Over-the-top (OTT) streaming services have become an increasingly popular medium for viewers to stream their favorite movies, sports, TV shows, and other entertainment content.
Statista estimates that VOD services will likely touch 1.636 billion users by 2027. With this bullish sentiment, it’s natural that the number of streaming platforms is growing.
While this means more options for viewers, the rising competition poses numerous challenges to broadcasters. It makes tackling ott churn or paying customers canceling subscriptions significantly trickier than before. After all, it negatively impacts market share, revenue, and growth.
So what's the solution?
The answer lies in first understanding your customer base and why they leave. This is a crucial first step because you can’t improve what you don’t know.
Once you have relevant insights, you can then take proactive steps to prevent churn from happening and maximize customer lifetime. But when you have so many subscribers, where do you even begin?
Enter: Application of machine learning to tackle OTT churn
Data science and machine learning present a robust and objective way for OTT businesses to go into the root causes of churn.
By simplifying the analysis of vast amounts of subscriber data, modern machine learning tools empower broadcasters to identify:
- Exact customers' patterns
- Customers preferences
- Behaviors at risk of churn
The combination of these insights puts you in an advantageous position to take meaningful steps for churn reduction.
With that, let’s explore actionable ways to leverage data intelligence to overcome OTT subscription churn. But first, let's quickly go over the basics.
Understanding OTT churn
OTT churn, or customer churn or subscriber churn, is among the core key performance indicators for OTT subscription services businesses to assess their health. This metric measures the rate at which ott service subscribers leave a service. This may include leaving out of a voluntary choice or even involuntary churn due to external circumstances.
Research estimates that OTT subscription churn currently averages around 10.81%. Out of this, 1.84% is involuntary, whereas 8.97% is voluntary.
Why does it matter?
Tackling churn is super important because it directly leads to revenue loss from churned customers. It additionally counteracts the effort and expense required to acquire new customers, ensure a smooth training and onboarding process, alongside provisioning, and supporting them. Both hit profitability.
- Customer acquisition is 5 to 25 times costlier than retaining existing ones.
- Loyal customers spend 67% more on a company's products and services.
- A mere 5% increase in customer retention can increase profits by at least 25%.
Therefore, controlling churn is critical to driving growth for ott platforms.
How to calculate churn?
You can calculate OTT churn as the percentage of streaming customers who cancel their subscriptions or stop using the streaming service during a given period.
Formula to calculate churn rate
Why do users churn from OTT services?
There can be several reasons for streaming service subscribers to churn. Involuntary churn usually happens due to declined payments from expired credit cards or other payment failures. On the other hand, some of the most common reasons for voluntary churn include:
- Content-related concern: If the platform content isn't interesting enough for the users, or they've burnt out consuming whatever they like, the likelihood of churning increases.
- Pricing: Pricing is a significant factor that influences user churn. With rising inflation, people are becoming increasingly conscious of their expenses. If they feel the subscription fee is too high or they're not getting enough value, they are quick to pass.
- User experience: A poor user experience, such as a messy interface, slow loading times, or even poor customer service, annoys users and motivates them to turn to other platforms instead.
- Subscription fatigue: Alongside specific reasons to churn, there's an overall force of subscription fatigue operating across the economy. In general, customers are feeling tired of paying for multiple subscriptions. This is feeding into churn rates for all subscriptions, including streaming services.
So how to reduce customer churn? Let’s look at how to tackle it in an intelligent way.
Five ways to reduce churn rates using AI-powered churn prediction
First and foremost - when you start with churn management, you must realize that it seldom occurs without warning.
Voluntary churn is always preceded by signs like a fall in customer engagement or a rise in inactivity. You may also find sudden overconsumption of your content, usually followed by unsubscribes (commonly called "burn before churn.”)
Machine learning and artificial intelligence are helpful here. It helps to identify these patterns from data and act on them timely. If you use the right data analytics tools or churn prevention software, you can identify the warning signs highlighting at-risk customer segments. With this foresight, you can quickly re-engage the customer with specific churn management strategies before they churn.
For instance, if you find your customers turning price sensitive, you can offer coupon discounts to entice them to say. For those who seem upset with the service and are providing negative customer feedback, you can work on improving that aspect.
Read More: How to use the customer support analytics to retain more subscribers
Churn prevention tools like ChurnIQ provide dashboards with metrics highlighting your churn rates and the associated subscriber cancellation reasons.
An example of ChurnIQ’s retain dashboard
It presents a clear picture of what’s happening at your baseline level. You also get a synopsis of upcoming renewals and an analysis of renewal performance.
The analytics tool uses a machine learning algorithm to track accurate churn probability scores with a breakdown of the number of at-risk subscribers and their reasons for leaving your platform.
Here are five ways you can use ChurnIQ’s data intelligence capabilities to address churn:
1. Find out how urgent your churn problem is
Image: Example of the "Subscription churn risk" graph from the Churn prediction dashboard
The foremost step to counter churn rates is knowing your exact risk status. The Subscription Churn Risk dashboard uses the graph above to illustrate the immediacy of your churn problem among the existing subscriber base. This information makes it an excellent starting point to assess how severe your churn risk is.
For example, the graph above shows that 85% of the at-risk subscribers display “Very High” risk patterns. From this, you can deduce how quickly you need to start addressing your at-risk subscribers and with what intensity. Intuitively, high risk demands immediate action with greater force. On the other hand, lesser-risk situations can afford lesser resources to be allocated immediately.
2. Find out why customers are churning
Once you know the "what," the next important thing is the "why ." After all, can you come up with a solution without knowing why?
Image: Example of the "Detected Churn Causes" graph from the Churn prediction dashboard
ChurnIQ’s algorithm analyzes the subscriber data and detects churn causes, ranging from past behavioral patterns to current ones. It also notices streaming and pricing plan issues, causing dissatisfaction and churn. This understanding puts you in a position to intervene and address the exact cause.
Campaign Example A:
In the graph above, we see that the primary churn causes for this broadcaster are
- Not engaged with the content
- Payment is unreliable.
This is a precious insight as it can point you to do the following:
- Better promotion of popular content OR invest in new, more popular content
- Launch an email campaign to remind customers of outdated payment details
3. Know which customers to prioritize
Once you know the severity of your churn problem and the primary causes of this, it's time to get specific.
It's nice to know the general churn status of your full customer base, but it's not that useful unless you can precisely locate the at-risk customers. An excellent way to do that is by creating segments based on risk levels and risk causes. You can use ChurnIQ to segment out Very High/High Risk of Churning this month. Then, coupling this with the detected churn cause, you can narrow down your audience and develop a campaign to compel that particular segment to stay.
Campaign Example B: Suppose you notice that high-risk subscribers are often linked to price complaints. Whereas low-risk subscribers are often linked to a poor customer experience. This should make it clear that prioritizing the price-sensitive group is a priority. Next, you can develop appropriate pricing strategies and re-engagement campaigns like a coupon campaign that offers attractive discounts.
In the image below, you can see several examples of crucial segments recommended by the ChurnIQ dashboard.
Image: An example of key segments to target, presented within the ChurnIQ dashboard
Using data from over a decade in the video subscription industry, we built a selection of subscriber segment suggestions, all available in the Cleeng Dashboard. This guides you toward the most logical ways to segment your customer base to address the different churn problems best.
Read More: 5 customer segments that will grow your OTT revenue
4. Follow best practices for effectively targeting at-risk customers
Once you've located your at-risk customers, the next step is creating a plan to re-engage them and secure them as loyal subscribers. This is an essential step, because a perfectly shaped message will be the difference between a retained and lost subscriber.
To simplify this, we used historical subscriber data paired with industry best practices to create a catalog of recommended retention actions. These actions are broken down per stage of the subscriber journey (Register vs. Experience vs. Winback etc.). And within each stage, the goal outcomes and recommended segments and actions are defined.
Image: The eight stages of the subscriber journey
For example, see below the recommendations for the Retain stage:
Image: The Retain stage of the Segments Catalogue (full catalog available within the ChurnIQ dashboard).
Campaign Example C: If your Prediction dashboard shows "High Risk" associated with "Poor experience," the Segments catalog recommends an apology with a discount to show the customer that the error has been addressed and that their loyalty is valued.
Campaign Example D: If your Prediction dashboard shows "High Risk" associated with "Frequent churner," you may find the customer burning through your content quickly and then canceling. In this instance, we recommend focusing on any upcoming content. Clearly, the content attracted the customer in the first place, so remind them that there is more to come.
No matter what your churn concerns are or what stage your customer is at, you can access a selection of recommended actions to give you the best chance of retaining them. Read More: How to fight churn with subscriber segments
Finally, you also need to implement plans, considering the time element.
5. Set up automated retention campaigns easily
If your execution of retention campaigns takes too long, you can lose customers from your net.
For example, consider a user who signed up for a hockey season pass with an end date in 2 weeks. If you wait for the season to be over before you convince them to spend longer on your platform, you could lose them for good once the season ends.
Therefore, acting quickly is essential. To that end, ChurnIQ Segments offers easy, automated campaign creation. No more hours of tiresome planning and list management. Through our integration with Looker, you have near-total freedom to connect to any marketing tool. Simply set up a segment once, set the campaign frequency, and have it run automatically in the background.
Bottom Line: Be proactive, not reactive
As the OTT landscape competition is at an all-time high, you must pull up your churn management performance to stay in the game and grow steadily. To that end, the best way to go is by being objective about the approach.
Machine learning presents a powerful data-backed way to identify at-risk subscribers, understand their behavior patterns, and take proactive measures to reduce churn.
So, if you’re looking to be better positioned for success in the long run, rely on ChurnIQ (known to predict churn with up to 92% accuracy)