If you’ve just bought yourself a brand new coffee-maker, being besieged with ads for another one can come across as creepy at worst, thoughtless at best. The brilliant retail customer experience you may have received when considering and buying that coffee machine is shattered with the realisation that the brand doesn’t know you from Adam after all. Or they just want to use you to tell Adam to also get a coffee-maker.
Recognising when the customer is telling you they want to buy
Not taking note of situations like this is wasted advertising spend for the brand and a poor experience for the customer. The challenge for retailers is recognition; identifying when the consumer is likely to be in the market for a coffee maker in the first place – and so place an increased focus on search advertising because that’s when the customer is flagging up their intent to buy.
Using a knowledge-based retail recognition approach
It’s not only buying cycle changes that retailers need to be aware of. Customers get married, change where they live, so there are data quality issues too. Sources of data have increased with third-party data and collaborative targeting. The way retailers identify the customer has also changed. Consumers have multiple phone numbers and email addresses and the rate at which we communicate with them has increased, for some, to every week if not every day. Customer bases have also become increasingly multinational.
So maybe Acxiom knows that David Jones from 12 Cherry Tree Lane, and a valued Joe Bloggs customer, is the same David Jones who changed address two years ago, but Joe Bloggs doesn’t because he never told them. Knowledge-based recognition would bring those two records together so that a transaction David made three years ago online can be connected with the store purchase he’ll make next week, listing his current address.
Considering use of near-field communications or beacon technology
Beacon retail recognition technology can give a retailer a lot of information about a customer; how they physically move around the store, what products they engage with.
There is a value exchange to be taken into consideration here so you’re offering the customer an improved experience in exchange for something that on its own might be perceived as a little intrusive; thought this is likely to be something that becomes increasingly accepted.
An example is one leading clothing retailer, who is trialling near-field devices on garments and hangers; taking note of what garments a shopper is taking into the fitting room and then altering the displays on the fitting room accordingly. The challenge to the retailer will be how to link that data back to an ensuing online experience. Recognising the online and offline customer as one on the same enables the retailer to augment the shopping experience but it’s not quite happening yet. Things like data-sharing (such as wishlists) ahead of a store visit are ripe for retailers to use more efficiently.
Taking a leaf out of Heathrow’s book
Heathrow Airport is the largest retail site in Europe by some measures. It has as many shops in it as Kent shopping mall Bluewater and a higher spend. However, shoppers relate to it in a very different way. Shoppers arrive because they are taking or have taken a flight somewhere. Most flights are booked in advance so there is lots of opportunity to find out who the customers are. It’s even possible to know what train they are arriving on if they’ve purchased a Heathrow Express ticket. But you don’t want to waste marketing on a businessperson who has 20 minutes to spare; you want to offer them a Costa voucher, and vice-versa, send a family of 4 with time to spare a meal, or entertainment offer. So, with help from Acxiom, beacon technology and Adobe Marketing Cloud, the airport is experimenting with retail recognition technology to see how different passengers move around the space by “helping” them find their way around the airport.