Fred LeFranc, CEO of LT Acquisition Corp., faced the task of turning around Louise’s Trattorria after buying the bankrupt restaurant chain in late 1997. (See Part 1.)
Shortly thereafter he encountered Gazelle Systems at a trade show and was impressed with the company’s data mining tools. Since 85 percent of Louise’s business was done via credit card, LeFranc commissioned Gazelle to analyze six months of the chain’s point-of-sale data.
What he found was almost a complete surprise: a sizable majority of Louise’s top 500 customers were single mothers, with children on average between the ages of 10 and 13. They were also college educated and well traveled, owned 1.4 cars, and liked fine wine.
“The biggest surprise was these people had money,” LeFranc said. “They could afford to pay for quality.”
The Gazelle reports also told LeFranc that he was losing new customers at too high a rate; that his regular customers weren’t coming in as often as they should; and
that he needed to build more local patronage.
These insights set off a course of changes. Under LeFranc’s guidance, Louise’s added more expensive vintages to its wine list and streamlined its menu, trading up
many hearty, old-world Italian dishes for healthier vegetarian fare while adding a seafood menu with slightly higher prices. Each restaurant in the chain was remodeled
in a more contemporary and lighter atmosphere.
With its new look in place, LeFranc began to tackle the frequency and churn problems. The CEO knew in order to deliver more customer intimacy, he needed to
build a database that went far beyond the top 500 patrons identified by Gazelle. To do that, he began instituting marketing and rewards programs that recognized
people for their loyalty — and encouraged them to provide personal data.
Birthday Clubs and Raffles
For example, Louise’s began instituting birthday clubs, with enlistees receiving a mailed coupon good for a free dinner. He raffled off a trip to Italy, worth around
$7,000, and in that one effort collected over 25,000 names. A couple of years into the effort, Louise’s customer database has gone from zero to 100,000 names.
“Once you have a database, you can communicate directly to your customers, and it’s easier to get them to come back if they already know who you are,” LeFranc
said. Being able to target direct mail to a set of known customers also makes efficient use of marketing dollars, he added.
To increase frequency, Louise’s uses the database to offer special values to repeat customers. Top patrons get free certificates during the holiday season and
newsletters that announce new specials — such as one introducing the new seafood section (complete with recipes) and another that emphasized upgraded take-out
Since Gazelle’s initial analysis, Louise’s has run a series of “Gaz Reports” every six months to gauge progress. So far, the results have been impressive. From a 10
percent decline in annual sales before LeFranc took over, the chain had a 9.5 percent bump in revenues in 2000, to $18 million. The frequency rate for regular
customers has improved from 2 visits a month to 3.5. And average check size has increased from $12.50 to $16 a dinner.
“We’ve been able to introduce higher priced entrees that people will pay for, because it’s not about price, its about value,” LeFranc said.
The CEO said he’s confident he would have been able to make the changes that led to Louise’s success without the Gazelle data mining initiative — but not nearly in
the same time frame.
“We would have eventually found our way, but this was essential for avoiding mistakes that would have been made by making decisions in a vacuum,” he said.
In the three years since it implemented the Gazelle data mining service, Louise’s has made strides in addressing internal operations and infrastructure problems while
improving marketing and positioning. But LeFranc said the chain can’t slow down: “We’re on solid ground now, but it doesn’t mean we’ll win the marathon
The most important thing, LeFranc said, is that management is confident that its higher end atmosphere and highbrow menu correspond much more closely to the
wants of its clientele — including some of Hollywood’s finest.
Beth Stackpole is a freelance writer based in Newbury, Mass. She can be reached at [email protected]