Netflix and Chill

The Netflix marketing team observed that there are many people ordering food when they are watching movies on Netflix. What is the Product Manager next take on this?

Recently I came across this question in the Product Management exercise page and it really fascinated me. As soon as I read the first line, it was like “Yeah, that’s what we do on a Saturday night — Netflix and chill (for me it’s Rom-com and milkshakes). But not just while watching shows in Netflix / other OTT platforms/ TV, even in movie theaters the films are never complete without buttery popcorn.

But if I consider myself as a Product Manager of Netflix, I would think about using this as an opportunity in improving the user experience of my customers. Before we actually solve the problem lets get to know some details about Netflix,

Netflix is the world leading OTT platform with about 183 million paid subscribers in over 190 countries. The users can watch TV series, feature films and documentaries, original contents across a wide variety of genres and languages. They can watch as many shows at any anytime, anywhere, on any internet-connected screen. The Members are free from commercials while watching the shows, which differentiates it from other OTT platforms.

Netflix allows customer to create multiple profiles and also allow multiple users to watch at the same time based on their subscription plan. They also allow parental control and allow us to select a maturity level that acts as a filter to the shows. A unique feature of Netflix is the “binary rating system”. You can rate either thumbs up or thumbs down (93% match) and your suggestions are based on these ratings.

Another major advantage of Netflix is its Data Analysis and Machine learning algorithm. They continuously design and deploy A/B testing to improve their user engagement. The company says

An algorithm/ feature/ Design “X” will increase user engagement and ultimately user retention.

Netflix terms this as “Customer Science”, where the UX of each individual user including the rows displayed in the home page, Titles / genres for each row, Thumbnail visuals for each movie and recommendations are personalized. This is made possible by tracking the view habits of the subscribed members and categorizing them into “Taste Communities.”

They test new ideas with real customers at scale and measure for statistically significant differences in how they engage.

Netflix also collects real time data logs from playback devices to measure how seamlessly the user devices are handling browsing and playback using Druid. They are currently ingesting at over 2 million events per second, and querying over 1.5 trillion rows to get detailed insights into how our users are experiencing the service.

Crack the opportunity:

The statement here is “Netflix members order food online while watching their favorite show.”

Though this statement may seem real from our personal experiences but it is necessary to gather enough data to prove that the above statement is true. The data can be collected through

1. Success rate of “Netflix x Swiggy : Valentine’s day survival kit”: For the valentine’s day 2020, Netflix and online food delivery platform swiggy launched the valentine’s day survival campaign in which promotional emails with show recommendation for singles and prompting single meal orders from swiggy pop.This campaign reshapes the way Indians spend their time i.e by ordering food online and watching content.

The success metrics of this campaign can be measure by

• Click to open rate of the promotional email
• Click through rate
• Compare the average screen time of a particular region on valentines day with that of the previous days average.
• Compare the number of online orders in that particular region on valentines day with that of the previous days.

These metrics would help us understand the effect of online orders on OTT platforms and the vice versa.

1. Analyze active session vs online order under different conditions:

We need to analyze the relation between the number of online orders and active sessions in the particular time at the particular region such as,

Number of online orders vs number of active sessions in Chennai,

• On a Monday morning.(Probably a very less active users)
• On midweek afternoon
• Weekdays evenings between 6–9 pm
• Weekends

A recent study shows that food ordering spikes between 10 pm and 1 am on weekends and on an average every Indian spends about 70 minutes on OTT platforms.

With these data, we can identify whether customers order food while watching Netflix. In case, if the state is false, this data can add more value to the Customer science and if it is “True” this will be an opportunity to improve customer experiences.

In the current pandemic situation with malls and theaters closed, movies have been released in various OTT platforms but still people miss the experience of a theater.

Netflix Party:

Netflix recently launched this Netflix extension which helps us synchronize video with our friends and watch the show together online. It also has a group chat feature.

To further improve this feature,

• When any movie / new season of a show is premiered, the users can schedule to watch the movie on a particular date and time along with pre-ordering of snacks and beverages (like booking a movie ticket). This can give the experience of an actual movie night.
• The food ordering can be either inbuilt in the app itself or redirected to the food delivery platform. In case, if this feature is inbuilt, there need to be an option for online payment.

Stream and Order:

• This feature can help us order online at the beginning / while streaming the show. This may interrupt the show but still add value to the user.
• The user can be encouraged to order on a particular platform to avail the discounts and offers.
• A competitive OTT platform Hotstar in partnership with swiggy launched an offer to order food from the hotstar app itself during the T20 series.

In such a way, this would be an opportunity to explore new ideas and improve the way of movie streaming. This would require a lot of research and strategies before introducing.