Going beyond Subscriber Data, when devising OTT Content strategy

OTT industry is aflush with subscriber-related data

As the India OTT war hots up, various perspectives are emerging, about subscriber behaviour data. One narrative centres around using such data to better understand viewer preferences and pre-empt their future content choices. It highlights the power of Tech & the control that OTT players hold, over their users’ data. In other words, OTT companies know exactly who is watching what, on what device, how often, at what time of day, for how long, at what cost. Such granular level of data-capture enables them to harness data and discover deep, actionable insight into viewer needs.

Subscriber-related data is expected to further explode, in the upcoming 5g era

Another narrative signals to the seemingly endless supply of bandwidth that 5G will bring in, and its impact on subscriber data-collection and use. The advent of 5g is expected to enhance volume and quality of content consumption, like never before. This change is expected to bring even more power and choice to viewers. Imagine a scenario where viewers have uninterrupted streaming and storage of superior quality… a seamless content-viewing experience across in & out-of-home, irrespective of number of OTT subscribers within a household, irrespective of device used, irrespective of data-connection (wifi/ mobile data) used. OTT players are gearing up for the increased volume of subscriber data the 5G shift is expected to trigger.

OTT’s key challenge — ‘How do I stand apart from competition?’ The answer — Content.

At the supplier end of the industry… today, OTT is a crowded space, with over a dozen players. 2018 saw OTT back-end (Amazon Web Services, Microsoft Azure Stack) becoming increasingly commoditised. Thus, OTT players are similarly geared to respond to the much-anticipated data explosion. Tech is not as much of a differentiator as it was earlier.

To compete better, OTT companies are shifting focus from Tech and Distribution, back to Content. All major OTT players are investing heavily, in original content. The Netflix-TataSky partnership announced in 2018 is expected to significantly expand, the number and variety of titles available to viewers. Production of regional content is gaining ground, as OTT players ride on data democratization to penetrate lower-tier markets. Some OTT players ride on the popularity of major TV shows eg. Bigg Boss, Roadies etc. while regularly launching originals, to keep viewers engaged. On the other hand, players like ALT, Netflix, Viu, Hotstar are already driven by original/ exclusive content.

Building content acquisition strategy — an art or a science?

While the power of mining subscriber data is a compelling reality, it is important to accept the role and influence of the Human factor, in understanding viewer choices. Recommendation engines might trigger repeat viewing and extend time viewers spend on an OTT platform. Yet, viewer preferences are being continually formed and modified basis various cultural, social and psychological contexts in which viewers function. After all, playlist & title recommendations that pop up to a viewer are partly curated by talented individuals working in the OTT space. Let’s call this the ‘inside out’ approach to creating/ curating content.

However, Content acquisition decision-making cannot be an exact science. Subscriber data will provide a behaviour-led understanding (the ‘science’) of viewer preferences and habits. However, to drive Content-led differentiation, ‘art’ factors come into play. OTT companies need to complement subscriber data analytics with a deep understanding of viewer mindset, using various other disciplines. Layering learnings from varied influences onto Analytics, will help OTT players uncover content themes that truly resonate with viewers. So where do OTT companies access such influences?

ThinkBumblebee applies an ‘outside in’ lens, combining diverse disciplines like semiotics, ethnography, social psychology, social data etc. with Analytics. This helps OTT players gain a deeper contextual understanding of subscriber behaviour, preference and choices eg.:

  • What payoffs are viewers seeking — basis their search on the OTT app they are using? This is the ‘discoverer’ segment, which is hungry for fresh entertainment themes.
  • Who are the ‘early adopters’ — the set of viewers that leads others to sample/ binge-watch newly launched shows?
  • What are the contexts in which media is being consumed? What is the subscriber mood, in that moment?
  • Which genre/s cater to which payoff?
  • Is there a correlation between time of day and genre viewed? … and so on.

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