Redefining OTT with big data analytics

Over the top (OTT) has been the monster in the closet of the telecommunications industry for the past couple of years, and conventional wisdom would say there are two approaches that operators can take to such a threat: Beat them or join them. Initially responses were more defensive in trying to block OTT, though over time responses have shifted more toward embracing it.

Beating and joining, however, are not the only available options. A third approach that could represent greater value for operators is to take the approach of optimizing, thus redefining OTT as “optimizing the transaction.”

Operators have found a profitable position that doesn’t necessarily require the ownership of content but rather facilitates the transfer of content. The view taken with this business model stresses the volume of users that can be reached. The evolution of the competitive landscape as well as differing capabilities of operators to participate throughout this value chain mean most operators will diversify the methods used in their business models to include aspects of beating, joining, owning and optimizing.

Proactively maximizing the subscriber experience is the ultimate goal, and the key to reaching this goal is the effective use of big data analytics. Big data analytics, as demonstrated by companies like Guavus, driving optimized transactions can also be used to apply a certain quality of service to a specific OTT application. Ultimately OTT as we’ve come to know it will become less about managing over the top and more about optimizing the transaction and benefiting from the resulting customer experience.