Getting OTT Analytics Right: Common Pitfalls to Avoid

With every new product update, it seems OTT platforms are continuously improving their personalization and recommendation algorithms. These features—powered by sophisticated data analytics—have been instrumental in delivering strong customer experiences (CX) and fueling repeat content engagement.

But while much of the industry celebrates these front-end successes, many streaming providers are still missing a major opportunity: unlocking the full value of data across the commercial and operational sides of their business.

The Untapped Value of OTT Data Analytics

Understanding subscriber churn, ad effectiveness, content watch time, load times and stream quality is critical – not just for customer experience and satisfaction, but also for strategic business performance. When harnessed correctly, these insights can also benefit the commercial, marketing, operations, and security teams of video-on-demand platforms, driving better decision making and stronger results.

As a leading strategic advisor within the TMT sector, Cartesian has helped numerous OTT clients to improve their streaming data analytics. Through this work, we have identified various pain points that arise without a proper data analytics strategy.

Common Pain Points include:

1. High Costs: Rising cost of hosting and processing data through cloud services
2. Redundant Tools: Misaligned analytics strategies often lead to the usage of multiple tools with conflicting data
3. Team Misalignment: When analytics and business teams are not on the same page, the resulting deliverables may not align with business needs
4. Data Silos: When teams consume, produce, and analyze data without alignment they are often left with different and conflicting “truths” about the data
5. Poor Infrastructure: Legacy tools may not be appropriate for the volume and velocity of data, or business use cases
6. Unclear KPIs: Multiple, unclear definitions of KPIs in the business lead to unclear prioritization needs
7. Reporting Inaccuracies: Inaccurate or misunderstood analytics may lead to a total loss in confidence of reports and dashboards
8. Reactive vs. Proactive: Without a cohesive, forward-looking data plan, platforms are stuck in firefighting mode
9. Data Governance: Risk of PII (personal identifiable information) being stored/used incorrectly, which can lead to legal and reputational trouble

Cartesian’s Approach to OTT Analytics

For many businesses who are experiencing these issues, a targeted analytics ecosystem review is the first critical step to resolving the pain points. Cartesian works with clients to design customized, “right-sized” evaluations based on the highest priority pain points and the data issues that matter most for your business.