Brand advertising doesn’t have to exist in an accountability-free vacuum. According to panelists at a National Center for Database Marketing session in December, database analysis brings science to this largely artistic discipline.
Presenter Right Coast Marketing’s president Christine Anderson cited Quickbook, a service that arranges reservations for rooms in inexpensive hotels and that originally positioned itself as “America’s No. 1 hotel discounter.” Anderson believes Quickbook’s targeting of vacationing families in magazines such as Family Circle missed the mark.
Database analysis revealed that the service’s best customers were business travelers – or, more specifically, those employees responsible for reserving rooms for business travelers. But Quickbook’s ads had emphasized cheap rates, creating fears that a company executive – or even worse, a client – would be booked into a substandard hotel.
Armed with information gleaned from its best customers, Quickbook created an ad campaign (“For a great hotel at a great price”) that stressed the value of the service and attempted to reassure those making reservations.
Some database analysis can change a company’s marketing technique. One retailer, DSW Shoe Warehouse, was touting discounts in its ads. But the program was not meeting expectations for return on investment. Customers were able to sign up at the point of sale, so if they left their discount card home all they had to do was reregister. This created deduping headaches for the firm’s IT department. Additionally, the discounts were good only on clearance sales, not higher-priced merchandise.
DSW’s best customers, however, were insensitive to price; they really weren’t interested in clearance merchandise. In response, DSW set up a program “for people who love shoes” which de-emphasized instant discounts and highlighted longer-term rewards, such as discounts mailed to customers after certain spending levels had been met.
The creative changed as well, with warm-colored Valentine’s Day mailings encouraging “shoe lovers” to indulge in more shoes with less guilt.
Occasionally database analysis can completely change the audience a campaign targets. Amtrak’s Auto Train, which allows travelers to take their cars from Washington, DC to Orlando, FL, chose an audience that made reservations three or four months in advance – active senior males age 55 and older. As conventional wisdom held, they weren’t likely to ride longer distances.
Actually, Amtrak’s ad programs were geared to the wrong audience, at the wrong time, with the wrong focus. Auto Train customers were considerably older, with more than 60% over 65. Half of these seniors booked their fares less than a month in advance, and 12% already used the train for longer trips.
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