An interview with Dr Julio Amador, Research Associate, Imperial Business Analytics with KPMG
When logging in to Facebook for the first time, we share a lot about ourselves, including demographic information, university education, work details and even our relationship status. This information translates into accurate predictors of our attitudes, so if we mix this data with characteristics about our wider network, include the daily (sometimes hourly) inputs we feed into the platform via posts and shares, along with numerous likes or updates, micro-targeting becomes even easier.
While Facebook has leveraged considerable data using micro-targeting tools and techniques tailored to individual customers, Twitter has struggled to turn advertising messages into a workable business model. For Twitter, these techniques become more complicated as users have very small amounts of data available in their social profile, making the act of targeting far more difficult.
Given the limited data on such platforms such as Twitter, brands must consider how they diffuse messages that engage customers by instead exploiting the network structure in which communication takes place. Without the opportunity for micro-targeting available to Facebook, research suggests that messages are diffused more effectively on open networks if brands engage in interactions with ‘weak ties’ (e.g. people who share few similarities with them in terms of their attitudes and behaviors). For instance, a study of influencers on both sides of the Brexit campaign suggests people who engage with those who think differently from themselves achieve the greatest reach.
But what does this mean for advertisers? Instead of giving a free product to someone who tweets about all the same subjects or testing a new advertising message on like-minded people, brands might consider engaging with people who think differently from them in order to maximise the spread of their message.
Written by Christopher Corbishley (PhD candidate)