Big Data and STBS: Boxes with dedicated analytics tools

On the last blog in the Big Data series we discussed employing the Content to Commerce model in the STB environment. In this section we cover the psychology and science behind data analytics and the understanding of the demographic based on viewing habits and trends. An in-depth understanding of these data hacks and inferences developed by psychological experts and data analysts have helped us predict and formulate key value pairs in our product, that in turn help our clients make customized event and collective behaviour segments specific to their needs .

Here’s a little tipping from the experts that can help you decode your users to sell more to them and earn greater revenues as a Satellite TV Service Provider :

Decoding TRPs More Scientifically:

TRPs have long been a measure to figure out the most watched shows, popular channels and hence decide the commercials for the sponsorship. As any Ad Analyst would tell you, it doesn’t make sense to air commercials related to kids after 11 pm. Most families are wrapping up the day and the target audience and the decision makers are fast asleep.

But this information has been around for decades, where is the edge that you need from these numbers? TRPs alone are an obsolete method to decode audience profile, decide the target group and air the right content. The conventional prime time television is not everyone’s prime time television. With shows being recorded and commercials being fast forwarded not everything is sold by filler ad content. So how do you sell ? How do you lure sponsors and advertisers ?

The answer lies in more intricate data. Data that doesn’t depend on TRPs alone. It depends on extracting trends from the given numbers by analysing them. That’s where data analytics tools come into play. They involve intricate events, behaviour patterns as the logic for creating groups and helping you customize your key events. This understanding of the audience set also helps us build in key value pair events and suggestions as solutions to our clientele.

User Insights:

Experts from the Communication Research Facility at South California have decoded the audience behaviour , based on Tv viewing patterns.

The report suggests a psychological link between who we are and what we watch. The advertising industry brackets people in the Aspirer and Achiever category. Turns out that, age groups, social standing and occupation can all be bracketed by monitoring people’s TV viewing habits.
This however remains a research and a claim backed by a sample set. However you can create your own sample sets by referring to reports and predictive calculations using Analytics.

For example:

Ronnie, 34 year old male, watches a lot of Sci-Fi, He is addicted to crime shows as you can see from the air time schedules of different channels. Ronnie isn’t much for complex sports or intellectual information. Educational channels find him as a rare visitor. Most likely, Ronnie is a blue collar employee, holding a basic degree. Further, the afternoon air time finds his television set playing kid’s educational programs. The 8 to 10 pm slot has daily soaps playing. You have a family man with kids.

What can you sell to this profile? Movies under a pay to watch offer since a visit to the movies is a rare event for the family . A subscription to Kid’s Educational series that you air on service channels. Maybe even a new channel that airs only crime and detective series.

How can you sell this data further?

Production houses, advertisers are businesses need these consumer reports to show to sponsors and hiring firms. This data can be sold as a re-packaged product. Only if you have this data as a comprehensive report or structured information.

Why You Need a Big Data Analytics Tool?

Lot’s of researches and hacks can tell you different things. But how do you verify these reports or claims? This is why you pool in data from different places. This is a tedious activity. Plus studying real time data is very different from research data.

Data that is actually gathered by implementing algorithms and predictive analysis is far more accurate and insightful. Plus Data Experts work at incorporating features such as customized key value pairs specific to your industry for your convenience. There are also relevant suggestions that help you analyze your customers better. All this and as a final result you need to have structured reports that are easy to interpret and apply to your strategic models.

Television Revenue Models have always been data dependent.It’s time to look at data is a different way than the conventional TRP model. Adopt Big Data Analytics simplified by efficient tools. To know how we can help you further, contact us.

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