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Behavioral analytics

What is Behavioral Analytics?

Behavioral analytics is the practice of capturing, aggregating, and analyzing user behavior data from a software application to better understand user preferences, improve digital products, and drive user satisfaction.

For OTT video streaming services, behavioral analytics means capturing user behavior data from a digital video streaming platform, centralizing that data in an analytics software tool, then analyzing the data to develop insights into audience content preferences, viewing habits, and trends.


How Does Behavioral Analytics Work?

1) Capturing User Behavior Data

Capturing user behavior data is the first step in behavioral analytics. 

With traditional media distribution channels like cable television and broadcasting, there was no mechanism for distributors to track user behavior. But in OTT media distribution, where video content is streamed over the Internet, each and every user interaction can be programmatically captured and recorded for downstream analysis.

OTT video service providers use specialized software applications to capture user behavior data from every session that takes place on their platform, including things like signups, transactions, searches, browsing habits, which content a user views, the device they use, and much more.

2) Normalizing and Aggregating User Behavior Data

Before user behavior data can be efficiently analyzed, it needs to be cleaned, prepared, normalized, and aggregated into a single centralized system.

Data normalization ensures that the data is organized and consistently formatted across all records and fields, while aggregation brings all of the data into a single location where it can be analyzed without anything being missed.

3) Analyzing User Behavior Data

Once user behavior data has been captured, normalized, and aggregated, the data is ready to be analyzed. 

Content owners and distributors can analyze user behavior information in many different ways to gain insight into how audiences are engaging with their platforms. They can start with the basics (e.g. Which content offerings have been the most popular?) and then dive into content affinity and experiment with ways to enhance customer satisfaction and reduce churn.

OTT platform operators can leverage purpose-built analytics solutions for media distribution that leverage AI-driven automated data analysis to analyze user behavior data, extract insights, and deliver actionable recommendations for content owners to maximize revenue.


What are Three Types of Behavioral Analytics?

Content owners and distributors can use behavioral data in a variety of ways to develop insights into user activity and preferences. Below, we highlight three types of behavioral analytics and why they’re useful for OTT video streaming providers.

1) Segmentation Analysis

Market segmentation analysis is a type of behavioral analytics that tries to group users into defined categories based on some shared characteristics. OTT video streaming services are often interested in grouping users based on their common interests, attitudes toward specific types of content, or other personal characteristics.

Segmentation analysis helps OTT streaming companies understand audiences more deeply and predict what types of content will perform the best.

2) Funnel Analysis

A funnel analysis uses behavioral data to better understand how users are acting in the context of a marketing/sales funnel. Examining user behavior at various stages of the funnel can help marketing teams identify drop-off points and implement strategic changes to optimize conversions. 

In the context of an OTT video platform, that could mean testing different versions of the same movie trailer to determine which one is most likely to result in a TVOD transaction.

3) Cohort Analysis

In a cohort analysis, experimenters create cohorts of users who did a similar behavior within a similar timeframe, then follow them over time and compare their customer journey against other cohorts who did different behaviors. Cohorts are constructed based on a specific shared experience (e.g. enabling push notifications when signing up for the app). 

Comparing cohorts of users that vary across a single dimension can help OTT video providers measure the impact of specific events on the overall customer journey and optimize their strategies for satisfying and retaining customers.

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What are the Benefits of Behavioral Analytics in Content Distribution?

OTT video streaming companies can use behavior analytics to better understand their customers and optimize the user experience on their streaming platforms.

Behavioral analytics makes it possible for streaming companies to answer complex questions like:

  • What devices, platforms, and technologies are customers using to engage with my platform?
  • How are new users finding my services?
  • How are users engaging with the platform? How are they choosing to browse or discover new content? Do they re-watch the same content, or search for something new?
  • How long do users spend on the platform each day?
  • What causes users to lose interest in the platform?
  • Which advertisements are the most effective?
  • What kinds of content is my audience interested in?


How Does SymphonyAI Media Help with Behavioral Analytics?

SymphonyAI Media is applying artificial intelligence to behavioral analytics for media and entertainment companies. 

Our Revedia Digital platform uses a purpose-built, trained AI to automatically analyze user behavior data and reveal valuable insights into audience behavior and content performance that support business decision-making for both content owners and OTT video distributors.

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