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09 Aug Predictive Analytics to Improve Retention and Increase ROI

Managing churn is a priority for OTTs. In order to properly monetize content, a steady user base is essential. The use of predictive analytics algorithms is one of the best ways to successfully manage churn and guide decision making. Churn prevention solutions can be implemented at every level of the organization, from quality of experience improvements and content strategy and arrangement to advertising placement, proactive customer service measures, et cetera.

 

The Factors

Online media services must control for, and reduce, churn to build successful and profitable businesses. Quality of experience across the entire service, content offered and the way it is recommended, and OTT pricing packages are three key factors users value the most when selecting and staying loyal to an OTT service.

 

The Metrics

Descriptive analytics tools are crucial to react and implement action plans in real time, as well as to learn from past experiences, but how do I identify those customers that are likely to abandon my platform? How do I preempt future behaviors? How do I correlate platform performance with customer behavior trends? Predictive analytics arise as the extra mile tool to make data-driven decisions across departments and build long-lasting success stories.

The advanced ability to PREDICT CHURN and even to segment your audience based on those predictive algorithms – beyond segmentation based on demography or geography – is shedding light onto this field. Churn prediction will tell you the likelihood of a user or group of users to abandon your service. With this, all departments within your business can row in the same direction towards inhibiting churn: content department, ads, technical, operations, customer service, marketing. [Stay tuned to our upcoming article about using A/B testing and Multivariate Testing (MVT) to dodge wrong decisions].

On the other side of the coin, CUSTOMER LIFETIME VALUE metric will forecast how many times a user will consume content for a specific time frame. The value in it comes when you know how much revenue each view generates. With lifetime value you are set to estimate how much each user will help you gain you within the next week or month. BI turns to be a great support to respond to your ROI forecasting needs.

And when you are able to combine and correlate customer behavior with real time platform performance, you are boosting successful business decisions. ERROR PREDICTION and alerting system flagging views which are likely to present disturbances combined with 1:1 view tracking will help you make the right call to technical departments and customer service teams.

 

The Use Case: Customer Service in Action

Combining the real time view tracking and behavioral monitoring of BI platforms with the forecasting insights of predictive analytics provides a deeper understanding of audience behaviors, consumption trends and patterns, and lifetime value. With such a rich understanding of your audience, Customer Service Managers can guide their strategies toward improving their user engagement.

For instance, if user engagement for an individual or particular segment of the user base declines – e.g. users who will churn within the next month, “light” users, users approaching end-of-contract, and any other dimension provided -, messaging can be targeted toward them to offer a promotion.

Proactive communications or a check-in following a complaint from such users aimed at repairing and furthering the relationship can be sent to affected customers to better mitigate complaints and legitimize vouchers and refunds, as well as prioritize tickets. BI platforms unique methods for complaint validation yield an improved net promoter score (NPS) through improved customer service.

Superior care for customers now translates into veteran, reliable users in the future.

 

The Bottom Line

While the benefits of investing in predictive analytics are many, it is clear that  proactive management of user churn is a key concern for OTTs and media services. Identifying factors impacting churn and the group of users which about to damp you, will empower your entire business with the freedom and certainty to articulate longitudinal strategies reduce customer leakage, increase average revenue per user, and optimize customer acquisition.

 

MORE: Click here for an in-depth interview with NPAW Product Manager Lucas Bernat on the prospects of predictive analytics

 

Are you a media company interested in the proactive insights delivered through the use of predictive analytics? Wondering how NPAW’s YOUBORA is uniquely able to segment audiences? Click here to schedule a meeting with one of our Business Intelligence Experts.

Just another thing to think about from us here at NPAW.