Case study

We Enabled Our Client to Gather Audience Intelligence Around Their and Competitor’s OTT Content Enabling Better Marketing Strategies

Data Analytics Case Study


The client’s key objective was to get insights and recommendations around the voice of customers for their and their competition’s OTT content.


  • We developed a social media intelligence pipeline to gather data from multiple platforms such as Facebook, Instagram, Twitter, and Wikipedia using data scraping and APIs.
  • We created an NLP-based Audience Sentiment Model on the social data to extract key discussion themes, audience chatter around the topic, sentiment, and dominant emotions.
  • Using the outcome from the Model and historical analysis we provided insights to the clients on the content feedback, audience traction on competition shows, and likewise.
  • The insights were shared on a weekly basis to ensure our recommendations are more relevant.



We set up a weekly streaming app buzz insights report for our client showcasing the voice of customers along with recommendations around marketing and content improvement strategy.


The weekly insights enabled the client to take necessary decisions on improving the content promotions on social platforms, understand the reception of owned and competitors’ content and be aware of negative sentiments which may impact the viewership.



  • Social Media Intelligence was a game changer to stay ahead of the competition in content strategies and promotions.
  • Recommendations and Insights helped in improving audience experience leading to higher user retention.
  • It also helped in acquiring content available due to cancelations by other OTT platforms.

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