V1 should be good enough to address most use cases so that people could onboard in the system and help improve it by providing feedback. I wanted to make sure that the use cases I was targeting in the V0 or V1 release, included use cases coming from a variety of teams and users from whom I could get feedback. Next, I had to find a balance between the most important use cases. That helped me plan my milestones so that I delivered the most important features first. If a particular access pattern was important to them, was it more important than the other one? I wanted to understand and establish a clear order of priorities early on.
I would ask them very specific questions such as, How will you query the data or How will your systems integrate with the new system? I also wanted to learn about their priorities. I would also meet with other teams to get precise requirements for the projects. To do so, I talked to a number of consumers, meeting with them one-on-one. Actions takenįor starters, I had to understand what were the most common use cases.
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The challenge I found particularly difficult was how to manage expectations given the excitement surrounding the project from the start and furthermore, deliver the features timely without compromising on quality. Apparently, that was critically important to different business units, and no wonder that a number of teams, including the search, recommendation, page construction, and ranking team, were interested. We could go back for a month or two to learn from their activities, personalizing the system accordingly. If we could further ramp up our recommendation and personalization system, it would make an even more satisfying user experience.įrom a data perspective, we were collecting the data that would help us understand what users were doing in real-time and capture their interactions over a longer period of time. All those activities were important because they could tell us what a user’s intent was.
When not playing video content, our users would navigate the home page, engage with a few rows, play trailers, look for specific titles, using thumbs up/down to rate content, etc. We tried to improve the Netflix recommendation system and make it more real-time and take into account the browsing habits of our users. The craze kicked off even before we began articulating the idea and coming up with the design. The problem we were trying to solve was exceedingly important to the business, and many teams were interested in using our project. I started a brand new project, which was much in demand even before its official start.
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