Most customer data tells you something useful, such as location, gender or income – all of which could signal a customer is a good target for marketing. But intent data gives you the most useful information of all: confirmation that somebody really is likely to buy your product.
Intent data is simply any information about a customer displaying an intention to buy, though the intensity of that intention can vary. Intent data might range from a new sign-up to a mailing list, to a customer putting an item in an online shopping basket but not checking out. In nearly every case it’s clear their interest has already been won, and it’s just a case of overcoming remaining barriers to purchase.
As a general rule, the more direct and specific the intent data, the more useful it is. Purchasing a mailing list of everyone in Kent who has ever bought a lawnmower is certainly a good starting point for a local company selling replacement blades.
However, if that company had an e-mail newsletter and could then use visitor data to find out which people on the list have looked at which products on the site, it could put together very specific mailouts to tempt customers into making the purchase. Of course, it’s vital to comply with all relevant data processing regulations – not just to avoid legal problems, but to avoid upsetting and losing the very would-be customers just identified.
Location analytics can also be used to visualise intent data and gain valuable insight. For example, cross-referencing sales and intent data might reveal that a particular product line sells well in London; sells poorly in Newcastle but has lots of online visibility; and neither sells nor attracts interest in Glasgow. That could indicate the product appeals in Newcastle but the price is too high, meaning a local advertising campaign with a discount code could pay dividends.