All forms of TV data is what we are expert of

Posted In Technology - By Ryan Stewart On Thursday, November 16th, 2017 With 0 Comments

We are experts on all forms of TV data. From set-top-box to smart TV data, we have created platforms to collect, aggregate, store, model, and visualize TV data. We understand the differences between OTT viewing data and MVPD data and have developed models to provide integrated reporting across all platforms.

All forms of TV data

MVPD data processing

We have worked with many MVPDs across the world to collect, store, and analyze their viewing data from set-top-boxes, OTT services, and smart TVs. We’ve built viewing data processing platforms for many MVPDs covering platforms from Ericsson/Microsoft, Cisco, Verimatrix, RDK based and bespoke data collection platforms. The main characteristics that we find between all platforms are issues with the quality of the data, especially the EPG data and metadata for VOD, privacy issues connecting to the CRM data, and the complexity of Pay TV packaging. The architecture we implement is reasonably standard, and we now have sample code to interact with many of the common industry platforms. The conventional approach is collect the data from different devices, cleanse it through a set of learning filters, then storing it in a data warehouse where it can easily be queried and acted upon within the business.

Using TV data analytics to see why 4K’s failing

Deploying 4k video requires a considerable investment and many operators are finding that it does not have the expected uptake amongst consumers. We’ve been working with operators to use predictive analytics to help understand consumer uptake of 4k.

Taking set-top-box data to market

We worked with the TV ad sales division of an MVPD to establish the best monetization strategy for their set-top-box data. The set-top-box data is owned by a separate division of the holding company, so our first task was to work with both the media sales arm and the holding company to agree on the appropriate use cases for the data exchange, and how privacy would be handled. Once we had received the set-top-box data, we set up a cloud instance to ingest the data into, cleansed it, and fused it together with CRM data, EPG data, and as-run logs of the advertisements. With this in place, we had a sound dataset to begin the analysis. The MVPD is currently in the process of taking these segments to market, and the initial response has been positive.

Increasing VOD sell through

We’ve all heard Netflix’s claims that data gives them a competitive advantage over incumbent pay TV operators. The logic is that because they have data on all of the content their subscribers are watching they can better engage with them and improve their service. Our client, an MVPD, had recently launched a video-on-demand service but found that usage had plateaued after the first nine months. Although their marketing was effective they were struggling to convert trialists into paying customers. We had previously created a data warehousing infrastructure for our client using Amazon Redshift and used the data we had already collected to build a model that the client could use to drive usage.

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