The Math Problem With Digital Ad Targeting
https://www.linkedin.com/pulse/math-problem-digital-ad-targeting-john-andrews
Digital advertising has a glaring problem, at scale, there is little to no difference in data sets, resulting in increasingly homogenous performance for advertisers. To put it another way, brands relying on some magical targeting data have no advantage over their competitors. Take massive amounts of 'Big Data', crunch it up, use it to target people who are likely buyers, non-buyers (so give them a better deal), competitive buyers, etc. etc. and you win right? Nope, every brand has similar access to the same third party data, any advantages are short lived as they are copied by competitors; it's just simple math.
If you don’t believe me, consider the ridiculousness that is the digital ad market today. Fully one half of digital advertising is never seen by a human. One half. And yet, digital spending continues to expand at a blistering pace. Compound that with the fact that the problem is getting worse, not better and the costs are increasing. It’s the ultimate head-scratcher for and industry, lower quality and higher prices. How is this even possible? The answer lies in capacity. There is simply too much advertising chasing too little attention. As spending pours into digital advertising, the problem simply gets worse. Math strikes again, a new solution is needed.
Shoppers are only occasionally in 'buy' mode. Constantly bombarding them with conversion messaging based simply on inferred data reeks of desperation.
What if marketers could add a new data set into the mix to better understand where shoppers are along the path to purchase. Instead of spamming people with endless messaging about products that aren’t wanted, needed or relevant, they could add value by offering messaging at known points along the shoppers journey. Thanks to a powerful new data source created by IRI, this is now possible.
Through its relationships with regional and national retailers, IRI has assembled a behavioral data stream based on a combination of loyalty cards, point-of-sale and shopper panel data to create the largest database of actual shopper data. Using this dataset, marketer's can break free from the declining effectiveness of digital marketing by understanding where shoppers are along the path to purchase. This approach can also significantly reduce the crushing noise level that is not only interrupting shoppers needlessly but also turning them against social media platforms and brands. What's more, it works! This approach offers IRI clients 3-4 times sales uplift and up to 70% improvement on return on advertising spend.
