When it comes right down to it, there are only three ways to increase same-store revenues: get more customers, get existing customers to return more often, or get them to spend more on each visit either by selling them more product or by charging more for what they are already buying. Anything else is just a variation on one of those basic themes.
Sales promotion has long been used to drive these sorts of customer behaviors. Until recently, however, a challenge has been that it is often hard to target promotions to specific customers in order to maximize response and minimize waste. Promoting blindly can be costly. A coupon in the newspaper or dropped to a mail route may reach new prospects, but also risks discounting existing customers who would have been happy to pay full fare. These aren’t the results that stores want or need.
But what if you had the ability to identify and segment customers based on traits such as how often they visit your location, how long they stay, or how much they spend while they’re there? And what if you could target specific customers and trigger promotions automatically based on such behaviors? Three recent advances have made this easy for single- and multi-location stores alike, and explain the current surge in location-based customer analytics and marketing.
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