When discussing the role mobile plays in the retail experience, one word crops up again and again – omnichannel. Most retailers now realise that mobile, ‘big web’ and physical stores don’t exist in isolation. Customers research online and buy in store, just as they research and compare prices on their phone in store, before deciding whether to buy there and then or go somewhere else, digitally or physically, to get the item cheaper.
RichRelevance makes its money by trying to tie all this together to present shoppers with relevant recommendations, based on the data retailers hold on their customers. It has pretty good credentials – the company was formed in 2006 by David Selinger, a former head of R&D within Amazon’s personalisation team.
Since then, the company has worked with over 175 multinational companies to create a data-centric, single view of the shopper, with the aim of delivering the most relevant experiences across web, mobile and in store. Customers include Marks & Spencer, Tesco and John Lewis, and the company claims to have generated over $10bn in sales for its clients, primarily by offering them relevant recommendations, in a very Amazon-like way, when they are shopping online or using the retailer’s app.
“We help retailers analyse the data they have on customers, from their loyalty card to past purchases to returns, to which stores they like to visit, so that we can present them with a personalised ability to discover the right products,” explains chief marketing officer, Diane Kegley.
A few weeks ago, the company extended its offering with the launch of Relevance in Store, describing it as “the next era of data-driven retail”. The release announcing the launch spoke of the shopper being greeted at the store entrance “with relevant offers, promotions and notifications”. Elsewhere, it explained how “a shopper’s own behaviour combines with online and offline data to expose the most relevant inventory in real time, creating an ‘endless aisle’ of product and offers.”
I put it to Kegley that this sort of interaction between the retailer and the shopper could very quickly become very annoying for the consumer if not handled sensitively.
“The important thing is to look at the layout of the store and work out where are the right places to be able to have that kind of interaction,” she says. “What is the retailer trying to do in terms of creating a personalised, curated experience? We will be recommending no more than the store entrance, exit, through the associate app and maybe one additional placement, so for a pharmacy, it might be a message to say that your prescription is ready. Something that’s useful for the shopper.
“We are working with a fashion retailer where the consumer has a ‘Dressing Room’ app on their phone and they can use it to ask the sales assistant to bring them additional merchandise to try on, based on what is being presented to them on the phone. The retailers we are working with want to do proofs of concept to find out what works and learn from it. They are not looking to bite off more than they can chew. It’s about using the data they hold to develop an in-store solution that does not offend the consumer, but instead, delivers appropriate messaging and exposure to additional inventory beyond what is in the store. Every brand has a different take on it.”
For many retailers, Kegley adds, gathering data on what a customer does in store is the Holy Grail. “The in-store data completes the picture,” she says. “If you can develop a customer map of all the data points on a consumer, you can build a profile on where they shop and what they have bought and use this in real time to deliver a relevant experience, complete with predictive recommendations about what else they might like to buy.”
The trick, of course, is to use this information responsibly. For those retailers that get it right, there is the potential for a win-win of happy customers and increased sales. For those that can’t resist the opportunity to spam, the prospects look somewhat different.