By analysing such big data, retailers can gain insights into customer behavior and prepare marketing programmes to strengthen relationships with loyal customers (and turn occasional shoppers into loyal buyers).
A McKinsey study from 2011 suggests the enormous potential of mining big data: 'We estimate that a retailer using big data to the full has the potential to increase its operating margin by more than 60 percent'.
Amazon, in fact, has boosted sales by analysing big data to present customers with product recommendations based on previous purchases and browsing history. Customers benefit because the shopping experience is tailored to their needs and preferences.
Waitrose and John Lewis, part of the same corporate entity, now have a joint customer insight director to help mine big data for actionable information. 'Customer insight is an increasingly sophisticated area and a central part of modern retailing', explains the group chairman. (At left, the first cobranded ads from these two stores.)
A Harvard Business Review blog post observes that smaller retailers may be unable to afford data collection and analysis on this level, possibly putting them at a competitive disadvantage. On the other hand, there's an app for that--big data analysis, I mean. Of course, this is oversimplification of a complex situation, but the point is that customers have more power than at any time in the past, so retailers of all sizes must be ready to satisfy shoppers' needs or risk losing relevance and market share. Big data is only part of the solution, but it's a big part.
