Are you a red dot, a yellow dot, or a green dot?
You probably have no idea. But you may already be a dot on a marketer’s map, a sort of code used to judge how likely an advertising campaign is to appeal to you.
That was the case for a segment of Chatham, Ont.-based Union Gas Ltd.’s customers recently. They may not know what colour they are, but they received mailed offers tailored to their specific profiles. Behind this campaign were literal maps of neighbourhoods, with coloured dots that helped Union Gas approach people based on location-based information. And it paid off.
“Location, location, location” is no longer just a real estate mantra. While the ability to target customers with specialized offers has always been valuable to marketers, the availability of massive amounts of data, and the increasing ability to make sense of it, means that more and more, where you are is becoming a crucial part of knowing who you are.
Union Gas is required to offer a number of energy-saving programs, such as upgrading insulation or replacing an old furnace, every year and is compensated by the provincial energy board for the cost of those programs. However, figuring out which of its 1.4 million customers may be in the market for such services is a challenge.
Before, the company’s best strategy for reaching the low-income customers targeted for this particular energy conservation campaign, was to market to people in subsidized housing – hardly comprehensive. So it used data from a Toronto-based company that specializes in location-based targeting, DMTI Spatial, and cross-referenced details such as neighbourhood income levels, resident demographics, and the age and size of the homes. That information was coded onto maps, giving Union Gas a clear idea of which households to target.
“We just didn’t have that information available to us before,” said Jeff Okrucky, the company’s director of distribution marketing.
The typical response rate for one of these campaigns is about 1 per cent. The location-specific campaign increased that by 400 per cent on average.
“There’s been a wholesale change in the amount …of data available and the tools available to actually understand it. It’s turning that data into knowledge that is the biggest task,” Mr. Okrucky said.
In an age where we transmit data from devices in our pockets many times a day, using information such as postal code profiles, housing statistics, and demographics by district may seem like an old-fashioned marketing tactic. And it is. But the processing of that information is changing rapidly: the ability to sort through massive data sets, to cross-reference them, and create detailed targets, has accelerated.
“It really gets to the cloud computing capability. We do programs with all these data sets very quickly. And some of the data sets can be absolutely massive,” said Phil Kaszuba, vice-president and general manager at DMTI.
The company recently did a campaign for a client comprising billions of rows of data. On a traditional server would have taken close to a year to compute; it took about six days.
“The possibilities for data analysis have expanded exponentially,” said Martin Hayward, vice-president of global digital strategy with Montreal-based loyalty program provider Aimia Inc. “Go back 20 or 30 years, our great challenge was, if only we had more data. If only we could find things out quicker. Now, data is gushing in by the pipe-loads.”
Aimia commonly uses mapping to encourage members to use their loyalty programs more. For example, in multipartner plans such as Aeroplan (as opposed to a retailer-specific plan), “member engagement” grows if people shop in more partners’ stores. To address this, Aimia’s Nectar reward program in Italy used maps to find areas where members lived near partner stores, but weren’t doing much cross-partner shopping.
It then sent those members bonus offers to encourage them to visit a partner such as a supermarket or electronics retailer where Nectar points are given. Each mailer included a personalized map showing the location of the person’s house and nearby store locations. The campaign boosted coupon redemptions by 30 per cent.
The most exciting location data for Aimia, however, and for most marketers these days, comes from the mobile devices that can continually transmit GPS location as well as a raft of behavioural information about each individual.
“The data is living with each and every one of us in real time, in our mobile devices,” said Asif Khan, founder of the Toronto-based Location Based Marketing Association.
He was particularly impressed, for example, by a winter campaign run by Cadbury for its Halls cough drops in the U.S. It mapped data from the Centres for Disease Control on flu density, then sent offers for Halls to consumers passing near CVS pharmacies, Wal-Mart, and Walgreens locations in the geographic areas where they were most likely to be sick. When the flu index spiked, it sent out alerts in that area.
In the U.K., Nectar’s mobile app asks for permission to track users’ GPS location, in order to increase the relevance of offers it sends to them. The large grocery chain Sainsbury’s, which uses Nectar as its loyalty plan, can now offer extra points to shoppers the moment they are passing by a store.
The trick is to make this exchange of information valuable to the customer. The app allows users to limit what time of day they receive offers, as well as how close they need to be to a store for a message to be useful, as well as determine which stores they never want to hear from. This flexibility is key for Aimia – and for any marketer in the mobile age. If consumers see the incentive in sharing their mobile data, marketers can create a living map, speaking to those dots based on where they are, what they are doing, and what they may want or need.
“Customers will share their data with us because they know some benefit will accrue from it. It becomes much more of a two-way relationship,” Aimia’s Mr. Hayward said. “We are entering a new era of personalization.”