These are among the names given to Looking Glass' 27 Cohorts, or population segments, which separate the U.S. population into categories that bundle people with similar lifestyle characteristics. Looking Glass applied Cohorts data to Proflowers' 500,000-name house file to more clearly define its customer base and identify its "best customers"-those frequent buyers and high spenders to whom it would send customized e-mail messages.
"Their goals were really to move into more personalized marketing to elevate response and speak to customers more relevantly," said Mike Fitzpatrick, director of business development at Denver-based Looking Glass. "Because we've been working with Cohorts successfully in traditional direct marketing applications for years, we have proved time and again with different types of clients that consumers who are similar in their demographics and lifestyles are going to be similar in their other types of consumer behavior if you speak to them as relevant members of a given segment."
A little more than a month after Looking Glass segmented Pro-flowers' database, the online seller of flowers began sending out eight unique e-mail versions, each with distinct copy to appeal to different customer groups.
"You see a lot more people doing e-mail marketing," said Chris d'Eon, VP-marketing for retention at Proflowers. "We felt that to break through the noise we needed more compelling copy."
A message to the "Mary Beth" Cohort, for example, representing the educated working woman, reads like an e-mail from a friend explaining how happy the friend's mother was when she recently received flowers from the e-mail writer.
The personalized messages garnered a 35% higher response than the the non-customized messages previously sent and added an average of $1.44 to each order. "I was looking for a 20% lift of response," Mr. d'Eon said. "It surpassed my expectations."
Although Proflowers is a pure-play Internet company, its marketing philosophy hinges on traditional direct marketing principles of testing a communications strategy against a control and measuring response rates. This policy led to its partnership with Looking Glass' Cohorts system, Mr. d'Eon said. "I was looking for something that was understandable, that was easily implemented and that when I was done, I knew it worked."