With data driving the success of the SVoD industry, OTT providers are faced with a bewildering array of data visualization platforms to choose from. However, with different platforms and a diverse range of capabilities available in the market, service providers are often left with little guidance on what may suit them. This article provides a checklist of criteria to compare different platforms and identify which is best suited to your needs.
Data visualization tools help SVoD businesses understand user behavior, pre-empt churn, and make critical business decisions on a micro as well as macro level. From industry leaders like Netflix, who makes no secret of its data-led strategy, OTT service providers across the board rely on big data to unpick audience behavior and spot patterns to inform key business decisions.
The market is crowded with generalist data visualization platforms making similar claims about depth of analysis, ease of deployment, user interface and so on. So it is important to choose a solution that offers the latest technology, the right implementation experience, experience of your sector, and the features and services that will help you grow your user base and convert trialists into loyal customers. How can you go about finding the data visualization platform that’s right for you? We recommend following these eight key assessment criteria.
1. What is the solution’s track record in the OTT industry?
The SVOD space has very particular requirements when it comes to data visualization. Service providers need insights around customer acquisition, behavior, viewership patterns and use them to drive conversion, retention, and growth. Consequently, you should be wary of platforms that claim to work equally well across a range of industries – say, from retail to streaming services. These generic platforms will need extensive customization to work for you and your specific business needs, and you may well find yourself having to adapt your requirements to match the platform’s capabilities. So, when you are looking for options, consider whether the solution has a heritage in the OTT space. A tool that is created specifically for the streaming video industry will be structured better for your specific needs, in a way that can connect the dots more effectively and streamline the process of uncovering actionable insights.
2. Where can the solution pull data from? What source connectors are available?
While conversion will always remain a critical metric for OTT providers, retention is equally important. Data insights can help you convert casual subscribers, including the growing segment of binge-and-churn subscribers, into die-hard fans. While exploring your options, look for a data visualization tool that can pull data from every source in your tech stack, be it marketing, subscriber management, app store, revenue, video metadata, site or even app analytics data. Only then can the platform give you a nuanced, 360-degree insight into subscriber behavior patterns.
Ensuring your data visualization tool uses inputs from all your data sources also helps deliver answers to vital business questions like what sources are performing best, gains from specific marketing campaigns, how well customers are converting from trials, how many happy customers are in the service, and so on.
3. What is the implementation process and deployment model?
Spend time thinking about how seamless your vendor’s deployment process is and how easily it can be integrated with your existing systems. Smooth integration is the first stage in an effective deployment. Consider whether your data visualization platform is cloud-based and easy to integrate via an API, or does it have to be installed on-premise: cloud-based platforms are far easier to get up and running. A dedicated customer success team is a critical part of the deployment process, to ensure you are not left alone to figure out the solution all by yourself and have a smooth onboarding experience. Put all the features to their best use and get the most out of your investment.
4. How extensive are the reporting and analytics capabilities?
Given the sheer size of the data sets that SVoD players work with, the right data visualization tool must be able to harmonize all the appropriate data sets in a holistic way, eliminating the need for any manual processing.
Fitting right in is the Wicket Scorecard, which is designed with exactly this philosophy in mind. It not only aggregates and harmonizes data from all your back-end systems automatically, it then applies machine learning and AI to help identify additional insights and trends. Wicket Labs also has a machine learning model to identify at-risk subscribers and a customer happiness index (CHI®) to categorize users. CHI uses your data to identify which subscribers are at-risk of leaving your service and allows you to identify the trends and elements that have the most influence over their possible departure, allowing you to deploy the right strategies to retain and remarket.
5. Are insights uncovered by the solution simple to export and make actionable?
Consider if the platform you are evaluating easily allows you to bridge the gap between analytics and actionable insights. Your platform should allow you to export information and key metrics easily, converting your data into intelligence that then needs no further processing. Only then can you identify happy customers, acquire more of them by running lookalike campaigns, and implement strategies to increase loyalty and keep trialists returning to the service.
6. Does the solution employ machine learning for predictive analytics into subscriber churn propensity, lifetime value?
AI and machine learning technology can help you aggregate and harmonize all your data sets and achieve greater levels of insights into user behavior to foster better decision making. Subscriber churn is a complex problem and is affected by more than 60 interrelated factors, or features in machine learning parlance, that have causal relationships with a customer leaving a subscription video service. A data visualization platform with the right machine learning model will be able to determine which elements are the most important and rank them accordingly. The Wicket Labs CHI score was developed to identify users that fit these patterns and has a proven track record in reducing churn and increasing audience lifetime value.
7. Does the solution provide visibility into third-party distribution channels?
An understanding of the performance of the third-party marketplaces that are directing viewers to your platform (think Apple’s App Store, Google Play, and Amazon Channels) is essential for growth. With subscribers coming onto your platform from different channels, and each channel featuring different metrics, SVOD businesses need a unified way of evaluating how each channel contributes to subscriber acquisition figures. Ensure that your audience insights platform provides a unified view into your third-party video distribution efforts, saving significant time in the process.
8. Can the solution provide a complete picture of user health and revenue performance? And can it answer the critical business success questions?
Only an advanced data visualization platform will have the ability to answer critical business questions and the insights to connect marketing spend with subscriber health. The right data visualization platform can help aggregate, synthesize, correlate, and visualize unique insights about audience behavior, and can apply this analysis into marketing promotions, re-engaging with at-risk subscribers, finding new audiences and so on.
Also, ensure you check the pedigree of your vendor and its track record in the industry. Just as no two SVOD players are equal, neither are data visualization platforms created equal. The right solution can help you boost audience lifetime value by understanding the big picture around user health, forming the foundation of effective macro-level business decisions.
Schedule a demo to see how Wicket Scorecard can help supercharge your business and uncover actionable insights into audience behavior.
Tags: artificial intelligence • audience insights platform • Customer happiness • data visualization • distribution channels • OTT • SVoD