Brian Kilcourse
Through a special arrangement, what follows is a summary of an article from Retail Paradox, RSR Research’s weekly analysis on emerging issues facing retailers, presented here for discussion.
A recent RSR survey found half of retailers had implemented capabilities related to capturing and analyzing "Big Data while less than a quarter claimed to be “satisfied” with what they had implemented.
So are retailers just in the very early days when it comes to truly leveraging non-transactional data or just too slow to change?
Predictive analytics represent a huge leap forward because it takes into consideration not only internal transactional data but path-to-purchase and social data as well as exogenous data like weather, competitive, consumer psychographic profile, calendared events (such as concerts or sporting events), and manufacturer and supply chain data.
Consumers want more relevance, and that also means not slogging through mountains of merchandise they don’t want to get to the items they do want. That’s what localization of the offer is all about.
But one-on-one marketing isn’t the right answer for everyone. Retailers need to answer these questions:
- What level of “intimacy” is needed to know what you need to know to be relevant? The granularity of customer-specific data needed to make a highly relevant offer is closely related to the specificity of the need (for example, offering basic commodities doesn’t require much customer specificity);
- What level of relevance is needed to be relevant? This relates to the granularity of the offer itself. Extreme localization isn’t necessary for every brand;
- How much data do you really need? Or how much analytical sophistication do you need to have to apply what you know to be relevant to customers?