Putting loyalty to work

As computer modeling and mapping systems become more advanced, flyer distribution is going from scattershot to pinpoint targeting, right down to postal codes of only 10 to 15 houses.
And as the mapping software gets more advanced, a whole new wealth of raw information is finding its way into the hands of flyer distribution consultants, thanks to loyalty programs at retailers such as Zellers, A&P and Shoppers Drug Mart.

As computer modeling and mapping systems become more advanced, flyer distribution is going from scattershot to pinpoint targeting, right down to postal codes of only 10 to 15 houses.

And as the mapping software gets more advanced, a whole new wealth of raw information is finding its way into the hands of flyer distribution consultants, thanks to loyalty programs at retailers such as Zellers, A&P and Shoppers Drug Mart.

Now marketers can proceed one of two ways when they sit down to plot out what geographical areas would be most receptive to a particular flyer.

The first method makes use of detailed purchase data gleaned through Air Miles and other loyalty programs. This method basically involves correlating past purchases in categories relevant to the flyer with geographic areas so that flyers can be sent only to postal codes that have demonstrated a willingness to buy similar products in the past.

It’s a ‘birds of a feather flock together philosophy,’ says Steve Acland, VP of client services at Toronto-based flyer media manager Geomedia. ‘It’s using sales analysis in order to determine where your high sales penetrations are within every geographic market.’

The second distribution method is used when there is no customer data available, or to widen a flyer’s distribution into likely pockets of new customers.

In that case, distributors turn to firms such as Toronto-based Generation 5, which is essentially a postal code-level micro marketing database firm which has compiled comprehensive consumer databases through customer surveys, Statistics Canada information, and other sources. With this ‘predictive modeling’ or ‘outreach’ route, a percentage of probability for every product or store can be determined.

Acland cites Canadian Tire as an example. Say the retailer wants to sell a seasonal product category such as hockey equipment and would like to send out flyers to promote it.

Through its own database, it can find out regionally what areas account for the top 20% of past Canadian Tire hockey equipment purchases.

From there it can move into predictive modeling by asking Generation 5 to find out what geographic areas represent particularly high hockey equipment purchases or ownership in general.

According to Geomedia president Peter Martin predictive modeling is the older, more tried-and-true method of flyer distribution. It has only been relatively recently that chains have developed comprehensive proprietary customer databases. And using those databases for flyer distribution requires even more advanced computing power and software than addressed mail because of the extra step of feeding the raw data into geographic information systems (GIS).

This ability to link spending habits with definable geographic areas has even caught the eye of some upscale companies, such as Harry Rosen, which is considering using flyers or other forms of unaddressed ad mail.

But technology alone doesn’t change long-time distribution habits. ‘There’s more awareness now of how important it is to bore down to those smaller levels of geography and look at finite areas that are postal codes of only 15 to 20 houses,’ Acland says. ‘It’s the competitive nature of the world – everyone wants to get more bang for their buck.’ AV