A Batch of Delicious Data
Tell us about this scrumptious company of yours.
In 1992, I started Fairytale Brownies with a childhood friend. Around high school we decided we wanted to start a business together. We brainstormed a bunch of ideas and settled on my mother’s brownies recipe. We started selling the brownies wholesale to coffee houses, street fairs, and farmers’ markets. It evolved into a mail-order business with a mailing list. Customers would sample brownies and would then decide to ship a batch for when they got home.
What challenges were you facing?
For one thing, we’ve evolved into a gift-giving business: Virtually every order is going to someone other than who ordered it—maybe 1 to 2 percent of orders are for self-consumption. We realized early we were having a lot of address corrections. With gifts, all things go wrong with address problems—the gift doesn’t get delivered or is late. And timelines are very important, especially with events such as birthdays, anniversaries, or Valentine’s Day. We’re now mailing some two and a half million catalogs for the year, and we do about 60 percent of our revenue in three weeks in December. Over time, we saw that the bad addresses add up—and as address-correction costs went up, we started chipping away at them from a manual perspective. We were getting on the Internet, checking addresses. Over time we started developing our own tool internally to validate addresses. We refined that over a few years, and we saw benefits immediately—correct addresses meant orders were delivered.
With addresses, we are pretty generous in terms of customer service. If a customer has a problem, we do whatever it takes to get it right—whether that means we reship or reorder. Each one isn’t that big of a deal, but it adds up. Then there’s the customer-satisfaction standpoint. If we can get that correction before billing, there are so many additional benefits—satisfied customers, less time on the phone with customer service, the receiver gets the brownies sooner.
Volume became the problem. There still had to be a human involved. We were only validating orders through the phone. We didn’t have a system to go back and match information every time and we weren’t catching all the wrong addresses.
After hearing about [Experian] QAS, we purchased the QAS Pro product and integrated it with Escalate, the mail-order software we use. With phone orders you get live address validation. The immediate benefit is that phone calls are shorter. QAS works as a drill-down so you don’t have to type in the whole address.
And the implementation process?
It was really easy. It’s a standalone application, so there was minimal set-up. Tech support was great. We have this unconditional guarantee: Our Fairytale promise says we will do anything it takes to fix a problem. It’s not only about the money or having to refund or reship or field customer service calls or emails, it’s just a lot more about confidence. Customers appreciate seeing, when they put in an address, if they entered it wrong. It’s an additional service to them. Do anything you can to prevent problems. Don’t give the customer a reason to call. They just want to be provided with as much information as possible with an order. We are now able to do that with automation.
SIDEBAR: 5 Fast Facts
How old is the initiative?
We started with QAS Pro a while ago—and added the Web version and the QAS Batch a year later.
Who was involved in the decision process?
An IT manager and I did the review.
Best idea?
We call it “The $100 Employee Policy.” It’s the idea that any employee can spend up to $100 of the company’s money to solve a customer problem. It allows customer service to resolve problems in the first
call without escalation. With us, $100 solves 99 percent of problems. And first-call resolution will bring the customer back.
Biggest surprise?
That there weren’t any bugs or any crashes! Normally, with any technology upgrade or enhancement, we assume things will go wrong—and plan for it. This solution really was plug-and-play.
Biggest CRM mistake?
Task-sharing. For a long time we thought, “Let’s have everyone do a bit of everything.” We found that, in the end, that doesn’t work too well. Now each person has a specific task and then we have a back-up person. We found that it was a lot better to develop experts in all those different fields rather than cross-training.
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