Blindly trusting it can lead you to the wrong conclusions.
Nicholas Barr's insight:
A timely reminder that 'big data' does not tell the whole story. Social TV analytics, which may be seen as an application of big data, have become very useful in measuring and identifying what certain niche groups are watching and the moments that excite them. However, as the article suggests, the insights may not reflect the scale and sentiments of the whole audience, possibly not even the majority of the audience. This time last year there were three big independent names in social TV analytics: Bluefin Labs, Social Guide and Trendrr. Since then SocialGuide was snapped up by Nielsen and Bluefin Labs by Twitter with further news that Nielsen and Twitter are themselves collaborating. It may seem that there is a circling of the wagons in the 'wild west' of the new TV landcape. However, there is still more pioneering work to be done to truly unlock the gold in them data hills.
The poor translation makes reading this quite hard going. However, pages 11 - 22 contain some interesting analysis. The crux of this paper is that, within France, Social TV offers only a limited opportunity for advertisers. Currently, it is a niche market. Driving audiences towards social interactions means steering them away from the main screen towards second-screen devices. Moreover, the most obvious time for second-screen engagement is during commercial breaks. As such, broadcasters risk undermining their core ad sales and alienating their majority audience by trying to chase these early adopters.
The difficult truth is that the majority of people within the UK television audience don’t use Twitter. This fact, that it is only ever represents a small sub-set of an audience, has huge implications for Twitter as a measurement tool, let alone as an audience driver or advertising medium...
Nicholas Barr's insight:
All too true. Nigel echoes the point highlighted earlier this week on the hidden biases in big data. Twitter seem to be riding the principle that if it can be measured it can be sold. However, although a lot of very big numbers are often quoted they are currently abstracted from meaning. We have yet to understand what 'good' numbers should actually even look like.
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