The FT recently produced a calculator on its online site that calculates the value of your individual personal data to marketers. The average person’s data often retails for less than a dollar. I am clearly an average person, with the my data worth the princely sum of $0.4639. General information about a person, such as age, gender, location is worth a minimal amount. More specific information, such as if you are shopping for a car, a house or travel is slightly more, and milestone events such as having a first child (which prompts a dramatic change in buying patterns) drives up the value significantly.
I love the story that I heard in a marketing course at business school about Tesco’s monitoring of post birth shopping patterns. Their ClubCard data appeared to pickup a high correlation between nappies being added to a shopping basket and beer sales. As it turned out in the weeks post childbirth it is often the male who is dispatched to the shops, which results in an element of randomness to shopping baskets. The increase in beer sales was a temporary phenomenon as after a few weeks the shopper reverted to her former self. What was apparent to the shopper marketing folk at Tesco was that as beer is bought quite generically most of the time…i.e. it’s always Carlsberg, or always Heineken (as to be quite honest as long as there is beer in the fridge at home, men tend not to be that picky), there was a major opportunity for brand switching during the 2-3 period after nappies started appearing in shopping baskets. Apparently, the smart folks who sell beer in Tesco started running beer promotions in the nappy aisle, resulting in switching patterns that were of significant value to the beer retailers who’s product they were trafficking.
The opportunity that “big data” presents to marketers is profound, and there is clearly a fine line between personalising a marketing approach and breaching common decency and privacy laws. The opportunity insightful data mining presents is in mass personalisation - customising advertising to limit the waste of spend and to maximise the likelihood of encouraging certain behaviours.
Google manages this at scale - if you search for “hairdressers in Clapham” it probably means that you are interested in the services of a hairdresser in Clapham. The search itself pre-selects the searcher into a category of buyer whos likelihood of purchase is exponentially higher. That is incredibly valuable, as Google’s market cap would attest to. As the FT calculator shows, you can acquire this data from 3rd party sources and often relatively cheaply – but Google owns the bazooka; both the data generator and the advertising platform.