The conventional thinking about profiling online users is that Facebook (in particular) has enormous amounts of profile data about your tastes, while Amazon has equivalent quantities of data about your shopping habits.
While both are true to some extent, the reality is that your liking of cat videos and flirt-Liking work colleagues’ posts doesn’t amount to a heck of a lot, while Amazon’s knowledge of you is locked inside your re-orders of washing powder. Admittedly that might be a simplification…
Suffice it to say, a better scenario would be a platform that could look at all your actual purchasing behaviour (perhaps even start to make predictions about it?) and which was not locked inside the big social platforms or e-commerce giants? What if it was available to all publishers and content owners, and all the data, where users were
anonymized, got larger and larger as more and more publishers joined? Would this not free them of the shackles of Facebook/Amazon/Google, and the like?
It turns out just such as platform exists, and has emerged from left-field out of a hot new trend in online publishing.
So-called “Editorial commerce-related content” emerged from early commerce-related blogs like Wirecutter, but have quickly caught on amongst bigger publishers like Buzzfeed, who have realised that placing buy links inside content could be a way out of the declining world of online advertising. Indeed, even reverse-engineering shopping habits and over-laying that data inside an ad network has many untold possibilities.
The company spearheading this new approach is Skimlinks.
Better known for their platform which give publishers control of how affiliate schemes appear, this mid-stage startup has recently launched a new product aimed at mining the big data it has accumulated about users shopping habits, and make that available to all its publisher clients.