What we share and reveal about ourselves, either consciously through social media or through our browsing habits all contributes to our digital fingerprint – a fingerprint that is then used to categorise us into ‘buckets’ for targeting of marketing activity.
this fingerprint is constructed is always under scrutiny – with a balance of
user privacy and the needs of the publisher to generate revenue from their content
in constant tension.
the announcements from Mozilla around 3rd party cookies has
refocused people on this topic and how the necessary profiling of people to
deliver relevant messages needs to move on from the current methods.
use of ‘public’ data to infer gender, brand preference and age is one area of
opportunity – but really what can you infer from this freely available information
– quite a lot it would seem.
research from the University of Cambridge and Microsoft using Facebook ‘likes’ has
been able to correlate ‘likes’ to attributes such as political and sexual orientation,
as well as intellect and gender.
data from 58,000 volunteers who provided their Facebook Likes, detailed
demographic proﬁles, and the results of several psychometric tests to build
models analysts were able predict with high probability which ‘buckets’.
example, users who “liked” Thunderstorms and Curly fries were predicted to be
of higher intelligence than those who showed affinity towards Harley Davidson
its own it’s application is limited, however if used in combination with others
methods of tracking, such as context / semantics and device finger-printing may
actually offer a more robust solution (over cookies) to the whole challenge of
delivering relevant marketing to users.
research : here