Algorithms and storytelling

Last evening I spent some time interacting with filmmakers, storytellers and other such exotic people whom I admire because they can do things that I can barely imagine. One of the moderators asked about the importance of analytics and data on deciding what to make for an OTT platform. My answer was too brief to make everyone understand and hence am attempting a respone to everyone who nodded their heads by using this extract from an article that I read almost 2 years ago. I am writing this as an article because of the word count limit on the usual Linkedin posts.

         { To the uninitiated, it may seem that Netflix’s analytics go only as far as views. They may also think that the show House of Cards was chosen because Netflix “thought subscribers might like it.” But the truth is much, much deeper. The $100 million show wasn’t green-lighted solely because it seemed like a good plot. The decision was based on a number of factors and seemingly almost entirely on data.

Traditional television networks don’t have these kinds of privileges in their broadcasting. Ratings are just approximations, green-lighting a pilot is based on tradition and intuition. Netflix has the advantage because being an internet company allows Netflix to know their customers well, not just have a “persona” or “idea” of what their average customer is like. Let’s look at an example.

If you’re watching a series like Arrested Development, Netflix is able to see (on a large scale) the “completion rate” (for lack of a better term) of users. For example, the people at Netflix could ask themselves “How many users who started Arrested Development (from season 1) finished it to the end of season 3?” Then they get an answer. Let’s say it’s 70%.

Then they ask “Where was the common cut off point for users? What did the other 30% of users do? How big of a ‘time gap’ was there between when consumers watched one episode and when they watched the next? We need to get a good idea of the overall engagement of this show.”

They then gather this data and see user trends to understand engagement at a deep level. If Netflix saw that 70% of users watched all seasons available of a cancelled show, that may provoke some interest in restarting Arrested Development. They know there’s a good chance users will watch the new season. }

Before we jump off and run into the horizon shouting Eureka, we have to temper this data-based decision making with a few things that are unique to the India market.

1.  Which platform are you pitching your show for? Ad-funded platforms have requirements that are different from subscription only platforms.

2.  What medium will your audience use to watch the show? Mobile phone or connected devices? The two have different needs. Mobile phone audiences snack – they have a limitation of memory if they download and watch. They will not watch shows that have explicit language and content on a large screen. Most OTT content is for personal viewing. Try not to confuse the audience.

3.  Jio Effect – the 2 GB pack is used for everything every day. Tiktok to downloading porn to watching your show. At an average where a decent quality video file is being consumed the duration won't be more than 60 minutes. So as a writer, director, storyteller how will you bring the audience back to complete the show at the end of that 60 minutes spread over 6 / 7 sessions?

4.  How does your concept, story, idea make money for the platform? If your platform of choice is ad-funded then don’t crib about budgets.

5. You are not competing with only sleep in India.

6. Collectively the OTTs in India have not touched more than 25% of the connected audience, paying audience is far smaller currently, the playbook has not yet been written and anyone telling you otherwise is smoking good quality grass.

Lastly – I asked the audience if they have seemed the island in bookstores where the best sellers like Chetan Bhagat are showcased. Algorithms use data in the same way – they show what’s selling and not what is the best show. If you need to find gems then you need to browse the book store, the good ones are always at the back. Algorithms and data will tell you what's been watched, by whom, where, how, when and so on - it cannot replace at any time human intuition/gut feel/experience.

And lastly - never try to tie data up to a chair and extract a confession from it. You will always hear what you want to hear and not an unbiased version.

Additional must read: https://www.salon.com/control/2013/02/01/how_netflix_is_turning_viewers_into_puppets/

https://www.inlander.com/spokane/why-algorithms-like-spotifys-discover-weekly-playlist-are-actually-bad/Content?oid=11068414