In the word of digital marketing, one of the more controversial moves I’ve seen recently was from U.K. car insurer Admiral. The company recently announced that it would begin offering car insurance discounts to less risky customers based on voluntarily provided social media data. The insurer would analyze Facebook likes and posts, and could analyze the language and patterns. This allows it to identify behaviour and personality traits which predict a higher or lower risk compared with the average for that demographic profile.
While Admiral’s plans were eventually scrapped due to Facebook’s data privacy policies, the simple truth is that many digital footprints are already being harnessed, analysed and shared to assist digital marketing efforts (from consumer goods to political parties). It’s possible to increase conversions and reduce the cost of acquisition through understanding digital visitors better and ensuring that adverts reach the “right kind” of consumer.
Trading of such data between interested third parties is also growing, with data management platforms (DMPs) providing digital marketing teams with behavioral profiles based digital data collected across a wide variety of websites over a period of time. For example, an online clothing retailer may identify you, a first-time shopper on the site, and query this centralised DMP to get a detailed shopper profile indicating your likely segment and product category interest probabilities. This is based on your previous visits to sites such as airline and hotel bookings, the news articles you've read and your cellphone company.
Generally, consumers seem happy to share much of their digital data (even if they're not aware of the full extent of how their data is used) as long as they perceive some value – particularly when it comes to personalisation of the website experience. A variety of research showed that well over 50% of consumers expect brands to know them more intimately, 90% are willing to share basic browsing behaviour, and over 60% are willing to share detailed personal information in order to receive a more personalised experience.
Recent behavioural analysis research at Stanford University aimed to predict a customer’s likely personality traits, beliefs and opinions based on an analysis of the digital behaviour of 8 million social media accounts (compared with online psychometric tests). The algorithms showed that personality traits such as generation, introversion/extroversion, family situation, race, smoking/alcohol use and political or religious beliefs can be predicted to a high degree of accuracy based on an analysis of an average of 200 Facebook likes per user.
