Chris Jackson

viewer relationship management: what data is available?

There’s a lot of talk right now about approaches to Viewer Relationship Management (VRM). TV broadcasters are keen to make the most of modern technology in collecting and analysing data about viewers, just as retailers have been doing for years in CRM initiatives.

The most recent UK announcement in this area was from Sky, who are growing their viewer panel to an impressive 500,000 homes. Channel 4 have been talking publicly about the importance of VRM for some time.

Connecting viewers more closely with broadcasters is a major theme of our work here at MetaBroadcast. Over the next months I’m going to write a series of blog posts on this topic.

how close is too close?

To start off, I want to explore the strength of the relationship between broadcaster and viewer.

Broadcasters occupy an exceptionally strong place in the national consciousness. Despite a massive increase in available TV channels, the old analogue terrestrial broadcasters still bring in 75% of viewing hours across their families of channels. On average people in Britain watch four hours of TV per day. In the US, where a massive choice of TV channels has been commonplace for twenty years, the broadcast networks also still also occupy a pivotal place and TV hours are even higher.

All good news for broadcasters, but exactly what kind of relationship can a broadcaster expect with their viewer? People might spend longer with a broadcaster than a retailer, but how does a broadcaster translate that into data, and ultimately a stronger relationship?

To answer this, let’s try a thought experiment: how comfortable would you be if someone at a broadcaster could access all your TV viewing? The answer for almost everyone is “not very comfortable”. TV is a guilty pleasure for many people—not the sort of thing we want to publicise. A few years back we ran an experiment, called Gawp, where we asked people to share everything they watch on TV, just as some people share all their music listening on Facebook/ Spotify, and previously last.fm. Gawp did not resonate well with mass market users. More recently, the similar features on Facebook have not taken off for TV.

A lot of people are equally uncomfortable with a retailer having access to their purchase and browsing history. The difference is that often they have little choice. An online retailer can force you to use an online account, you don’t need to log into a TV, and even if you did, how would anyone know who was in the room, and whether they were truly paying attention? The only way to collect comprehensive TV viewing data is with a lot of help from the viewer.

what data is available?

Broadcasters are left with a varied set of data. It’s really useful stuff, but a long way from the holy grail of a simple, single customer view. Major data sources available to broadcasters will include:

  • full, anonymous data from representative panels consisting of a small sample of viewers
  • full, anonymous data for all users on some platforms
  • full data for on-demand platforms operated by the broadcaster themselves

They’ll also have high-level viewing statistics for some platforms, a mass of anonymous access log data from across their own websites and apps, and scattered rich data for some shows that have made a multiplatform investment.

what now?

How can a broadcaster turn this mixed bag into something useful? There’s a wide range of data fusion techniques that can be employed to use the available data. But we think there are two areas of low-hanging fruit:

  • Social: there’s a huge amount of viewer data on Facebook and Twitter, and loads of effective ways to mine it for insights. All the data is pinned to specific users. Yet most broadcasters use these tools as a marketing tool, just to get the word out about a show. Few go back to collect and analyse the data about their viewers.
  • Fans: to get great data you need viewer cooperation. Can you engage with your biggest fans in a way that makes them want to give data back to you?

To begin this series of blog posts, I’m going to cover each of these opportunities in turn, before discussing some of the data fusion techniques. Meanwhile, we would be delighted to hear your views about the development of VRM in your organisation or across the entire market.

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