When First Watch partnered with wait list management platform NoWait last month, the restaurant company was making a move more strategic than many in the industry realized.

"We have about 120 restaurants, and like any marketer, the more I can know about my customers, the better," says Chris Tomasso, chief marketing officer at breakfast, brunch, and lunch brand First Watch. "The restaurant industry is very transactional, and it's hard to get data on your customers. We've been working with Zipscene for a long time on a number of different points, and when they presented us this opportunity on this platform, it fell right in line with what we were looking for."

The platform Tomasso is referencing is zDMP, launched last month by Zipscene, a technology company that uses data to understand guest dining habits and help restaurants market better. zDMP is tying together all of First Watch's disparate technology vendors—Fishbowl for email marketing, NCR for point-of-sale, and NoWait for its wait list—to start assembling profiles of each customer, using customer data that is scattered across the varied platforms.

"The idea is that a lot of restaurants are employing multiple technology vendors to meet whatever their customers' needs are," says Sameer Mungur, founder and CEO of Zipscene. "Unfortunately, as they're doing that, they're building data silos about their customer. zDMP's role is to pull all those data pieces together from separate systems and construct that profile for the first time. Some of our clients have never really seen that holistic profile."

Zipscene's clients include First Watch and Hooters, which both aim to reach individuals in a personalized format.

Reaching Customers on an Individual Level

"For us, a lot of times it starts with: Does the restaurant even have systems in place that are capturing data today?" Mungur says. "In most cases, the answer is no."

That was the case with First Watch, which had been working with Zipscene as an ongoing consultant for more than three years, Tomasso says, but wanted to create a more solid foundation from a POS and IT standpoint, such as the NoWait partnership, before engaging Zipscene for this specific service.

"We don't take reservations, and our customer feedback over the years had told us that our customers would come more if the wait was more manageable," Tomasso says. "Now, whenever a customer utilizes the NoWait system to get on our wait list, we get a cell phone number. Likewise, with our email marketing campaign, our loyalty club, which is run through Fishbowl, we have email addresses, birthdays, and all kinds of information."

What First Watch desires is the ability to coalesce the information from Fishbowl and NoWait—and, ultimately, its online ordering and loyalty vendors—so that no matter which door customers come through to connect with the brand, even if it's more than one platform, First Watch can tie it to that person's profile and begin to understand how that individual uses the brand, when they use it, their frequency, and their likes.

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"The ultimate goal of all of this is to go from mass marketing to customized marketing," Tomasso says, indicating a service that would go beyond just local store marketing. "That's really what we're doing all this for, is to get to a point where you can market to customers in a very personal and personalized way—text, email, or any way they've asked us to communicate with them—that lets them know we know why they use us, how they use us, and what's important to them."

The next step at First Watch, Mungur says, will be for Zipscene to take the knowledge and begin altering First Watch's campaigning system, beginning with more segmented email campaigns.

With Hooters, Zipscene acted as a general contractor and advisor, helping the brand source the technology solutions it needed to start building data sets necessary for Zipscene to make an impact. Mungur says Zipscene helped Hooters find a loyalty provider that integrated with its POS, and the wings brand is now amassing the six to nine months of historical data it needs before Zipscene can begin a campaigning effort.

A Bigger Picture of One Consumer

As Zipscene draws more restaurants into zDMP, it is developing an understanding of consumers' buying behavior across all types of eateries, whether it's quick- or full-service, to aggregate a granular understanding of buying behavior across the industry. This breaks down into how many dining occasions a person has at a specific restaurant, how often and when he is likely to patronize a quick-serve versus a full-service restaurant, and more.

"If I am a casual-dining brand and I only see that person in my restaurant three times a year, but that customer eats a lot more at some kind of quick-serve or fast-casual restaurant, then there's knowledge to be imparted from those other locations," Mungur says.

"The [casual] restaurant would have to see them over a very long period of time—years—before you can begin predicting their behavior. So in a way, we're compressing that cycle for any new brand. A lot of the growing brands that join our platform are young and don't have very large databases, so for them it's gaining knowledge about their customers very quickly."

The idea beyond that is to begin predicting when the individual will have his next dining occasion, and then talking to him in a relevant manner, whether that's through advertising or the restaurant's customer-relationship management systems.

To do that, Zipscene ties its first-party data in with data collected from third-party providers such as Axiom, which gathers different demographic and psychographic information about an individual beyond the restaurant industry, including purchasing behavior in retail.

Mungur envisions that as zDMP matures, it will begin impacting the first step in the customer’s process to find a restaurant to eat at: search engines such as Google and Yelp. The ability to impact individual marketing using those engines is a big-picture plan for Zipscene.

"We think that's interesting for a lot of restaurants," Mungur says. "Today, the process of doing a lot of search engine advertising is very manual and is not informed by that restaurant's customer data. And if it could be—it could be a pretty powerful too."

By Sonya Chudgar