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This is how industry leaders are minimizing user churn


The benefits of focusing on customer retention aren’t solely to do with cost. As a returning customer, they are in many ways an ambassador for your product – able to talk about it, promote it and share it with others. The longer a customer stays with you, the more loyal they become to your brand.

Big players in the video industry know this and understand the importance of customer loyalty in terms of both ROI and reputation. Famously, Netflix has said they spend an average of $100 to acquire one customer who could leave after a one-month free trial or before spending more than that much on membership fees. However, statistics show it is indeed four times cheaper to retain a customer than acquire one.

It is important to not let churning customers stay in the back of your mind. Come up with ways of rewarding them. Whether it be price-drops, first access to new features or event invitations. These things will give them further incentive to start shouting about your product!

For example, if you’re running a cake shop, your way of investing in returning customers is going to be making sure you sell the best cakes around. But once that’s over, you’ll be pushing people to bring their friends, follow you on social media, and maybe even subscribe to your newsletter.

But if you’re running a Saas business, this becomes a whole new beast. Customer retention requires investment and precise marketing methods. Newsletters and automated subscription emails work well, but the best way to analyse this is by using software that tracks customer behaviour and gives visibility of likely churning users so you can focus on these consumers, or even reward those whose usage is high.

How do you classify churn?

Before digging deep into your data and offering discounts or exclusive offers, it’s important to understand how to predict churn. Calculating your total MAU, WAU and DAU and thinking about your KPIs regarding usage gives you the tools to start fighting against churn.

Regardless of your business model, identifying inactive users is vital for AVODs, SVODs, PVODs or hybrid models to maintain a loyal audience and create a steady flow of income. Shanti Bergel, in Designing For Monetization: How To Apply THE Key Metric In Social Gaming, argues that DAU “has emerged as the key metric determining the popularity and potential of a social game.” This is the benchmark almost any video service should strive towards. With more daily active users comes more assured income.

Understanding these metrics and implementing a defensive strategy to counteract user churn is always going to supported with the use of an analytics tool like YOUBORA which is capable of giving full visibility of your audience’s user behaviour to understand consumption patterns and apply this data to predict which users will leave so you have time to try and rectify the situation.

What is audience distribution?

Let’s say you know you have 500,000 users. Accumulatively, you know you’re getting an average of 8,000 hours of view time per day, but you don’t know how this is distributed. Knowing that your platform is being viewed let’s you know which content performs well and what trends users follow, but what if a large chunk of your audience is inactive and you’re relying on a small percentage of your users for most of your impressions? It could be that you have 20,000 avid users of your platform, with 480,000 casual or completely inactive consumers. This puts your platform at risk, as once you start losing these users to a competitor, your income is going take a hit.

audience Distirbution at NPAW with YOUBORA


How can user segmentation help?

As we’ve discussed before, understanding your users is incredibly important when it comes to growing your audience. While we have in the past discussed using recommendation and personalization platforms to create tailor-made experiences, user segmentation broken down by usage frequency opens up a whole new realm of marketing and strategy to support user retention.

Still classified as behavioural segmentation, creating samples of users who are likely to churn allows you to zero in on this problem, figure out a strategy to minimize this and, over time, move towards a much more evenly distributed average view time per user and reduce churn.

To support video services looking to tackle user churn with a powerful strategy, NPAW has come up with USERS, our platform that offers in-depth analysis of user behavior, churn prediction and highly precise segmentation.  You can learn more about it here.




Research & Editorial Team on September 26th 2018

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