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This is an exploratory data analysis project where I worked on a Netflix dataset sourced from Kaggle (check readme file for link). I have used python libraries for data cleaning and analysis to derive actionable insights.

HarshaRishi/Netflix-Case-Study

Folders and files, repository files navigation, netflix-case-study.

About NETFLIX

Netflix is one of the most popular media and video streaming platforms. They have over 10000 movies and TV shows available on their platform, as of mid-2021, they have over 222M subscribers globally. This tabular dataset consists of listings of all the movies and tv shows available on Netflix, along with details such as - cast, directors, ratings, release year, duration, etc.

Business Problem

Analyse the data and generate insights that could help Netflix in deciding which type of shows/movies to produce and how they can grow the business in different countries.

Link to the dataset: https://www.kaggle.com/datasets/shivamb/netflix-shows

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How Data Analytics can be a Game Changer: A Netflix Case Study

As per McKinsey, machine learning that incorporates a wide plethora of algorithms in the past few years is evolving faster due to the advent of analytics. With businesses investing heavily in cloud and the rapid digitization of the professional ecosystem, analytics is all set to become a significant aspect in deciding the fate of organizations.

Data Analytics – How Can It Transform Your Business?

As per a study by SAS , more than 70% of organizations believe that data analytics plays a vital role in getting precise insights. The study also said that out of ten organizations, six of them said that leveraging analytics makes them more innovative. Analytics is slowly but steadily evolving in the competitive landscape. Industry leaders are using analytics to make decisions that can help them to stay ahead of their peers, besides exploring better revenue opportunities, new markets, and building a better relationship with their customers.

The very reason why business models of Uber, Airbnb, and Spotify are sustaining is data and analytics. When you digitize your interactions with customers, you create a window to get immense information. This customer information could be utilized for making effective marketing strategies, better products, and making more sales.

A lot of C-suite leaders now understand the importance of data and understand the risk it carries if not secured correctly. What is startling is and makes investment in data and analytics even more important is the kind of ROI it gives. In the Journal of Applied Marketing Analytics, Jacques Bughin says, the ROI on data and analytics is better than the investments done in computers during the 1980s.

The power of data and analytics is also harnessed to improvise core operations or create new business models from scratch. The most exceptional example is Netflix. Netflix has efficiently used its customer data to refine its recommendation engine and give a better experience to the users. Not only that Netflix has surpassed Disney as the most valued media company in the world with a valuation of more than $160 billion. One of the biggest reasons for their success is their impeccable customer retention rate. Their customer retention rate is more than a staggering 90% which is far better than Hulu’s 64% and Amazon Prime’s 75%.

The second most important reason why Netflix is way ahead of its competitors is- Content Creation . The kind of quality shows and movies it makes like “Orange is The New Black”, “Sacred Games”, and “BirdBox”. These shows have received a thunderous response across the globe resulting in a steady rise in subscription rates. One of the primary reasons why they succeed in making better content is that they understand what their audience wants to see leveraging data and analytics.

So, How Does Netflix Leverage Big Data and Analytics?

Netflix has digitized its interactions with its 151 million subscribers . It collects data from each of its users and with the help of data analytics understands the behavior of subscribers and their watching patterns. It then leverages that information to recommend movies and TV shows customized as per the subscriber’s choice and preferences.

As per Netflix, around 80% of the viewer’s activity is triggered by personalized algorithmic recommendations. Where Netflix gains an edge over its peers is that by collecting different data points, it creates detailed profiles of its subscribers which helps them engage with them better.

Netflix collects information on how a user interacted and responded to a TV show or a movie. If we go into details, it collects the following data: –

• Time and date when a user watched a show
• The device used to watch the show
• If the user pauses the show, do they resume watching
• Does the user binge-watch an entire season of a TV show?
• If they do, how much time does it take to binge watch it?

More than that, Netflix has ratings that the viewer gives to the content they watch, the number of searches they do, and what they search. The information collected is enough for creating a detailed profile of a user, and this is exactly what Netflix does. It leverages data analytics to make a robust recommendation algorithm that suggests the best content to the subscriber as per their needs and preferences. The user no more must endlessly search through streams of content to find out what he or she wants to watch. Netflix makes the job easier for them in the process, giving them a better and customized viewer experience.

The recommendation system of Netflix contributes to more than 80% of the content streamed by its subscribers which has helped Netflix earn a whopping one billion via customer retention . Due to this reason, Netflix doesn’t have to invest too much on advertising and marketing their shows. They precisely know an estimate of the people who would be interested in watching a show.

Apart from monitoring the online behavior of their users, Netflix has a feedback system in place. They encourage feedback from their audience, which further helps them understand their preferences and helps them in suggesting better shows and creating better content.

Why Investing in Data Analytics is Important?

There is a data explosion today, and the need for analytics has been growing exponentially. Tools and software are being developed to get precise insights from data.

If you want to know your customers better, find revenue opportunities, and tap into new markets. You need to have a mechanism that helps you gain better insights. As an organization, investing in data analytics will give you four significant benefits.

1. A Deeper Understanding of Customers

Earlier companies would generally categorize customers based on age, gender, and location. Now with the help of AI, one can map the digital footprints of their customers. Decision-makers can go through crucial behavior patterns of customers like price sensitivity, brand affinity, affluence, and preferences. These kinds of data mapping help in understanding your customers better enhancing your ability to build better products and services for them.

2. Early Detection of Problems in Products And Services

More than half of the professionals across North America and Europe are heavily dependent on analytics to enhance the quality of their products and services as per research from Forbes Insights and Cisco. Analytics can give you precise insights on the kind of concerns customers have, their changing needs, and based on that, you can innovate your offerings.

3. Identifying Better Marketing Strategies

With various digitization channels for customer interaction available now, businesses are adopting an omnichannel approach to engage with customers. Using analytics, marketers can get inputs on how to have meaningful engagements with customers across all channels. Also, analytics can help analyze successful marketing programs and identify strategies that yield better ROIs.

4. Finding Ways To Reduce Expenses

Once you start getting insights at departmental levels, it will help you identify areas where you can curb your costs. Insurance companies saved a good amount of money by identifying patterns of fraud and dismissing false claims.

How To Harness The Power of Data?

As an organization, do not be afraid of change. If you are yet to use analytics as an organization, start with small steps, fail faster, and make a steady transition. Do not go for overnight results instead practice consistency and prioritize your efforts.

The first step you need to do as a decision-maker is incorporating data and analytics into the core vision of the organization, focus on nurturing a data-driven culture. Slowly but steadily create a powerful data infrastructure and hire talent to operate it, make sure to highlight your data-driven culture in your employer branding campaigns.

Your success doesn’t lie in adopting the most powerful technology rather digitization of your organization from the bottom. Companies like Netflix, Amazon, and Google, who are leading the analytics game, gradually transitioned to a data-savvy culture. It wasn’t all overnight but a gradual process that took a few years. Not only did they heavily invest in analytics but they have also kept themselves observant of the changing trends of artificial intelligence. They are putting the case strongly before all other organizations- if you want to survive in the market, you need to invest in data analytics, and that is not negotiable at all. Contact Us for more details.

References-

1. https://seleritysas.com/blog/2019/04/05/how-netflix-used-big-data-and-analytics-to-generate-billions 2. https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/how-companies-are-using-big-data-and-analytics

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Please note you do not have access to teaching notes, netflix leading with data: the emergence of data-driven video.

Publication date: 20 January 2017

Teaching notes

By 2009 Netflix had all but trounced its traditional bricks-and-mortar competitors in the video rental industry. Since its founding in the late 1990s, the company had changed the face of the industry and threatened the existence of such entrenched giants as Blockbuster, in large part because of its easy-to-understand subscription model, policy of no late fees, and use of analytics to leverage customer data to provide a superior customer experience and grow its e-commerce media platform. Netflix's investment in data collection, IT systems, and advanced analytics such as proprietary data mining techniques and algorithms for customer and product matching played a crucial role in both its strategy and success. However, the explosive growth of the digital media market presents a serious challenge for Netflix's business going forward. How will its analytics, customer data, and customer interaction models play a role in the future of the digital media space? Will it be able to stand up to competition from more seasoned players in the digital market, such as Amazon and Apple? What position must Netflix take in order to successfully compete in this digital arena?

To examine the benefits and risks of investment in analytical technology as a means for mining customer data for business insights. Students will develop a strategy position for Netflix's investment in technology and its digital media business. Students must also consider how new corporate partnerships and changes to the customer channel model will allow the company to prosper in the highly competitive digital space.

• Blockbuster
• Data Mining
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• Reed Hastings

Walker, R. , Jeffery, M. , So, L. , Sriram, S. , Nathanson, J. , Ferreira, J. and Feldmeier, J. (2017), "Netflix Leading with Data: The Emergence of Data-Driven Video", . https://doi.org/10.1108/case.kellogg.2016.000232

Kellogg School of Management

Copyright © 2010, The Kellogg School of Management at Northwestern University

You do not currently have access to these teaching notes. Teaching notes are available for teaching faculty at subscribing institutions. Teaching notes accompany case studies with suggested learning objectives, classroom methods and potential assignment questions. They support dynamic classroom discussion to help develop student's analytical skills.

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