How to Measure and Optimize Your App for Over-the-Top (OTT) Devices

If there’s one thing consumers love more than content, it’s having the ability to control it.

The popularity of over-the-top (OTT) devices is undeniable. According to the Bureau of Labor Statistics, over half of the average American’s leisure time was spent watching television, and many did so by interacting with OTT devices and apps.

In my previous post, I touched on several use cases for developing an OTT-device app, including the psychographic needs that could be met through an immersive affinity app designed to turn customers into brand advocates. The value proposition for OTT-customer engagement is profound — as long as brands know how to effectively analyze, test, and optimize the user experience.

Let’s dive deeper into the world of developing OTT apps for these devices by turning our attention to Apple TV.

What Can OTT-App Developers Learn From Apple TV?
The simplicity and sophistication behind Apple TV is something every OTT-app developer should consider before traveling down the road of OTT-app creation. Apple TV utilizes a grid-based layout that is easy to navigate.

The most important aspect of the Apple TV grid layout is the Top Shelf. This high-value real estate showcases personalized, dynamic content while providing a direct path to specific content within the app. This could include highlighting a user’s favorite television shows on a particular network or displaying home décor ideas that may be of interest based on user preferences.

Top Shelf app placement can be huge for your brand. Top Shelf placement reveals strong customer loyalty and can provide high value for both your business and your customers — when done properly. This requires using analytics and optimization tools to enhance the customer experience. How can your brand accomplish this?

Apple TV: Analytic Tips
Analytics plays an integral role in gaining a real-time understanding of how your customers interact with your brand on Apple TV. Further, software development kits (SDKs) are available for Apple TV that include Adobe Analytics and Adobe Target. Here are some quick tips to help you get started.

• Capture How the App Is Launched.
  Are customers launching your app from the home screen or from the Top Shelf? By placing the launch location in conversion variables (eVars), your brand can determine where your customers are engaging with your app most frequently. Of course, this is important to know for analysis; but did you also know that, when your customers place your app in their Top Shelf displays, they are telling you that they highly value your app?
• Use SDK Timers to Measure Time Spent in Content as Well as Load Times.
  Engagement falls by the wayside when load times are lagging. Whether you are delivering a large piece of content over a fast connection, or a small piece of content across dial-up, using SDK timers will help you evaluate how content load times may be affecting the user experience.
• Use the SDK Lifetime Metric to Differentiate High- and Low-Value App Users.
  This metric helps differentiate between high- and low-value app users by measuring data such as videos completed, recipes viewed, or content favorited over the lifetime use of the app. The lifetime-value metric can also be used from an analytics standpoint to segment the customer behavior of high-value users and compare it to others.
• Use Analytics to Find the Sweet Spot of Preloaded Vs. Streamed Content.
  Because Apple TV apps are limited to 200 megabytes in size, it’s important for your brand to determine what the value of upfront delivery is versus streaming content in. Brands can use Adobe Analytics to find the perfect optimization point, creating the best user experience so users — especially those on slower connections — don’t have to wait.

Apple TV: Testing and Optimization Tips
Below are tips to help you develop an OTT-device app that delivers personalized customer experiences by using a SDK for Apple TV with Adobe Target.

• Use Target Recommendations for Personalizing Content Within the Top Shelf.
  Delivering video recommendations to your customers based on their past viewing histories is a great example of OTT-app personalization. Other examples include listing top-five recommended recipes based on previously favorited recipes or workout suggestions based on previously completed routines.
• Test What Content to Show Based on Time of the Day and Day of the Week.
  Finding the optimal time for content consumption is key to optimizing the user experience. For example, a public-television app may test to see whether more content is consumed based on promoting children’s programs weekdays during early morning and midafternoon hours. Another example would be for a financials app to measure content consumption by displaying a stock ticker during trading hours and relevant news updates before and after trading hours.
• Use Rules-Based Targeting to Turn on “Bonus Content” for High-Value Users.
  Including a hidden app feature that comes to life after your customers have watched one hundred shows or spent a hundred hours interacting with your app gives your customers members-only experiences that make them feel as if they are part of something special. Marketers can also use rules-based targeting without having to contact the IT department.

Looking for ways to measure and optimize for wearables? Then check out my previous post in which I discuss ways you can analyze, test, and enhance your brand’s app for Apple Watch.

Still wondering whether your brand should take the leap into wearables and OTT-app development? Read my post titled, “Marketing Across Wearables and Over-the-Top (OTT) Devices: Should Your Brand Take the Leap?”