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SEED Guide

5.7. Netflix

Netflix leveraged design thinking to revolutionize the entertainment industry. By understanding user preferences and viewing habits, Netflix developed personalized recommendation algorithms that keep users engaged and coming back for more. Keep in mind that Netflix's human-centered UX design goes further than digital design itself since it covers the user experience from start to finish.

Empathizing: Starting in 1997, Netflix founder Reed Hastings spent $10 million a year on streaming technology research to better understand the market, the trends, and users. To understand their users' preferences, behaviors, and pain points related to discovering and enjoying content, they analyzed user data, conducted user interviews, and observed how users interacted with the platform to gain insights into their needs and desires, especially the challenges related to content overload and user dissatisfaction with browsing experiences. Rather than appealing to the masses, knowing their users also helped the company understand the value of catering to niches, provoking their target audiences with in-house productions like Black Mirror (starting in 2011) and Stranger Things (from 2016).

Re-defining to understand: After gathering insights from the empathizing phase, Netflix would redefine the problem they are trying to solve. This could involve identifying challenges such as the overwhelming amount of content available, difficulty in finding relevant recommendations, or user dissatisfaction with the browsing experience.

Ideating: In the ideation phase, Netflix brainstorms potential solutions to address the redefined problem. This can involve exploring innovative approaches to content discovery, such as personalized recommendation algorithms, user-driven curation features, or interactive content exploration tools.

Prototyping: Netflix creates prototypes to visualize and test potential solutions developed during the ideation phase. This includes building prototype recommendation algorithms and interfaces to simulate how personalized recommendations would appear to users. Prototyping has allowed Netflix to experiment with different approaches and iterate based on feedback. For example, to understand feasibility, and following up on the results of a series of Streaming Tests, this feature was included in the DVD subscription, permitting users to become accustomed to streaming itself and gathering recommendations for further change.

Evaluating: In the evaluation phase, Netflix gathers feedback on the prototypes from users and stakeholders to validate the effectiveness of the personalized recommendation algorithms in delivering relevant content recommendations. Conducting A/B testing, user surveys, and data analysis, the teams can assess the impact of the prototypes on user engagement and satisfaction. By 2010, after more than a decade of experimentation and in keeping with their four pillars: think big — start small — fail quickly — scale fast, Netflix was prepared to destroy their DVD delivery service and their early attempts at streaming

Implementing: Finally, Netflix moves forward with implementing the personalized recommendation algorithms based on the feedback received during the evaluation phase. This involves integrating the algorithms into the Netflix platform, optimizing them for scalability and performance, and rolling out the feature to users. Implementation also includes ongoing monitoring and refinement based on user feedback and usage data.

This process demonstrates how Netflix has leveraged design thinking principles to develop personalized recommendation algorithms that enhance the user experience and drive engagement on the platform. The Forbes’ review of Netflix’s innovation process by Chunka Mui, a futurist and innovation advisor who also publishes in the Harvard Business Review, the MIT Technology Review, and the Future Perfect Newsletter via LinkedIn, can serve as a portal to finding other writing by this author and his co-authors Peter B. Carroll and Tim Andrews.

Further reading:

Discussion questions related to Netflix

  1. How did Netflix use design thinking to figure out what shows and movies their viewers would like?
  2. How did Netflix initially empathize with their users to gain insights into their preferences, behaviors, and challenges related to content discovery?
  3. What were some of the challenges Netflix faced when trying to recommend shows to their viewers?
  4. What role did prototyping play in their experimentation process?
  5. Consider the impact of user interfaces that do not fully contemplate the user experience. In what areas of activity in your life do you use satisfying interfaces? What makes each case a good experience?
  6. What evidence can you find that Netflix applied their four pillars − think big, start small, fail quickly, scale fast − during their experimentation with streaming and the implementation of personalized recommendation algorithms?
  7. How did Netflix implement the personalized recommendation algorithms developed during the design thinking process, and how did they continuously refine these algorithms based on user feedback and usage data?
  8. How did Netflix leverage design thinking principles to develop personalized recommendation algorithms?
  9. What is your impression of the enhanced user experience? Do the algos drive engagement on the platform?
  10. How do other competitors in the entertainment industry promote sustainability and where do you think Netflix ranks in comparison?