MUCH OF THE DICSUSSION has been on how Cambridge Analytica was able to obtain data on more than 50m Facebook users – and how it allegedly failed to delete this data when told to do so. But there is also the matter of what Cambridge Analytica actually did with the data. In fact the data crunching company’s approach represents a step change in how analytics can today be used as a tool to generate insights – and to exert influence.
For example, pollsters have long used segmentation to target particular groups of voters, such as through categorising audiences by gender, age, income, education and family size. Segments can also be created around political affiliation or purchase preferences. The data analytics machine that presidential candidate Hillary Clinton used in her 2016 campaign – named Ada after the 19th-century mathematician and early computing pioneer – used state-of-the-art segmentation techniques to target groups of eligible voters in the same way that Barack Obama had done four years previously.
Cambridge Analytica was contracted to the Trump campaign and provided an entirely new weapon for the election machine. While it also used demographic segments to identify groups of voters, as Clinton’s campaign had, Cambridge Analytica also segmented using psychographics. As definitions of class, education, employment, age and so on, demographics are informational. Psychographics are behavioural – a means to segment by personality.
This makes a lot of sense. It’s obvious that two people with the same demographic profile (for example, white, middle-aged, employed, married men) can have markedly different personalities and opinions. We also know that adapting a message to a person’s personality – whether they are open, introverted, argumentative, and so on – goes a long way to help getting that message across.