How OTT Platforms Can Use Behavioral Analysis To Boost User Experience

“Keep ’em hooked!”

That’s probably the mission statement of every single streaming platform we have today. 

Whether it is Netflix, Amazon Prime, Disney+, Hulu, Peacock, or any other OTT player, each of them is involved in a never-ending race to attract more viewers and retain existing subscribers. 

However, what started as a unique form of content consumption has now turned into a highly competitive market as these platforms struggle to keep their viewers hooked while also dealing with problems like user churn, lack of customer engagement, and loss of revenue. 

While there might be different reasons for each of these problems, a large part of it can be attributed to the quality of experience that users are offered on these platforms.

Improving the user experience at every stage of interaction is the best way to counter these challenges and stay ahead of the competition.

But, how do you go about it? 

Understanding the importance of behavioral analysis

Be it award-winning documentaries, viral TV shows, or the latest star-studded action flick, viewers are bombarded with every possible content right from the moment they arrive on a platform.

On the other hand, Netflix, which is currently the largest streaming platform, lost close to one million subscribers in a single quarter of 2022.   

This shows how platforms are struggling to retain subscribers, which makes it all the more important for them to continuously improve user experiences.

Understanding how these users interact with your platform, observing the kind of actions they take, and identifying friction points in their journey are key to building an optimized experience.

This is what behavioral analysis is all about. 

For example, let’s consider that an OTT platform displays a section called ‘Watch More Like This’ whenever a user has finished watching any content. However, data from their analytics tool shows that the section is not receiving enough clicks.

This is quite concerning as it indicates that users are probably not interested in the recommendations being shown and as a result, they are just leaving the website immediately after finishing an episode or movie. 

While this may not seem like a major issue, getting a viewer to binge-watch as much content as possible is something that OTT platforms thrive upon. 

To overcome this challenge, the platform can adopt behavioral analysis to track how these users are interacting with the ‘Watch More Like This’ section. 

For starters, they can observe the heatmap of this page to identify the areas that receive the most attention, while they can also watch the session recordings to see what actions users take after they’ve finished watching something. 

Based on these insights, the platform can then discover different ways to engage users at this stage and optimize this particular section. 

Leveraging customer behavior insights at every step of a user’s journey

While the primary goal of users on an OTT platform is to stream content, not all of them have the same preferences, challenges, and mindset. 

Some are new to the platform and are just trying to figure out how it works, while others might be regular users who know exactly what they want to watch. 

Building an optimized experience for every type of user is a challenge that every business has to deal with consistently. This is why you must have a robust strategy in place to leverage behavioral analysis and get deeper insights into user behavior. 

One of the key strategies is to define the important stages of the user journey on an OTT platform and implement behavioral analysis according to the specific goals and challenges of users at these stages.

1. Discovering the platform

In the initial stage of the user journey users arrive on your website to not only explore the platform but also to get an idea about the content you are offering. Based on what they see and experience, these new users will decide whether or not they want to become paying customers.

Here, businesses can closely analyze the behavior of new users to understand their perception of the platform and discover important patterns or trends in their decision-making process.

For example, new visitors who arrive on an OTT platform are often trying to find one specific movie or show, and they just want to know whether the platform has it or not. 

Suppose Gary, a new visitor, arrives on a streaming platform looking for a popular crime-thriller show called ‘Mindhunter’. 

If the show is available, Gary will most likely convert and become a paid subscriber. However, if he cannot find this show, he will just leave the page and move on to another platform. 

This is a lost opportunity for the business and can lead to even more drop-offs in similar cases. 

To prevent this from happening, the streaming platform can opt for behavioral analytics tools like session recordings to see how visitors like Gary interact with the platform once they realize that it does not have their preferred show or movie.

Do visitors immediately leave the page? 

Do they stop and explore the other shows or movie recommendations? 

How far do they scroll on this page?

Through session recordings, the platform can find answers to all of these questions and can also discover interesting insights about visitor interactions at this stage of their journey.

Based on these insights and observations, the platform can then improve its content recommendation algorithm and also make sure that its best content is displayed within the area that receives the most attention on this page.     

By fine-tuning these crucial aspects based on visitor behavior, you can significantly impact the decision-making process, enticing users to move from consideration to subscription.

2. The consideration stage

Another crucial aspect of a visitor’s journey is the consideration stage. Here, the visitors are convinced of the platform’s offering but are still trying to learn more about it before they become customers. 

When it comes to streaming services, visitors want to experience the platform before they even convert into paid subscribers. This is why most streaming platforms offer a free trial period where users can access most of the available content for a limited period.

For instance, let’s assume that a streaming platform offers a 14-day free trial to new visitors. However, there has been no growth in this number and it has remained within the same range for the past 6-8 months. 

The platform then decides to conduct a thorough analysis using website heatmaps and starts to observe visitor behavior on its home page. 

During this analysis, they realized that even though the home page displays a wide range of shows, movies, and documentaries, new visitors hardly interacted. 

Also, since there was no clear CTA on the home page, a lot of visitors were clicking on the navigation bar to probably get more information about the platform. 

So, based on these crucial website heatmap observations, the company can now either optimize its home page to guide new visitors or display relevant information about the pricing, benefits, and other important FAQs. 

Also, instead of displaying all the available content at once, the platform can instead promote only its most popular shows and movies to new visitors. 

This is how businesses can leverage website heatmaps to gather actionable insights and use these observations to guide changes and improvements on important pages.

3. Onboarding new visitors 

Now that the visitor has finally become a paid subscriber, the onboarding process sets the tone for the entire relationship. 

Crafting a user-friendly interface and recommending relevant content that aligns with their preferences is a great way to improve the onboarding journey. 

Additionally, analyzing customer behavior becomes all the more important as the business now has the opportunity to learn more about the user’s preferences, likes, dislikes, interests, and so on.

For example, let’s say that a user has just become a paid subscriber and is ready to explore the platform and watch all their favorite content. 

However, as we saw in the previous example, users often feel overwhelmed when there are many options to choose from. To avoid this problem you can opt for a crucial part of behavior analytics – on-page surveys. 

When a new customer is about to explore the platform, you can prompt a survey with questions about their favorite genres, categories, formats, or preferences.

As soon as the user shares their answers, you can recommend content that aligns with the preferences they just shared. Also, based on these survey responses, you can predict content formats or genres that they might like and optimize their recommendations accordingly. 

By doing so, you create a continuous cycle of content recommendations that perfectly match the user’s taste and liking.

Moreover, you can also use these on-page surveys at different stages to understand whether or not the users are enjoying their experience and also ask for feedback and suggestions to make further improvements.  

4. Engagement and content consumption

As users continue to watch content and interact even more with your platform, you need to focus on improving user engagement and ensuring they remain satisfied with the available offerings. 

Again, behavioral analysis is a great way to achieve this and learn more about important aspects such as watch patterns, consumption trends, and viewer preferences.

Ever wondered why certain shows or movies become binge-worthy favorites? 

Apart from a lot of social media promotions, streaming platforms heavily recommend these shows to their existing customers based on their watch patterns and viewing trends. 

Also, they analyze various behaviors such as whether users prefer shorter episodes over lengthy ones, or whether they prefer movies over TV shows. 

All of this research and behavioral analysis gives them valuable insights into viewer preferences, based on which these streaming platforms try to promote relevant content. 

One of the best ways to do this is by analyzing heatmaps of different pages and understanding how users interact with important sections. 

For example, a streaming platform can use website heatmaps to observe the ‘What Others Are Watching’ section and identify the areas that receive the highest clicks and interaction. 

Based on these insights, the platform can then strategically place popular shows or new releases in these areas, ensuring that users are drawn to their best content effortlessly.

As we saw in one of the previous examples, streaming platforms can opt for session recordings to observe user behavior and identify potential friction points in the recommendations section. 

These insights can help refine their algorithms, and can also enable businesses to offer more accurate and appealing content suggestions, ensuring that users stay engaged throughout their time on the platform.

5. Burnout and retention

Be it eCommerce, B2B, or even on-demand streaming, retaining customers is the key to the success and growth of any business.

Using a combination of different behavior analytics tools, you can develop a strategy to avoid customer burnout and find effective ways to retain outgoing customers.

For example, you can look at your analytics tool to identify users who have been using the platform less frequently. These users might be potential churners who are no longer interested in the streaming platform for some reason. 

To make sure that they continue to use the platform, the business can prompt pop-up surveys whenever these users interact with the website and either offer plan extensions or try to understand why they are not as active anymore.

Moreover, some streaming platforms also offer breaks to customers where they can stop their subscription temporarily and join back after a few months for no extra cost.

By understanding the intention of your customers through on-page surveys, you can implement either of these strategies to show empathy and offer assistance at different points to your customers. 

Another key strategy is to analyze user behavior on account exit pages.

For example, if users wish to deactivate their account, streaming platforms usually prompt personalized offers or benefits to prevent them from taking this action. 

You can take this a step further by watching the session recordings on this page and understanding how users are interacting with these offerings. Also, you can analyze the heatmaps to identify click patterns on this page.

This should be an ongoing activity where you gather actionable insights from these pages and use them to optimize the content and placement of your offerings. 

By monitoring watch history, survey responses, heatmaps, and session recordings, streaming services can optimize their content libraries, introduce loyalty programs, and offer exclusive previews to keep viewers hooked and invested in the platform.

Discover the ‘why’ behind every user action with VWO Insights – Web 

User expectations are at an all-time high. 

No matter what industry you belong to, users expect you to provide an optimized experience that not only matches their needs, and preferences but also offers innovative solutions to their problems. 

This is where VWO Insights – Web comes into the picture. 

Unlike the traditional analytics tools that only offer data about what actions a user is taking, VWO Insights – Web provides the tools that are necessary to discover the reason behind these actions.

Be it AI-powered surveys that help you understand the customer’s voice better or advanced form analytics that help you identify friction points in crucial lead generation forms, VWO Insights – Web offers everything you need to optimize roadblocks and improve the overall website experience.

Moreover, VWO’s website heatmaps and session recordings help you to see exactly how visitors interact with every page on your platform, enabling you to uncover actionable insights and optimize every stage of a user’s journey. 

Take a free trial of VWO Insights – Web to experience all of these features in action and discover in-depth insights to boost your website’s performance.