim to improve products or services: Understanding preferences means you can improve your products or services to match your customer’s expectations
• While crafting brand messaging and content that resonates: Customer research provides clarity on customer motivations and pain points, which you can use to personalize messaging and communicate effectively with your customers
• To identify new opportunities: Discovering new things about your audience opens up the chance to create products, services, and features your team hasn’t considered before
• For guiding your business decisions: Knowing what your customers want, and how they want it, serves as a signpost for making major business decisions—for example, positioning your brand, allocating resources, and signing off on major UX design and development changes

What are the types of customer research?

There’s more than one way to get the scoop on your customer’s deepest desires, expectations and motivations. You might be surprised to learn you can gather useful customer insights from what your users are already saying about your brand. All you need to do is tune in.

Here are the four types of customer research.

1. Primary research

Primary research is research that you conduct alone or with the help of your team. Here, you select your own research methods , design your project, and analyze data to gain specific insights on topics you’ve outlined beforehand.

Primary research is beneficial because it gathers the customer insights and knowledge you need. However, unless you’re conducting guerilla testing and meeting your customers in real-life situations, primary research can be resource-intensive.

This brings us to our second way to do customer research.

2. Secondary research

Secondary research entails investigating data provided by someone else. Yes—you can do that! All you need to do is find the forums, communities, and review sites where your customers hang out and discuss their needs, preferences, and satisfaction levels. You can use Voice of the Customer tools, or one of the easiest ways to get customer feedback is by linking up with your customer success and support teams—tune into client meetings, read up on feature requests, and follow Slack channels to hear on-the-ground feedback.

You can also conduct secondary research by revisiting data from previous research studies your product or UX research team may have conducted, or looking at industry trend studies done by other companies—for example, our Future of User Research Report . If your organization has an existing research operations team or central UX research repository , you can garner a lot of first-hand insights that already exist.

Secondary data can be a quick and easy way to conduct customer research. But since it's done by other parties, you have no control over the amount of data or the exact insights you’re getting. It’s also important to consider any confines of the data you’re looking at—for example, the research questions asked, or research objectives being pursued when the insights were collected.

But what about the different data types that result from customer research?

3. Quantitative research

Quantitative research uncovers numerical data, statistics and trends about your customers. The number-based insights work best for identifying patterns and gathering broad understandings of preferences, opinions, or how many people fall into a certain category.

Quantitative research is best done with UX research methods like heatmaps or UX surveys with Likert scales, close-ended questioning, and multiple-choice questions. It aims to answer ‘what’, ‘where’, and ‘when’ with objective metrics, collected indirectly—often through a UX research tool .

4. Qualitative research

Qualitative research entails collecting and analyzing descriptive, contextual, and interpretive data. This non-statistical data looks at the ‘why’, aiming to uncover customer opinions, viewpoints, and experiences.

Typically obtained through research methods like focus groups, user interviews , and open-ended question surveys, qualitative research helps you get deeper insight into your customers’ motivations and pain points. To give customers space and the opportunity to provide rich, descriptive feedback, qualitative research methods will typically have open-ended ‘why’ questions.

5 Customer research methods for uncovering insights

There are plenty of research methods that can uncover and collect the customer insights you’re looking for. Here’s our top five recommended methods for conducting customer research.

1. Customer interviews and focus groups

Nothing uncovers rich, descriptive, contextual insights better than sitting down with your customers and asking them the questions that matter. That’s exactly what customer interviews and focus groups do.

For interviews, you can prepare a list of open- and closed-ended questions, connect with customers one-on-one, and transcribe your answers with the help of a specialized research tool—like Maze Interview Studies .

With a focus group, you’re sitting down with no more than ten customers to gather a collective opinion of a market segment with representative sampling.

Both interviews and focus groups are especially helpful for uncovering customer:

• Experiences

While interviews and focus groups do go in-depth, conducting them can be time-consuming. If you’re short on time or resources, UX surveys and questionnaires can save you time and effort.

2. Research surveys and questionnaires

Customer experience surveys and questionnaires are a quick and easy way to gain insights with a list of open- and closed-ended questions . Instead of sitting down with your customers, you can send surveys through channels like email, social media or in-product pop-ups .

Surveys and questionnaires are especially versatile due to the many types of questions you can include; from open-ended questions to collect qualitative data, to close-ended questions, rating scales , and multiple choice for quantitative customer feedback.

3. Usability testing and product analytics

Both usability testing and product analytics are common customer research methods, and should form a big part of your customer experience strategy .

With usability testing , you give customers a task to complete and see how accomplish it with your digital product and service. Note down any friction points: where did customers find it difficult to progress during the digital experience? You can follow up usability testing with a quick survey or longer user interview to gather more context on their experience.

Identifying where customers struggle, and seeing this first-hand, gives you insight into their preferences and needs.

Product analytics show you how customers interact with your product by tracking metrics such as time spent on your product, success rates, heatmaps, and click rates. This analytical data helps you common problems and patterns, and identify which customer segments are having the hardest time using your product.

4. Social media and online review mining

Instead of meticulously creating tests to gather customer insights, social media and online review mining lets you collect already existing data from and about your customers. By finding reviews, comments, and ratings online and through social media, you can hear from customers in their own words, to identify where your product falls short, and where it matches their exact expectations.

So, where will you find this treasure trove of valuable insights? Look toward:

• Public review sites such as Capterra and G2Crowd
• Niche communities and forums where your customers gather such as Reddit, Slack, and Quora
• Comments and hashtags on your company’s social media channels such as LinkedIn, X, Instagram, and Facebook

5. Competitive analysis and market research

Customer research helps you understand who your customers are. Competitive product analysis and market research give insights into the space in which you and your customers exist, and provide you with more context on their preferences.

With competitive analysis, you’re not just looking at how customers react to your product but also to your competition . Look for which customer needs or expectations other companies fulfill; where they fall short, and how you can leverage data to understand your customers and create better products and services.

For example, maybe a competitor’s newest helpdesk offer tracks customer resolution times for airline services, but customers are complaining about the platform's lack of reporting options. This could indicate that your product’s major differentiator and competitive advantage should be extensive reporting options and in-depth analytics.

You can also apply your customer research strategy to the market and study bigger industry trends. Market research helps you better understand demand, what customers are willing to pay for a product or service, customer demographics, and segmentation.

How to do customer research: 5 steps for success

Understanding your customers will tell you almost everything you need to know about how to create a product or service that exceeds their needs. It’s the daunting task of collecting these insights that often stops organizations from investing in customer research —but it shouldn’t.

While conducting customer research can feel a lot like navigating a maze, having a solid UX research strategy sets you up for success.

We’ve put together five steps to guide your research process , to ensure you don’t spend valuable resources on dead ends.

1. Define your customer research objectives

As with any other initiative, effective customer research starts with defining the grounds for success. Your mantra to meditate on always starts with: “What do I want to accomplish with these customer insights?”

This question will help you set the course and choose the appropriate method for your customer research project.

Some example objectives:

• I want to create comprehensive customer personas to help us personalize our product
• I want to craft compelling brand content, copy, and communications based on our customers’ biggest pain points
• I want to introduce a new feature that I’m sure customers will want to upgrade their account to use

Once you’ve set your target, defined any specific customer experience metrics you want to track, and gained clarity on what you want to know, it’s time to decide who you’re going to ask.

2. Identify your customer segment

At first glance, it might seem obvious that you’re going to reach out to customers to recruit participants for your research . However, your customer segments may be widely different, each with a unique set of preferences and expectations. Before you conduct research, identify a single segment and tailor your research methodology and questions to them.

Your chosen segment should be large enough to be representative of most of your brand’s customer base. Consider key characteristics in current customer data. What demographic categories do your customers fall into? Are there any preferences and motivations that you already know of?

3. Select a customer research method

The customer research method you opt for should align with your overarching goals. Let’s say you want to understand customer motivations in order to create an empathy map and customer personas.

Such a goal warrants conducting customer interviews and focus groups for contextual, qualitative insights. Perhaps you want to know your customer segment’s single greatest pain point and target that in the next bug-fix sprint. A quick survey with Likert scales and closed-ended questioning may reveal that 87% of your customer segment struggles with inefficient workflows that lead to lost time.

Running low on resources for customer research? Guerilla research tactics are an informal and cost-effective way to gather insights by meeting your customers face-to-face where they’re likely to use your product, and asking them questions in short 5–15-minute sessions.

4. Conduct your customer research

Once you’ve settled on the appropriate testing method, you’re ready to contact customers and begin your research project.

If you’ve chosen surveys or questionnaires, you’ll need to choose a distribution channel such as email or social media. Consider offering customers incentives for completing interview—you can offer free upgrade trials, access to exclusive features, discounts, or brand merchandise.

While conducting research without a tool works, it can be time-consuming. A research tool like Maze lets you create surveys, interviews, and usability tests and automatically analyzes your data for actionable insights. Product analytics capabilities also provide you with heatmaps, click rates, and scroll analytics for an in-depth look at how customers interact with your product.

Using specialized AI tools can also help you streamline tasks throughout conducting research, such as ensuring you don’t ask leading questions.

5. Analyze your data and draw findings

Your customer research will return responses, transcripts, and customer feedback in the form of qualitative or quantitative data. But data by itself is unusable—you need to create UX reportings and conduct data analysis before you can get the insights you’ve been hoping for.

If you’ve done interviews or focus groups, perform thematic analysis or affinity mapping to make sense of these large amounts of qualitative data. For surveys and usability testing, conduct statistical analysis to arrive at insights.

Once you have your insights, highlight key findings, connect them back to your overarching customer research objective, and share with your team.

Get customer research insights with Maze

Customer research opens the door to better products, happier customers, and a more successful business. It may feel like a large task, but breaking it down into bitesize steps and enlisting an all-in-one research tool can turn this large task into part of your everyday workflow.

Not sure where to start?

Maze’s comprehensive suite of user research methods make collecting customer insights (qualitative or quantitative) simple. From Interview Studies to Feedback Surveys , Usability Testing to Card Sorting —it’s a holistic research platform for gathering decision-driving data.

Frequently asked questions about customer research

Who conducts customer research?

Customer research isn’t a strictly defined role for one professional or team. Market research teams most frequently conduct customer research, but it can also be conducted by product management, marketing, and user experience teams.

Why does customer research matter?

Customer research provides decision-makers and product teams with extensive information on customers’ pain points, expectations, desires, and motivations. You can leverage this information to create customer personas, personalize brand messaging, identify new opportunities, and tailor products and services to your customers.

What is consumer research?

Consumer research consists of gathering information on consumer needs and preferences in relation to a product or service. It’s similar to customer research, but a consumer is any person who uses a product or service, while a customer is the person who pays for the product or service.

Capturing value from your customer data

In an increasingly customer-centric world, the ability to capture and use customer insights to shape products, solutions, and the buying experience as a whole is critically important. Research tells us that organizations that leverage customer behavioral insights outperform peers by 85 percent in sales growth and more than 25 percent in gross margin. 1 1. “Behavioral economics,” Gallup, gallup.com. Customer data must be seen as strategic.

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Yet most companies are using only a fraction of the data in their possession. Sprawling legacy systems, siloed databases, and sporadic automation  are common obstacles. Models and dashboards may be forced to rely on stale data, and core processes may require considerable manual intervention. Often, too, organizations may not have a clear understanding of the specific outcomes they’re looking to achieve through data optimization. All that is leaving significant value on the table.

How much, you ask? A McKinsey survey of more than 700 organizations worldwide found that spending on analytics  to gain competitive intelligence on future market conditions, to target customers more successfully, and to optimize operations and supply chains generated operating-profit increases in the 6 percent range.

Our work suggests that these returns don’t have to be confined to a handful of top players. Rather, when it comes to generating measurable value from their data , most organizations have plenty of low-hanging fruit they have yet to harvest.

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Here are three of the most promising avenues available now to most organizations.

Tease out critical patterns

Information on what customers purchase, how many times they contact customer service, and how long they linger on a given website can create an insightful narrative about buying habits and preferences. Most organizations capture much of this information, but often in isolated packets. Too few marry it all together. A bank, for instance, can minimize churn, fraud, and default risk by pooling customer data and applying advanced analytics to understand the needs and possible next actions of key segments. Those patterns can be used across the business. Credit-risk teams will want to know if a customer whose bank balance falls into the red more than once a quarter could be at higher risk for defaulting on a mortgage. Marketing could use the data to pitch financial-planning and overdraft-protection services. Such customer data can also be packaged, sanitized, and sold to relevant third parties, such as credit bureaus and payments companies—allowing the initial investment of analytics time and modeling to yield multiple dividends.

In addition, pattern data can be used to direct spending. An industrial-parts manufacturer, for instance, studied customer-buying histories, behavioral data, and surveys to understand the typical purchasing path for their highest-value segments. The data revealed that buyers were far more likely to rely on distributors for product recommendations and much less likely to be influenced by trade-show demonstrations and collateral. Marketers were able to reallocate budgets accordingly.

Others, led especially by consumer companies, are taking things further and using customer data to personalize outreach . By pulling together rich customer profiles and rigorously tracking response rates, marketers can know precisely what types of content over what channel and format are likely to have the greatest impact on key segments and microsegments. A decade ago, the tools weren’t available to do this. Now they are. And nearly all companies can benefit. An automotive insurer, for instance, learned that the customer journey to buy car-insurance policies typically starts 60 days before customers receive their first quote and usually involves an average of 15 signals. They can use that information to tailor the tone and timing of their outreach. Such personalization can deliver five to eight times the return on investment on marketing expenditure, and can lift sales by 10 percent or more.

Exponentially improve productivity

While frontline monetization opportunities tend to get the headlines, often the biggest, near-term gains are operational in nature. Data optimization helps reduce inefficiency. Many B2B companies, for instance, can find it hard to enforce pricing discipline  given their large and distributed field networks. Exceptions, all too often, can be the rule. But league tables, reporting dashboards, next-best-action analytics, and other solutions can have a profound impact, allowing managers to compare performance and see what pricing, discounts, and bundles are working at other, similar clients.

Data-enabled processes can also help businesses scale scarce institutional expertise by making specialist knowledge more readily available. A financial institution, for instance, found that its transaction specialists were being inundated with foreign-trade questions from regional offices. That was frustrating the head of transactions, who had hired the team to create a suite of new services. The team solved the problem by implementing a system based on artificial intelligence (AI) capable of capturing and interpreting reams of data to surface answers to the most commonly asked questions.

Similarly, better data integration across a range of internal and external sources can cut down on search times and help analysts, auditors, and others spend less time tracking down information and more time applying the results. Professionals can run the numbers on much bigger sets of data, do better vetting, and do it all faster, allowing specialists to apply their skills in other ways. While AI and machine-learning tools  do require a more significant investment of time and resources, many other capabilities can be created using tools and systems that most organizations have in place today, and then refined from there.

Forge breakthrough solutions and services

Upstart Network is a lending company whose specialized algorithms and nontraditional measures allow it to use a range of customer-background data to offer market-leading rates. Ginger.io similarly relies on customer data from smartphones and fitness wearables, such as sleep, mobility, and communication patterns, to improve clinical assessments and diagnose when patients with mental illness may be becoming symptomatic. Customer data is also enabling the creation of online marketplaces and bold new business models, such as Airbnb’s. They join a fast-growing list of companies that are using data to innovate breakthrough data applications and business models.

Such breakthroughs don’t have to be the preserve of digital pure plays, however. Many incumbent organizations have the advantage of long-standing client relationships, deep pockets of expertise, and scale. By prioritizing a handful of specific customer outcomes, such as reduced churn or improved cross-sell, and setting up small, dedicated cross-functional teams to experiment, refine, and release new approaches, established players can generate significant returns .

Making it happen

Organizations are at different data-maturity levels. But regardless of how far along a company is, virtually every organization has valuable customer data assets that could be put to better and more active use. Although the basic requirements of any strategic initiative still apply—articulating a strong and cohesive digital strategy , securing strong leadership backing and the right resources, and prioritizing one or two high-impact pilots—companies don’t need to wait until they have the “perfect” systems or technologies in place. These two foundational steps alone can open up a wellspring of opportunity.

Making data analytics work for you—instead of the other way around

Enrich customer data. Customer data should be enriched to incorporate digital profiles, life events, community information, transaction-based insights, customer preferences, sentiment scoring, and so forth in order to get a full picture of the customer. Organizations can capture digital profiles and digital activity by linking web, mobile, and social-presence data. Marketing or customer teams can start by attaching activities to customer profiles. Those activities might include customer-sentiment-behavior scores, insights derived from purchasing transactions, call-center queries, and online behavior. A property-and-casualty insurer, for instance, linked customer-footprint data from an online real-estate site to identify customers who might be considering moving. Agents could see that information on the customer’s profile and send potential customers a prepackaged quote for the relevant zip codes.

Make that data shareable and accessible. Using “two speed” IT , where specialist business and IT teams fast-track digital development, businesses can get a jump on high-value customer initiatives even as they build out their longer-term transformation. Software overlays can link data silos among different lines of business, and semantic layers can funnel information into a user-friendly interface. Integrating pertinent customer data and making it accessible across the business not only cuts down on duplicate information gathering and manual data entry but can also lead to offering customers lower prices, greater convenience, and improved experiences.

When a customer calls into a contact center to raise a concern, some organizations are able to update that interaction in real time, so that relevant parties across all the organizations can get a 360-degree view of the customer and better respond to her needs. Likewise, rather than holding up clinicians who wanted fast access to their patients’ complete medical histories, a dedicated digital-services team created a patient portal that allowed doctors to log on, search for a patient’s name, and receive an at-a-glance complete patient report including links to X-rays and other images. The portal masked the complexity of the underlying data environment and helped improve service, outcomes, pricing, and risk management. The team then worked with those managing the hospital’s larger digital transformation to migrate the portal over to the new environment once it was ready.

Companies getting started might consider a few key questions:

• What customer data can we turn into unique data products, and where does it reside?
• What external data could we acquire, and what third parties should we collaborate with to create data-driven value?
• Is there an opportunity to use customer data to create a marketplace to bypass or reshape an existing industry?
• What skill sets and capabilities will we need, and where can we find or develop them?

Brad Brown  is a senior partner in McKinsey’s Boston office, Kumar Kanagasabai is a partner in the New York office, Prashant Pant is an expert in the Chicago office, and  Gonçalo Serpa Pinto is a senior partner in the Lisbon office.

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Consumer Data

Unveiling the Power of Market Insights

Understanding, Valuing, and Utilizing Consumer Data

In a world where understanding consumer behavior is crucial for business success, consumer data emerges as a beacon of insight. It’s a powerful tool, offering a glimpse into the consumer’s mind, guiding strategic decisions in industries like B2C commerce and retail. This guide by NielsenIQ (NIQ) is your compass in the complex terrain of consumer data, designed for those seeking to harness its power for informed decision-making.

What Defines Consumer Data Today?

Consumer data is the lifeblood of modern business strategy, offering a window into the consumer’s world. It encompasses a variety of information types, from basic demographic details to complex behavioral patterns. In the digital era, the scope of consumer data has broadened, encompassing everything from online shopping habits to social media interactions. This data is not just numbers and statistics; it’s a narrative of consumer lives, telling stories that businesses can use to tailor their strategies.

The evolution of consumer data reflects the changing landscape of consumer interactions. With the advent of the internet and mobile technology, the amount of available data has exploded. Businesses now have access to real-time data streams, offering up-to-the-minute insights into consumer behavior . This data is diverse, including transactional records, online browsing activities, social media engagement, and even sensor data from smart devices.

The value of consumer data lies in its ability to inform decision-making. It helps businesses understand their customers’ needs, preferences, and pain points. This understanding is crucial in today’s competitive market, where personalization and customer experience are key differentiators. By analyzing consumer data, businesses can identify trends, predict consumer behavior, and make data-driven decisions that enhance customer satisfaction and drive growth.

However, the use of consumer data comes with its challenges. Privacy concerns and data security are at the forefront of consumer minds. Regulations like GDPR and CCPA have changed the way businesses collect and handle consumer data, emphasizing the need for ethical data practices. Businesses must navigate these challenges carefully, balancing the need for insights with respect for consumer privacy.

In summary, consumer data today is a dynamic and multifaceted asset. It offers invaluable insights but requires careful handling. As we delve deeper into the types and uses of consumer data, it’s important to keep in mind its evolving nature and the responsibilities that come with it.

Consumer and shopper insights

Understand consumer and shopper behavior, demographics, and loyalty with NielsenIQs solutions: modern, representative consumer panels and customer survey capabilities.

Types of Consumer Data

Consumer data can be categorized into several types, each offering unique insights into consumer behavior:

• Demographic Data: This includes basic information such as age, gender, income, and education level. It’s useful for segmenting the market and targeting specific consumer groups.
• Psychographic Data: This type of data delves into the consumer’s lifestyle, interests, values, and attitudes. It helps businesses understand the ‘why’ behind consumer choices.
• Behavioral Data: This is data related to consumer interactions with a brand or product, such as purchase history, website visits, and engagement with marketing campaigns. It’s crucial for understanding consumer habits and preferences.
• Transactional Data : This encompasses data generated from consumer transactions, including purchase history, payment methods, and spending patterns. It’s key for analyzing sales trends and consumer loyalty.

Each type of consumer data offers distinct advantages and plays a crucial role in building a comprehensive understanding of consumers. By combining these data types, businesses can gain a holistic view of their customers, leading to more effective marketing strategies and improved customer experiences.

First-party Data

First-party data is collected directly from your customers and includes interactions with your brand, such as website visits, app usage, and customer feedback. Tools like Analytics tools, CRM systems, and customer feedback platforms are pivotal in gathering this data. The key to harnessing first-party data lies in ensuring compliance with data protection laws like GDPR. Its main advantage is its accuracy and relevance, but it can be limited in scope.

This data type is invaluable as it’s gathered directly from the source – your customers. It provides the most accurate and relevant insights into consumer behavior, preferences, and attitudes. For instance, analyzing website traffic and user behavior can reveal which products are most popular and which marketing messages resonate with your audience.

However, collecting first-party data requires a strategic approach. Businesses need to have the right tools in place to capture and analyze this data effectively. This includes investing in robust analytics platforms and developing mechanisms to encourage customers to share their data, such as through loyalty programs or engaging online experiences.

Compliance with legal frameworks is another critical aspect of handling first-party data. With regulations like GDPR and CCPA in place, businesses must ensure that they collect and use consumer data ethically and transparently. This includes obtaining explicit consent from consumers and providing them with control over their data.

The pros of first-party data are significant. It offers high accuracy, relevance, and valuable insights for personalized marketing strategies. However, the cons include limited scope (as it only covers interactions with your brand) and the need for rigorous compliance with data protection laws.

In conclusion, first-party data is a powerful tool for businesses seeking to understand their customers better. When collected and used responsibly, it can drive personalized marketing strategies and enhance customer experiences, ultimately leading to increased loyalty and revenue.

Second-party Data

Second-party data is essentially someone else’s first-party data that you acquire directly from them. It’s more trustworthy than third-party data and can provide insights that you might not have captured. However, its relevance can vary, and there are potential privacy concerns to navigate.

This type of data is acquired through partnerships or direct purchases from another organization. For example, a retailer might partner with a complementary brand to access their customer data, providing insights into a broader market segment. This data is beneficial as it comes from a reliable source and can add depth to your existing data.

However, the relevance of second-party data can be a challenge. Since this data wasn’t collected with your specific needs in mind, it might not be entirely applicable to your business or customer base. It requires careful analysis to extract valuable insights.

Privacy and legal compliance are also crucial when dealing with second-party data. It’s essential to ensure that the data was collected ethically and that its use complies with privacy laws. This includes understanding the data collection practices of your partner and ensuring that data sharing agreements respect consumer privacy.

The pros of second-party data include its reliability and the opportunity to gain insights beyond your customer base. It can be a valuable asset in understanding broader market trends and consumer behaviors. The cons, however, include potential relevance issues and the need to navigate privacy concerns and legal compliance.

In summary, second-party data can be a valuable addition to your data strategy, offering new perspectives and insights. However, it requires careful selection and analysis to ensure its relevance and compliance with privacy laws.

Third-party Data

Third-party data is purchased from external sources and can provide a broader view of consumer behavior. While it expands your understanding of the market, its accuracy and relevance can sometimes be questionable. Additionally, with increasing privacy concerns and regulations, its future is uncertain.

This data type is often aggregated from various sources by third-party providers and includes a wide range of information, from demographic details to behavioral patterns. It’s commonly used to supplement first-party data, filling in gaps and providing a more comprehensive view of the consumer landscape.

However, the accuracy and relevance of third-party data can be a concern. Since this data is collected without a specific purpose or audience in mind, it may not align perfectly with your business needs. It’s essential to vet third-party data sources carefully and understand their data collection and aggregation methods.

Privacy and legal compliance are significant challenges with third-party data. With increasing scrutiny on data privacy and the rise of regulations like GDPR, the use of third-party data is becoming more complex. Businesses must ensure that their use of this data complies with all relevant laws and regulations.

The pros of third-party data include its ability to provide a broad view of the market and consumer behavior, which can be invaluable for identifying trends and opportunities. However, the cons include potential issues with accuracy and relevance, as well as the need to navigate an increasingly complex legal landscape regarding data privacy.

In conclusion, while third-party data can offer valuable insights, it requires careful consideration and handling. Businesses must balance the benefits of expanded market knowledge with the challenges of accuracy, relevance, and compliance.

Zero-party Data

Zero-party data is information that consumers willingly share with brands, often through direct interactions. This data is highly valuable as it is explicitly provided by the consumer, ensuring relevance and accuracy. However, collecting this data requires building trust with your audience.

This type of data is gathered through mechanisms where consumers intentionally and proactively share information. This can include preferences, purchase intentions, or personal context. Methods to collect zero-party data include interactive quizzes, polls, preference centers, and direct conversations.

The primary advantage of zero-party data is its high level of accuracy and relevance. Since consumers are choosing to share this information, it’s inherently trustworthy and can be used to create highly personalized experiences and products. It also demonstrates a level of consumer trust and engagement with your brand.

However, the challenge lies in encouraging consumers to share this data. Brands must create engaging and valuable experiences that incentivize consumers to provide their information. This requires creativity and a deep understanding of what drives your audience.

Compliance with legal frameworks is generally more straightforward with zero-party data, as consumers are giving their information willingly. However, it’s still important to handle this data responsibly and transparently, respecting consumer privacy and preferences.

The pros of zero-party data include its high accuracy, relevance, and the trust it signifies from consumers. The cons involve the challenge of encouraging consumers to share their data and the need to create engaging mechanisms for data collection.

In summary, zero-party data represents a goldmine of accurate and relevant consumer insights. When collected and used effectively, it can significantly enhance personalization efforts and strengthen consumer relationships.

How Consumer Data Is Captured

Capturing consumer data involves employing diverse methodologies, each offering distinct insights and advantages. Businesses seeking comprehensive consumer insights must grasp these methods to drive informed decision-making and enhance consumer experiences.

Website Analytics:

Analytics tools furnish insights into user behavior on websites, tracking metrics such as page views, session duration, and user flow. This data illuminates how consumers engage with online platforms, aiding in website optimization and content personalization.

Social Media:

Platforms with analytics tools feature data on consumer interactions with content, including likes, shares, comments, and demographic details, offering valuable insights for targeted marketing strategies.

Customer Feedback and Surveys:

Utilizing platforms for surveys, businesses can directly solicit feedback from consumers, gaining insights into product opinions, service satisfaction, and brand experiences. Partnering with survey experts offers the added advantage of professional expertise, ensuring robust data collection and analysis.

Customer Service Software:

Solutions for tracking customer interactions provide invaluable insights into consumer pain points and service efficiency. Integrating this data with broader consumer insights enhances operational efficacy and customer satisfaction.

Transactional Information:

E-commerce platforms and point-of-sale systems furnish data on consumer purchasing behavior, encompassing purchase history, payment methods, and buying patterns. Leveraging this data aids in inventory management, personalized marketing, and strategic decision-making.

Website Analytics

Understanding consumer behavior online is crucial for businesses, and website analytics are instrumental in achieving this goal. Various tools offer a wealth of information without reliance on specific brand names, allowing insights into user interactions with your website.

These tools track diverse metrics such as page views, bounce rates, session duration, and user flow, unveiling insights into page popularity, navigation patterns, and potential drop-off points. This data serves as a cornerstone for optimizing website design, enhancing user experience, and tailoring content to meet consumer needs.

In sectors like retail and e-commerce, website analytics unveil valuable insights into consumer shopping behavior. For instance, analyzing the user journey from product discovery to purchase uncovers opportunities to streamline the buying process and mitigate cart abandonment.

Yet, effective utilization of website analytics poses challenges. Coping with the vast volume of available data is a primary concern. Businesses must prioritize relevant metrics aligned with their objectives to prevent data overload. Furthermore, accurate interpretation of data is pivotal for making informed decisions.

The advantages of website analytics are profound, offering detailed insights into consumer behavior, trend identification, and data-driven decision-making to enhance the online experience. However, alongside these benefits come challenges, including the risk of data overload and the requisite expertise in data analysis.

In summary, website analytics serve as a powerful tool for businesses seeking to comprehend and enhance their online presence. By focusing on pertinent metrics and interpreting data judiciously, businesses can glean invaluable insights driving website optimization and bolstered consumer engagement.

Social Media

Social media analytics are essential for tracking, analyzing, and interpreting interactions and associations across social platforms, providing valuable insights without relying on specific brand names. Businesses utilize various tools to monitor social media mentions, engagement rates, and trend analyses.

In retail, social media data serves as a key informant of consumer trends and brand perception, guiding strategic marketing campaigns. E-commerce enterprises leverage social media analytics to understand consumer responses to products and services, facilitating tailored online presence and personalized marketing strategies. Similarly, for FMCG companies, social media analytics unveil consumer sentiments about products, shaping product development and marketing endeavors.

However, the landscape of social media analytics presents challenges. The dynamic nature of social platforms’ algorithms necessitates constant adaptation to remain effective. Additionally, the qualitative aspect of social media data demands sophisticated tools and expertise for accurate interpretation.

In summary, social media analytics offer businesses invaluable insights into consumer behavior and market trends. By navigating the challenges inherent in this field and employing judicious interpretation, businesses can harness the power of social media analytics to drive informed decision-making and enhance consumer engagement.

Customer Feedback and Surveys

Understanding consumer opinions and preferences through direct methods such as customer feedback and surveys is paramount for businesses, with various tools available for data collection without mentioning specific brands.

In retail, customer feedback serves as a window into in-store experiences and product preferences, guiding inventory management and customer service strategies. For e-commerce enterprises, survey data illuminates user experience on their platforms, facilitating enhancements in website design and functionality. Similarly, FMCG companies leverage surveys to assess product satisfaction and demand, informing product development and marketing initiatives.

However, the efficacy of customer feedback relies on overcoming certain challenges. Ensuring a representative sample and interpreting data in the context of broader market trends are pivotal. Additionally, encouraging customer participation can pose difficulties.

In summary, customer feedback and surveys offer businesses profound insights into consumer sentiments and preferences. Overcoming the challenges inherent in gathering and interpreting this data allows businesses to make informed decisions, enhance product offerings, and fortify consumer relationships.

Customer Service Software

Capturing data from customer interactions, customer service software offers insights into common issues, customer needs, and service efficiency, without relying on specific brand names. Platforms like Zendesk and Salesforce facilitate this data capture process.

Retail businesses leverage this data to enhance in-store service and address prevalent customer concerns effectively. Similarly, e-commerce companies derive benefits from understanding online customer service interactions, which inform improvements to website FAQs and chatbot programming. Additionally, for FMCG companies, customer service data unveils product issues and aids in quality control measures.

However, integrating this data with other consumer insights poses challenges. Achieving a holistic view requires seamless integration with broader consumer data streams. Moreover, managing and analyzing large volumes of customer service data demands robust systems and processes to derive meaningful insights.

In conclusion, customer service software provides businesses with invaluable insights into customer needs and service efficiency. Overcoming challenges in data integration and management empowers businesses to make informed decisions, enhance service offerings, and foster stronger customer relationships.

Transactional Information

Transactional information refers to data gathered from customer purchases, including details about the products bought, the amount spent, and the frequency of purchases. Tools for collecting this data include POS systems and e-commerce analytics platforms.

In retail, transactional data is crucial for inventory management and understanding buying patterns. E-commerce businesses use this data to personalize recommendations and optimize pricing strategies. FMCG companies can track product performance and consumer buying habits, informing production and distribution decisions.

The challenge with transactional data is ensuring privacy and security, especially with sensitive payment information. Additionally, interpreting this data requires sophisticated analytics to derive meaningful insights.

Each of these methodologies offers unique insights into consumer behavior and preferences. By employing a combination of these tools, businesses can cultivate a comprehensive understanding of their customer base, facilitating targeted strategies and enhanced consumer engagement.

However, effective data collection necessitates a strategic approach, ensuring alignment with organizational goals and compliance with privacy regulations. Furthermore, proficient data analysis is paramount for deriving actionable insights that drive business growth and foster positive consumer relationships.

In conclusion, capturing consumer data is a multifaceted endeavor, demanding strategic planning and adept utilization of resources. When executed thoughtfully, it empowers businesses to make informed decisions, optimize operations, and deliver exceptional consumer experiences.

How Is Consumer Data Used?

Consumer data is used across industries in various ways:

• Targeted Advertising: Tailoring ads based on consumer behavior and preferences.
• Customer Profiling: Creating detailed consumer profiles for personalized marketing..
• Market Research: Understanding market trends and consumer needs.
• Product Development: Informing new product design based on consumer feedback.
• Personalized Recommendations: Tailoring product suggestions in e-commerce.
• Customer Service Improvement: Enhancing service based on customer feedback.
• Inventory Management: Stocking products based on buying patterns.
• Pricing Strategies: Setting prices based on consumer data analysis.
• Brand Perception Analysis: Understanding how consumers view the brand.
• Risk Management: Identifying potential market risks based on consumer trends.

Each use case is tailored to specific industry needs, leveraging consumer data to drive decision-making and strategy development.

Dig Deeper on Risk Management and Governance

In the context of data governance, risk management involves identifying, assessing, and mitigating risks associated with consumer data. This includes ensuring data accuracy, protecting consumer privacy, and complying with regulations like GDPR and CCPA. Effective data governance ensures that consumer data is used ethically and responsibly, maintaining consumer trust and safeguarding the company’s reputation.

Targeted Advertising

Targeted advertising uses consumer data to deliver relevant ads to specific audiences. This requires data on consumer behavior, preferences, and demographics. Consumers benefit from receiving ads that are more relevant to their interests, potentially improving their shopping experience. For marketers, targeted advertising increases the efficiency of ad spend by reaching the most relevant audience.

In retail, targeted ads can drive in-store traffic by promoting relevant products. E-commerce businesses use it to increase conversion rates by showing ads based on browsing behavior. FMCG companies can target specific consumer segments, increasing the effectiveness of their marketing campaigns.

However, the challenge lies in balancing personalization with privacy concerns. Additionally, over-reliance on targeted ads can lead to ad fatigue among consumers.

Customer Profiling

Customer profiling involves creating detailed profiles of customers based on their data. This helps businesses understand their customers’ preferences, behaviors, and needs. Consumers benefit from more personalized experiences and products that better meet their needs. For marketers, customer profiling is essential for personalizing marketing efforts and developing targeted strategies.

Retail companies use customer profiles to tailor in-store experiences and product offerings. E-commerce businesses leverage profiles to personalize online shopping experiences.

For e-commerce businesses, customer profiling is crucial for personalizing the online shopping experience, offering tailored recommendations, and improving customer engagement. FMCG companies can use these profiles to understand consumer preferences, leading to more effective product development and targeted marketing campaigns.

The challenge in customer profiling lies in accurately integrating and interpreting data from multiple sources. Additionally, there is a need to balance personalization with consumer privacy concerns, ensuring that data collection and usage comply with legal standards and ethical considerations.

Microtargeting

Microtargeting involves using consumer data to target specific groups of people with highly tailored messages. This strategy is based on the analysis of various data points, including consumer behavior, purchase history, and personal preferences.

Consumers benefit from microtargeting through highly relevant and personalized interactions, which can enhance their experience with a brand. For marketers, microtargeting allows for more efficient use of resources, focusing efforts on the most receptive audiences, and increasing the likelihood of conversion.

In retail, microtargeting can help in creating personalized promotions and offers. E-commerce businesses can use it to target specific user segments with tailored product recommendations. FMCG companies can leverage microtargeting for launching targeted marketing campaigns for new products or in specific regions.

However, microtargeting also presents challenges, particularly in ensuring data accuracy and avoiding consumer privacy infringement. Over-targeting can lead to consumer discomfort and potential backlash, making it crucial for marketers to find the right balance.

CX Personalization

Customer Experience (CX) personalization is the practice of tailoring the customer’s experience based on their preferences, behavior, and history. This approach can significantly enhance customer satisfaction and loyalty.

Consumers benefit from CX personalization through more relevant and enjoyable interactions with brands, leading to a better overall experience. For marketers, personalizing the customer experience can lead to increased customer retention, higher conversion rates, and improved brand perception.

In retail, CX personalization can manifest in personalized shopping experiences, both online and in-store. E-commerce platforms can use it to customize the user interface, product recommendations, and communication. FMCG companies can personalize marketing messages and product offerings based on consumer preferences and purchase history.

The challenges of CX personalization include managing and analyzing large sets of data and ensuring that personalization strategies are not intrusive or perceived as invasive by consumers.

Create a 360-degree View of Each Consumer with Consumer Data

Creating a 360-degree view of each consumer involves integrating various data points to form a complete picture of the customer. This comprehensive view is based on data from multiple sources, including transactional data, online behavior, customer feedback, and social media interactions.

This approach allows businesses to understand their customers’ needs, preferences, and behavior in depth. It’s crucial for developing personalized marketing strategies, improving customer service, and enhancing product development. Retail, e-commerce, and FMCG industries, in particular, can benefit significantly from this holistic view, as it enables them to tailor their offerings and communications to meet the specific needs of different customer segments.

The challenge in creating a 360-degree view lies in effectively integrating and analyzing data from diverse sources and ensuring that the data is up-to-date and accurate.

Luxury Buyer

A Luxury Buyer is a consumer segment characterized by their purchasing of high-end products and services. Identifying a Luxury Buyer involves analyzing data points such as transaction history (high-value purchases), brand preferences (preference for luxury brands), and lifestyle indicators (travel, entertainment choices).

Tools like advanced CRM systems, analytics platforms, and AI-driven insights can be used to identify and understand this segment. Key Performance Indicators (KPIs) for identifying Luxury Buyers might include average transaction value, frequency of high-value purchases, and engagement with luxury brand content.

In terms of legal implications, it’s crucial to ensure that data collection and analysis comply with privacy laws and regulations. Retail and e-commerce industries, particularly those dealing in luxury goods, can benefit from identifying Luxury Buyers to tailor their marketing and product offerings. Other industries like high-end hospitality and luxury travel can also benefit from this data.

Tech-Savvy Millennial

Tech-Savvy Millennials are characterized by their proficiency with technology and digital platforms. Identifying them involves looking at data points like digital engagement (social media use, app usage), technology purchases, and online shopping behavior.

Tools for identifying Tech-Savvy Millennials include social media analytics, website behavior tracking, and e-commerce analytics. KPIs might include frequency of online purchases, engagement rates on digital platforms, and preferences for tech-related products.

Legal considerations revolve around ethical data use and compliance with digital privacy regulations. Industries that can benefit from identifying Tech-Savvy Millennials include e-commerce, consumer electronics, and digital services. This data helps in tailoring digital marketing strategies, product development, and enhancing online customer experiences.

Eco-Conscious Car Owner

An Eco-Conscious Car Owner is a consumer who prioritizes environmental sustainability, especially in their transportation choices. Identifying them involves analyzing data points like vehicle type (hybrid, electric), engagement with environmental content, and lifestyle choices indicative of eco-consciousness.

Tools for this analysis include vehicle registration data, social media analytics, and consumer survey data. KPIs might encompass the type of vehicle owned, participation in environmental programs, and purchasing patterns of eco-friendly products.

Legal implications include respecting consumer privacy and ensuring data accuracy. Industries like automotive, renewable energy, and sustainable consumer goods can benefit from this data, using it to tailor marketing strategies, product development, and customer engagement initiatives.

Holiday Gift Givers

Holiday Gift Givers are consumers who actively purchase gifts during holiday seasons. Identifying them involves looking at data points like seasonal purchase patterns, engagement with holiday-related promotions, and gift-related search history.

Tools for this analysis include e-commerce analytics, POS data, and search engine analytics. KPIs might include frequency and volume of purchases during holiday seasons, engagement with holiday campaigns, and types of products purchased.

Legal considerations involve ethical data use and compliance with marketing regulations. Industries like retail, e-commerce, and FMCG can benefit from this data by optimizing their holiday marketing campaigns, inventory management, and promotional strategies.

Customer Data Trends

Current trends in customer data include the increasing importance of privacy and data security, the shift towards more personalized and targeted marketing, and the use of AI and machine learning for data analysis. There’s also a growing emphasis on real-time data analysis and the integration of offline and online data to create a holistic view of the customer. These trends reflect the evolving landscape of consumer data, emphasizing the need for businesses to adapt their strategies to remain competitive and relevant.

Cookieless Marketing

Cookieless marketing refers to advertising strategies that do not rely on cookies for tracking user behavior. This approach is gaining traction due to increasing privacy concerns and regulatory changes. Cookieless marketing is beneficial as it respects user privacy and aligns with new data protection laws. However, it poses challenges for marketers accustomed to cookie-based tracking, requiring them to find alternative methods for collecting and analyzing consumer data.

In industries like retail and e-commerce, cookieless marketing necessitates a shift towards first-party data and contextual advertising. FMCG companies must also adapt by leveraging direct customer relationships and exploring innovative data collection methods. The pros include enhanced consumer trust and compliance with privacy regulations, while the cons involve the challenge of adapting to new technologies and potentially losing some granularity in data insights.

Retailers may face challenges in tracking customer journeys, but can benefit from a more positive brand perception. E-commerce platforms need to innovate in customer engagement and retention strategies without relying on cookies. For FMCG, the focus shifts to brand loyalty programs and direct consumer interactions to gather data.

Becoming Harder to Collect Customer Data

The increasing difficulty in collecting consumer data stems from heightened privacy concerns and stricter data protection laws. Consumers are more aware and cautious about how their data is used, leading to resistance against traditional data collection methods.

For marketers, this trend means navigating a landscape where data is not as readily accessible. The challenge lies in respecting consumer privacy while still gathering meaningful insights. Retail industries must focus on building trust and transparency to encourage data sharing. E-commerce platforms need to innovate in non-intrusive data collection methods, such as enhanced customer interactions and feedback mechanisms.

The pros include building stronger customer relationships based on trust and respect for privacy. However, the cons involve the need for more sophisticated data collection strategies and potential limitations in data availability and depth.

Customers Demand Personalization

Personalization in the context of the customer journey refers to tailoring the shopping experience to individual preferences, both online and offline. This trend is significant for marketers as it directly impacts customer satisfaction and loyalty.

Personalized experiences can lead to increased customer engagement and sales for businesses. Retail industries can use personalization to enhance in-store experiences, while e-commerce platforms can tailor the online shopping journey. FMCG companies can benefit from personalized marketing messages and product recommendations.

The pros of personalization include increased customer satisfaction and potential for higher sales. However, the cons involve the complexity of effectively managing and analyzing large sets of data to create truly personalized experiences.

Brands Build Communities

Building communities means creating spaces where customers can engage with the brand and each other, often around shared interests or values. This is important for brands as it fosters loyalty and creates advocates for the brand.

In retail, community building can be around product categories or lifestyle interests. E-commerce platforms can create online communities for customer engagement and feedback. FMCG brands might focus on communities centered around specific product uses or values, like sustainability.

The pros include enhanced brand loyalty and customer engagement. The cons can involve the resources required to build and maintain these communities and the need for consistent, value-driven content to keep the community engaged.

Customers Want to Know How Brands Use Their Data

Customers increasingly want transparency in how their data is used. This trend is driven by growing privacy concerns and the desire for control over personal information.

Brands can ensure they are using data according to customer preferences by being transparent about data collection and usage practices, and by providing options for customers to control their data. This includes clear communication about data practices and easy-to-use privacy settings.

The benefit of this approach is increased customer trust and loyalty. However, the challenge lies in balancing effective data use with transparency and customer control.

In conclusion, understanding and leveraging consumer data is crucial for businesses in today’s data-driven world. NielsenIQ (NIQ) and GfK provide the expertise and tools necessary to navigate this complex landscape. From capturing and analyzing different types of consumer data to applying these insights for targeted marketing, customer profiling, and risk management, NIQ and GfK empowers businesses to make informed decisions.

Explore our range of solutions to harness the full potential of consumer data:

• NielsenIQ’s Homescan : Track, diagnose, and analyze consumer behavior from more than 250,000 households across 25 countries.
• NielsenIQ’s Omnishopper : Capture consumer purchases across online and offline channels for a complete view of changing omnichannel behaviors.
• Consumer analytics : Go deeper and create more clarity around shopper behavior with custom surveys and segmentation.
• C onsumption moments : Reveal the true motivations behind customer consumption behavior and usage to guide product innovation and marketing strategy.
• gfknewron Consumer: Understand your consumers’ behavior to redefine your success
• gfknewron Consumer Audience Profiler: Simplify the complex consumer journey into a single framework to know your buyers better than ever before
• GfK Consumer Life: A robust and stable international consumer segmentation study based on values, lifestyle, buying behavior and affinity for tech. Can be customized by market and product.

With NIQ’s and GfK’s expertise, businesses can effectively navigate the evolving landscape of consumer data, ensuring compliance, enhancing customer experiences, and driving growth.

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Customer Research Methods: Key Strategies for Market Insights in 2024

• Customer surveys : Survey tools such as Survicate are essential for conducting quantitative and qualitative research across various customer touchpoints and improving digital CX
• Diverse research methods : Employ a mix of customer research methods like different types of surveys , interviews, focus groups, observational studies, and usability testing to gain comprehensive insights into customer behavior and product interaction.
• Importance of continuous feedback : Establishing feedback loop mechanisms is crucial for ongoing improvement, ensuring that products and services evolve in response to customer needs .
• Data analysis : Systematic data collection followed by thorough analysis using appropriate customer research tools is key to identifying trends and making informed decisions. ‍
• Actionable feedback : Prioritize and strategize based on research findings to create actionable insights that drive measurable improvements in customer experience management and business processes.

Cutting through the chatter to hear your customers' true opinions is no small feat.

Tailored for business owners and marketers, this article zeroes in on how to conduct customer research . We'll highlight the strategies that directly connect you to your audience's preferences and pain points. By tapping into these insights, you'll be equipped to make informed, impactful business decisions.

Dive in to transform customer feedback into a clear direction for your brand's growth and success.

What is customer research?

Customer research is an essential practice focused on collecting data about your customers to understand their characteristics, needs, and behaviors.

Why is customer research important?

• Informed Decision-Making: You gain actionable insights into customer preferences and satisfaction, empowering you to make data-driven decisions.
• Enhanced Customer Experience: Understanding what your customers value guides your efforts to improve their experiences with your product or service.
• Strategic Focus: Tailoring your business strategy becomes more focused as you identify key demographics and market segments.
• Product Development: Product features and improvements align better with customer expectations when informed by customer research.
• Competitive Edge: Detailed knowledge about your customers can give you a competitive advantage by identifying opportunities and gaps in the market.

Customer research vs. market research

Customer research and market research serve distinct purposes in understanding buyers and the competitive environment.

Customer research dives deep into your existing or potential customers' behaviors, needs, and preferences . It aims to create a detailed understanding of the customer journey , from awareness to purchase and is often qualitative in nature.

On the other hand, market research takes a broader approach, examining the market as a whole, including industry trends, competitor analysis, and market share.

While customer research is about the 'who' and 'why' behind purchasing decisions, conducting market research addresses the 'what' and 'how' of market conditions and opportunities.

Both types of research are crucial for informed decision-making but focus on different aspects of the business landscape. Customer research is about improving the customer experience and tailoring products or services to consumer needs. Market research is about understanding the market landscape to strategize and position offerings effectively.

Primary research vs. secondary research

In customer research, understanding the distinction between primary research and secondary research is crucial for choosing the right approach to obtain your insights.

Primary research

Primary research involves collecting data firsthand for your specific research goal. This data is original and gathered through methods directly controlled by you. Examples include:

• Surveys and questionnaires : Deploying custom surveys to collect customer feedback on a new product or service.
• Interviews : Conducting one-on-one dialogues to dive deep into customer opinions and experiences.
• Focus groups : Facilitated group discussions to obtain a range of perspectives on a particular topic.

Secondary research

Secondary research methods rely on data previously collected by others. It's an evaluation of existing information that may include:

• Industry Reports : Analyzing market research findings related to your sector.
• Academic Journals : Reviewing studies and papers for trends and outcomes that align with your interests.
• Market Analysis : Assessing competitor data and market summaries to inform your strategies.

Types of customer data

Before diving into specific categories, understand that customer data is essential to personalize your marketing strategies and enhance customer experiences. This data comes in two core types: qualitative and quantitative.

Qualitative data

Qualitative research gathers non-numeric information that captures your customers' opinions, motivations, and attitudes. This data often comes from:

• Interviews , direct conversations that provide in-depth insights.
• Open-ended survey responses allow customers to express their thoughts in their own words.

Quantitative data

Quantitative research collects numerical data and can be measured and analyzed statistically. Key sources include:

• Transaction records : Sales data showing purchasing patterns.
• Website analytics : Metrics like page views and click-through rates representing user behavior.

Best customer research methods

When conducting customer research, you need to select the right methodology to gain valuable insights. Various research methods cater to different needs, from understanding user behavior to gauging customer satisfaction.

Customer surveys and questionnaires

Deploy online surveys and questionnaires to quickly gather quantitative and qualitative data from a large audience. For example, a survey tool such as Survicate offers a variety of different distribution channels:

• surveys embedded in emails
• website pop-up surveys
• mobile app surveys
• link surveys
• in-product surveys

Surveys are a cost-effective way to gather market research insights from the entire customer digital journey . If you use them as a part of a feedback loop, they can help you improve the CX considerably.

widely via email, websites, or social media platforms. Ensure your questions are direct and easy to understand to maximize response rates.

Conduct interviews to collect in-depth qualitative data. One-on-one interviews allow for a deep dive into customer opinions, beliefs, and experiences. Record these sessions, if possible, to ensure that none of the details are lost.

Focus groups

Utilize focus groups to explore customer attitudes and behaviors in a group setting. This method sparks conversation and can uncover insights that might not surface in one-on-one interactions. Be wary of group dynamics such as conformity, which can influence individual responses.

Observational studies

Observational studies involve watching how users interact with your product in their natural environment. This method provides unfiltered, real-world user behavior that can be invaluable in understanding how your product is used.

Usability testing

Usability testing is imperative for evaluating the functionality and design of your product. Recruit participants to complete specific tasks while observers note where they encounter issues or experience confusion.

Field trials

Conduct field trials by providing users a prototype or beta version of your product for a certain period. This hands-on approach yields feedback on your product's performance in real-life scenarios.

Review mining

Lastly, review mining involves analyzing customer feedback found in online reviews and forums. This passive method is particularly useful for identifying common pain points and areas for improvement without the need for direct interaction.

Types of customer research

Customer research encompasses various methodologies aimed at understanding your market and clientele. Tailoring these approaches helps you stay informed and make data-driven decisions.

Competitive research

You analyze your competitors to benchmark your products, services, and customer satisfaction levels against them. This helps in identifying industry standards and areas for improvement.

Customer journey mapping

Journey mapping involves charting the steps your customers take, from discovering your brand to making a purchase and beyond. It's a strategic approach to understanding customer interactions with your brand.

Buyer persona research

You create detailed profiles of your typical customers based on demographic and psychographic data. These personas help in crafting targeted marketing strategies.

Customer experience research

You assess customers' overall experience with your brand, from the usability of your website to customer service interactions, to optimize every touchpoint.

Customer segmentation research

Market segmentation divides your customer base into distinct groups based on common characteristics to provide more personalized products and services.

Customer needs research

You investigate your customers' underlying needs and desires to develop products that solve specific problems or enhance their lives.

Customer satisfaction research

You measure how your products and services meet, exceed, or fall short of customer expectations, often using surveys, feedback forms, and follow-up interviews.

Pricing research

You evaluate customers' responses to pricing changes and their perception of your product's value to establish an optimal pricing strategy.

Brand perception research

You gauge how customers perceive your brand to ensure your messaging aligns with their beliefs and your company values.

Designing a research plan

Precision and structure are pivotal for gathering actionable insights in constructing a customer research plan. These steps will guide you through creating an effective framework for your research efforts.

Set objectives

Identify what you want to achieve with your research. For instance, you may aim to understand customer satisfaction , identify buying patterns, or test product concepts. These objectives should be Specific, Measurable, Achievable, Relevant, and Time-bound (SMART) to ensure clarity and focus.

Identify target audience

Determine who your customers are by segmenting the market. To accurately represent your overall market, include demographics, psychographics, and behaviors in your segmentation. Knowing your audience can tailor your research to yield more relevant data.

Recruit participants

Once you know who to target, select participants who best represent your customer base. Employ strategies such as customer databases, social media outreach, or third-party panels to gather a varied group that reflects your target audience's diversity.

Choose appropriate methods

Your objectives will dictate the methods you choose. Qualitative approaches like interviews afford depth, while quantitative methods like surveys provide breadth. Select the right blend of methods to gain a multidimensional view of customer sentiments.

Sampling techniques

Employ sampling techniques to generalize your findings. Random sampling ensures everyone has an equal chance of selection, while stratified sampling involves dividing your audience into subgroups and sampling from these categories to ensure all segments are represented.

Build a continuous process with feedback loops

Establish ongoing mechanisms to capture customer feedback regularly. This could involve periodic surveys or real-time feedback systems. Make sure you continuously iterate your product or service based on this input, creating a virtuous cycle of improvement.

Data collection and analysis

Effective customer research hinges on the systematic collection and meticulous analysis of data to decipher patterns, understand behaviors, and make informed decisions.

Gather data systematically and analyze it to uncover patterns and trends. Use analytical tools that can handle your data type and amount. Look for relationships between variables and compare these findings against your goals.

Quantitative data analysis

You'll handle numerical data that can be measured and compared in a straightforward manner. Quantitative analysis often employs statistical tools to interpret data sets and deduce meaningful insights. Common techniques include:

• Descriptive Statistics: Summarize your data through means, medians, and modes.
• Inferential Statistics: Make predictions and infer trends from your sample data.
• Regression Analysis: Determine the relationship between variables.

Qualitative data assessment

With qualitative data, your focus is on interpretative analysis of non-numerical information, such as customer interviews or open-ended survey responses. Key approaches involve:

• Thematic Analysis: Identify patterns or themes within qualitative data.
• Content Analysis: Categorize text to understand the frequency and relationships of words or concepts.
• Narrative Analysis: Explore the structure and content of stories to gain insights into customer perspectives.

Mixing methods

Combining quantitative and qualitative analysis can provide a holistic view of your customer research. Employ a 'mixed methods' strategy to:

• Validate findings across different data types.
• Gain a richer, more nuanced understanding of research questions.
• Balance the depth of qualitative assessment with the generalizability of quantitative analysis.

Interpreting and reporting results

Turn your data into action by using insights to inform business decisions. Whether it is refining product features or adjusting marketing strategies, use the research to create value for your customers and your business.

Drawing conclusions

When you are ready to draw conclusions from your customer research, begin by assessing the data's significance. Look for patterns and trends in the feedback and quantifiable data. Tabulate your findings when possible, as this makes comparisons clearer:

• Quantitative Data : Calculate averages, frequencies, and percentages. A table showing the response distribution for each question can clarify these statistics.
• Qualitative Data : Group feedback into themes. For instance, list common descriptors used by customers when discussing a product feature.

Conclusions should directly relate to the research objectives you set before the study.

Creating actionable insights

After drawing conclusions, it's crucial to translate them into actionable insights:

• Prioritize : Determine which findings substantially impact your objectives or pose the biggest challenge to your CX.
• Strategize : For each priority area, brainstorm potential strategies. This may involve a simple list or a SWOT analysis (Strengths, Weaknesses, Opportunities, Threats) for complex decisions.

Always ensure that your insights are actionable; they should inform decisions and lead to measurable improvement in consumer experience or business processes. Communicate these insights with clear, straightforward language to the relevant stakeholders in your organization.

Emerging trends in customer research

Conduct market research with ai.

Customer research is adapting to leverage cutting-edge technologies. You'll notice a significant shift towards harnessing data analytics and artificial intelligence (AI) to derive deeper insights into customer behavior.

You can leverage Survciate AI-powered features as well. Try the AI survey creator that will design your customer or market research survey in under a minute after you describe your needs and objectives.

After you collect feedback, you can use the AI Topics feature to speed up getting qualitative insights. It will automatically categorize and summarize answers to your open-ended questions. Worth trying, isn't it?

Social listening

Social listening tools are another trend on the rise. They enable you to monitor your brand's social media presence and gather direct feedback from conversations about your products or services. Mobile ethnography also offers a way to observe customer interactions in a natural setting, providing contextually rich data.

Predicting customer behavior

Lastly, as the emphasis on personalization grows, predictive analytics are being adopted to tailor customer experiences. These techniques analyze past behavior to anticipate future needs, enhancing your ability to meet customer expectations preemptively.

Remember, these methods involve collecting various forms of customer data, so being vigilant about privacy and ethical data use is crucial. Follow regulations and best practices to ethically manage the information you gather.

Survicate for your market and customer research

As we've explored, the key to thriving in the current market is to truly understand your customers. The challenge, however, lies in efficiently gathering and interpreting their feedback to inform your business strategies.

With its user-friendly interface, Survicate allows you to create targeted surveys, collect real-time feedback, and analyze the data with ease, ensuring that every customer voice is heard and accounted for.

Survicate's suite of features simplifies the process of connecting with customers and extracting the insights you need to make data-driven decisions. Whether it's through NPS , customer satisfaction surveys, or user experience research, Survicate provides the clarity and direction required to adapt and excel in a fast-paced market.

For those ready to elevate their customer research, consider giving Survicate a try. Start your journey to clearer insights today with a free 10-day trial of the Business Plan , and experience the full potential of focused customer feedback. Take the step today, and transform the way you connect with your audience.

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16 top customer insight tools for effective customer research

Last updated

16 March 2024

Reviewed by

Gone are the days when you were left wondering why your customers weren’t more engaged, why they didn’t respond well to a new product, or why they dropped off before paying for their shopping cart.

With advanced customer insight tools readily available, there’s no reason to wonder. It’s simpler than ever to deeply understand your customers, discover new insights, and ultimately deliver better experiences.

• What is customer research?

Customer research offers insights into your customers, helping you gain a deep understanding of their wants, needs, and pain points. It allows you to recognize their key motivations and behaviors so that you can deliver better, more satisfying products.

While there are some similarities, it’s important to recognize that customer research is distinct from market research and user research .

Market research is typically conducted in the early stages of product development to understand market readiness, size, competition, and demographics.

User research focuses on a specific subset of product users or aspects of a product. This helps product teams develop user-centric products.

Customer research is the process of gathering and analyzing customer data and information to gain key insights for more customer-centric products and services.

• What are customer insight tools?

Your customers leave a trail behind them every time they perform an action. This trail helps you better understand them, including their wants, needs, and preferences, so that you can continually evolve your business and boost customer centricity .

Customer insight tools (or consumer insight tools) are technologies that can gather, store, and analyze information about customer behaviors and preferences.

Here are some common types of customer insight software:

Survey tools

Online surveys are a common way to better understand your customers’ wants and needs .

Whether it’s a pop-up questionnaire that appears after a customer interaction, a mailout, or a post-purchase survey, these tools can help your team get into your customers’ minds at key parts of the purchasing journey.

Analytics tools

Analytics, in general, can reveal more about your customers, helping you improve your offering.

Web analytics tools analyze website visits in terms of demographics, visit duration, pages visited, and more. This helps highlight patterns and trends among your customers and can inform essential website improvements over time.

Diagnostic analytics tools can help reveal issues and areas of friction where customers may be slowed down unnecessarily. Meanwhile, predictive analytics tools offer insights into future customer behavior, helping you plan and forecast more effectively.

Heatmap tools

Heatmap and click-tracking tools enable you to discover your customers’ movements on your website or app. These are visual representations of the customer’s journey as they interact with your product, helping your team discover what is and isn’t delivering sales conversions.

Usability testing

Tools that allow your team to test user experiences with your products can be very helpful for launches and post-launch optimization.

Usability testing tools can collate and analyze data on areas of friction in products, helping highlight where you can offer more seamless and meaningful experiences.

Customer feedback

Some tools can analyze customer feedback (through the net promoter score , for example) to help your team discover overall sentiment toward the product and business. This can help you better understand customers and make improvements at a more rapid pace.

Social media listening

Social media listening tools can help you understand current trends, mentions, commonly asked questions, and overall sentiment toward your business.

These tools analyze comments and mentions about the business and its products, providing insights that can lead to positive actions.

Many new artificial intelligence (AI) tools can assist with consumer insights.

Machine learning tools, for example, can process large amounts of data and help teams predict future customer behavior and anticipate trends.

They can also surface key data quickly, facilitating prompt action. This can boost proactive decision-making and help the business plan more efficiently for the future.

• Why are customer insights platforms crucial for businesses?

Deeply understanding your customers helps you deliver much better experiences for them. Customer insights software and platforms can make the process of learning about your customers significantly faster, easier, and more effective.

A customer insight platform can help in several essential areas:

Data accuracy

Advanced tools can help researchers collect, store, and analyze data for faster and more accurate insights. This helps boost the amount of data that researchers can gather, improving accuracy.

Optimized experiences

Teams can use the insights obtained from large datasets to optimize customer experiences.

Detailed data from a website checkout, for example, can help teams understand where there are areas of friction and then streamline those experiences for better conversions. Obtaining this amount of data is rarely possible without advanced tools.

Better decision-making

Relying on larger datasets, more accurate data, and tools such as machine learning and predictive analytics tools enables you to anticipate trends and consumer behavior. With these insights, you can make better and more informed decisions, boosting business success over time. 

Personalization

Customer data allows you to unlock more in-depth details and better understand each customer, meaning you can personalize their experiences to make them more satisfying.

Boosted customer engagement

Data that helps teams streamline and optimize the customer experience tends to boost customer engagement , satisfaction, and loyalty, upgrading overall business performance.

• What should you look for in a customer insight tool?

The customer insight tool should help you deliver optimized experiences by providing data and information that tells you more about your customers’ needs , preferences, and frustrations. Assessing the tool’s usefulness in this respect is the most important part of deciding whether it’s right for you and your business.

Here are some other key considerations:

The right customer insight tool will be relevant and helpful. It should align with your overall business (or project) goals.

Scalability

As your business grows, the tools you use should be able to scale with you, providing more detailed insights. If the tools you onboard don’t scale, you’ll be forced to migrate to new platforms, which can be a time-consuming, convoluted, and expensive process.

When dealing with data, especially personally identifiable information (PII) , your systems must be highly secure and compliant with all regulations. For multinational companies, this can mean being compliant across multiple jurisdictions.

Choosing platforms and tools that are both secure and compliant is essential. Examples include systems that offer AI protection, complex password protection, encryption, and other security measures.

Keep in mind that only the necessary people should be able to access the data to minimize risk.

User-friendliness

Ease of use is another key factor to look out for. In today’s world, people expect the highest level of user experience from whatever they use, whether that’s smartphones, websites, or software. As a result, the technologies your business adopts should provide the same level of usability.

All tools and platforms should be simple to use and obtain results effectively to save the team time and avoid any unnecessary friction.

Cost-effectiveness

Any platforms or tools your business uses should be cost-effective. Performing a cost–benefit analysis can be helpful to assess the overall advantages a tool may provide over time. This can allow you to understand whether the initial investment will eventually pay off as well as the different tiers and costs that will be available to you as you scale. 

Positive customer support

The company behind that platform must be able to support your team as you use their tool. Having multiple points of contact—through live chat, phone calls, emails, and more—is important to ensure you get the guidance and answers you need to keep your workflows running smoothly.

High ratings

Before onboarding new tools, read reviews from impartial customers to gauge their opinions and experiences. This will help you determine whether the tool will help progress your business goals or cause problems later on.

• Best customer insight platforms for customer research

Here’s a roundup of the customer insight tools we think are most effective for customer research. Bear in mind that the best tool for one business will be different than for another.

Google Trends

One of the most commonly used insight tools is Google Trends. This free tool helps users understand and analyze search terms over time, compare searchers, drill into regional data, and access real-time data to spot patterns.

Google Trends can also help researchers and marketers better understand what’s currently trending, what consumers are paying attention to, and what search terms are more important than others.

You can use information from Google Trends to boost website metadata, create compelling content that draws consumers in, and develop products that are highly relevant in today’s world.

Google Analytics

Another well-known Google tool is Google Analytics. It allows researchers to track and analyze user interactions on websites and apps. This can provide key insights into users’ behavior when interacting with your company’s online content.

Google Analytics covers a range of areas, including demographics, conversions, webpage visits, page drop-offs, sources of website traffic, and specific user data. The platform also provides real-time data and custom reports to help researchers understand what’s working and where improvements can be made.

Dovetail is our all-in-one platform that helps teams streamline their customer research and reach actionable insights faster.

The platform offers visually engaging dashboards and concise summaries that cater to the needs of various stakeholders to boost communication and collaboration across teams. These reports translate raw data into actionable insights .

Additionally, flexibility allows for customization, ensuring that the reports align with specific objectives for strategic planning and continuous improvement .

Exploding Topics

Exploding Topics was created to predict trends before they occur. With this tool, users can understand what’s growing in popularity and interest across the internet to jump on new and trending topics.

Within Exploding Topics’ searchable database, users can view categories and niches, identify trends, and gain data-driven insights.

The platform is popular with marketers, creators, and researchers who use the information gathered to create content that draws in internet users.

Hotjar provides a range of tools to better understand how users interact with websites and apps. The tool takes you beyond the numbers to offer heatmap technology that tracks users’ website activity to highlight areas of interest and friction. It also has recording capabilities.

Feedback allows businesses to hear thoughts from real-life users, while surveys bring the voice of the customer into the design and development process.

All of this information can be used to optimize the web and app experience for increased engagement and loyalty.

Companies can access real-time analytics with Mixpanel. This tool helps you measure and then optimize customer engagement across mobile and web.

Use Mixpanel to track and gain insights into customer behavior, including scrolling, button clicks, and page visits. You’ll be able to access live updates, create metrics by which to measure growth and retention, and slice and dice data to spot key patterns and trends. This increases the quality of data-led decisions across your product offering.

Zendesk offers businesses increased connectivity with their customers alongside customer research tools that unlock new insights. Built-in customer satisfaction surveys , for example, give you the chance to track how customer support teams are performing.

Zendesk also allows you to make the most of the customer data you collect through the customer service process to drive more accurate decision-making and positive change across the business.

Kissmetrics

Teams can improve their metrics with Kissmetrics, a tool that allows you to see, identify, and understand analytics to make essential changes. This can help drive better product and marketing decisions.

The platform simplifies tracking customer behavior through a business’s web offering, spotting where customers are dropping off, reducing customer churn, and boosting revenue through optimization.

Kissmetrics also makes it easy to test user flows to identify the sequences that work and those that don’t, ultimately offering the best possible user experience.

Typeform makes sending engaging quizzes and surveys to customers simple. The platform’s user-friendly survey design can help boost engagement and make providing feedback more interesting for customers.

Easy embedding allows teams to include surveys at opportune moments to obtain relevant reactions and feedback. This essential data can then be used to make critical changes across the business.

Typeform users appear to be highly satisfied with the product, with 96% of customers saying they had a better brand experience after making the switch.

Numerator offers first-party consumer-sourced data to help organizations better understand their customers. Teams also gain the ability to interact with customers to learn about their attitudes and opinions, improving decision-making.

Some Numerator use cases include analyzing shopper behavior in relation to demographics, utilizing data to show brand value for investors, and better understanding media consumption to develop more relevant products.

Flame Analytics

While most customer insight tools and platforms focus on optimizing customer experiences in the digital world, some also help enhance in-person experiences. Whether it’s a sports venue, a shopping mall, a promotional pop-up, or a physical store, analytics can prove very useful.

Flame Analytics unlocks traffic information about a user’s physical space and key data for boosted planning, optimization, and best practices. These advanced analytics then seamlessly integrate with other sources, allowing businesses to act on key insights.

Trymata’s research tools can help you and your team better understand customers through usability testing, enabling you to improve the website experience.

You can use the tool to conduct A/B testing, utilize data to drive design decisions, identify the best user experience flows, gain insights from real users, and conduct real-time tests to spot pivotal friction points.

Hootsuite Insights

Hootsuite is a social media management platform that helps businesses stay connected with their customers across all their social channels.

The platform will allow your business to research its social media audience and gain key insights. This involves gathering demographic data to understand who makes up your company’s audience, discovering which social media platforms your audience prefers, and using surveys to validate and better understand customers.

With Hootsuite, you can also analyze the content your competitors are creating to understand how your business is performing in relation to them and where improvements could be made.

SurveyMonkey

Surveys are a common way to gain key insights into customers’ thoughts, opinions, and sentiments toward a business. SurveyMonkey provides answers to more than 20 million questions every day, enabling organizations to gain a competitive advantage.

Through SurveyMonkey, teams can deploy online surveys and forms to gain key data about customers and then make relevant decisions to improve their experiences.

UserTesting

The UserTesting platform allows you to gain direct input from users early in the development process. You can then embed that feedback into product development.

Through UserTesting, teams can more easily identify areas of friction, potential roadblocks, and aspects of products that aren’t working well for users. This valuable feedback can help teams optimize products to be more meaningful and solve customer problems.

Customer success software platform Totango is designed to help businesses reduce customer churn, increase revenue, and boost team efficiency, ultimately helping them retain and grow a healthy customer base .

The platform offers tools and solutions to track customer engagement, monitor the adoption of products or services, and analyze customer data to drive retention and growth.

Totango allows businesses to integrate data from multiple sources to get a clearer view of customers, better determine risk, and make data-led decisions. Customer segmentation also helps teams deeply understand customer segments to deliver more relevant experiences.

• Customer insights for boosted customer engagement

With advanced tools and platforms designed to facilitate customer research and provide customer insights, understanding how your customers feel about your product or brand is easier than ever before.

The right tools can reveal what your customers like and dislike about your offering, how likely they are to stay loyal to your company, and whether or not they would recommend you to other people.

These insights can help your business develop the best possible products that fulfill your customers’ needs, eliminate friction points, boost your marketing and sales efforts, and improve user and customer experience .

What are the six techniques to gain customer insights?

Many tools and techniques can be used to gain customer insights. Here are six of the most common techniques:

Customer surveys

Focus groups

Website analytics

What is a consumer insight example?

A consumer insight (or customer insight) occurs when an observation based on customer data turns into a conclusion about that information.

Here’s an example: by gathering data, an organization discovers that a product is performing best with a younger demographic. The reason for this, as they deduce by analyzing the data, is the product’s environmental friendliness.

This knowledge encourages the team to develop more environmentally friendly products and processes and communicate about them. This will get better results from the younger demographic, increasing overall business performance as a result.

Should you be using a customer insights hub?

Do you want to discover previous customer research faster?

Do you share your customer research findings with others?

Do you analyze customer research data?

Start for free today, add your research, and get to key insights faster

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