Identifying consumer purchase trends through social data
We believe marketing is effective when it focuses on actual behaviours – the things we all do, like it or not, everyday. Social and digital data sets can often (but not always) allow us to identify these due to the scale and speed with which they can be gathered.
So, it was with a degree of satisfaction (OK, a lot of smugness), that we read ONS’s inflation basket update this week. For those unfamiliar, ONS is the national stats body for the UK, and they run a 700 item strong basket, which is intended to be reflective of UK household consumer spending. Prices in that basket are then used to calculate inflation. Every year the basket’s composition is updated to reflect changing household purchasing patterns. It is one of the most accurate guides to what the UK is really buying, and the annual updates provide a snappy barometer of what’s rising and falling in wider consumer popularity.
This year (2017) saw gin, cycling helmets and non-dairy milks (e.g. almond, soy) enter the basket. Or, in other words, items which directly confirm the trends we’d previously identified through social data (veganism, cycling, gin).
An important caveat to our prescience is that we aren’t claiming our research predicted a trend through social data (although that is sometimes possible) – but identified a purchasing trend which was underway through a parallel series of behavioural data (social content creation and/or engagement which meets certain patterns).
This work demonstrates the potential to use consumer social behaviour to identify and interact with realtime purchase shifts. The pressure is now somewhat ‘on’ for the trends for the remainder of 2017 we identify, having secured a 100% accuracy record in Q1…