The income gap in the US has risen dramatically in the last 20 years. In fact, the disparity between the top and bottom households is now at an alarming level. Ray Dalio, the founder of Bridgewater Associates, shared a chart his LinkedIn post which analyzes the share of US household wealth by income level. To put it in perspective, he showed that the top 0.1% of households now hold the same amount of wealth as the bottom 90%, a level that is akin to the wealth gap in the great depression of 1935 to 1940. Full article is here: http://bit.ly/premexio.
Rather than focus on the socio-political-economic policy considerations, it is important to understand how wealth or lack thereof can inform our marketing efforts. Digital marketing has an unprecedented ability to target based on highly detailed audience attributes from gender, to location, to age, to content affinity and drumroll....wealth. The problem is that most media buying platforms/DSPs/trading desks are not configured to ingest raw attributes and use them in their machine learning algorithms. Some platforms allow for modest rules-based optimization and this is a good start to a fully open and programmable bidder.
In the case of marketing to the affluent, high net worth and ultra affluent, Premex can use our patented WealthGraph(SM) data to inform your media and creative optimization. Imagine if 90% of your spend could be saved, allowing you to bid higher for users that can afford your products. That is precisely what we are offering brands that have been on the sidelines of programmatic for too long.