For restaurants, key data comes in all sizes

This past Thursday, I had the pleasure of speaking on the Restaurant Technology panel at the 33rd Annual Piper Jaffray Consumer Conference at the New York Palace Hotel. The two-day event was filled with inspiring presentations and Q&A sessions by retail and restaurant industry CEOs and CFOs, who had committed to memory an impressive set of facts and figures about their concepts' daypart mix, average unit volume, cash on cash return and so on. One concept that came up in nearly every session was how each concept was using "big data" to optimize its financial performance.

By the time the question of "big data" came up in my panel, I was ready to change the conversation.

"We spend so much time thinking about big data," I said. "I think it's time that we focus on little data."

Of course, I didn't mean to offend. But the power of all data is the combination of sizes.

Operators can explain how traffic patterns, weather patterns and sales patterns turn into actionable insights. They can rattle off regional-level data, store-level data and even transaction-level data. But I'm shocked by how little restaurants know about their customers. Long ago, the proprietor of a restaurant could recognize a loyal customer's face when he or she walked in the front door, call her by name, and maybe pour his favorite drink before he sat down at the bar (cue the intro music from Cheers).

But as restaurant chains have scaled to the point that the proprietor is speaking to investors at finance conferences and not tending the bar, the focus has shifted away from the individual customer. Sure, restaurant-level staff might know Norm or Diane, but operators can't access that information to make chain-level decisions — like they can with big data. Or can they? Do we know Diane only comes in for breakfast? Or that Norm stops by every night at 5 p.m. and orders the same sandwich to go? In some cases, the answer is yes.

When customers create mobile ordering accounts and place orders from their smartphones rather than an anonymous point-of-sale terminal, every order is logged back to the customer's account. This type of "little data" provides savvy operators with actionable insights to better understand and engage their new and loyal customers. For instance, a chief marketing officer can view mobile ordering records, find customers who have never visited one of their stores during the breakfast daypart and send them a coupon for a free breakfast sandwich, without throwing away marketing dollars on existing breakfast customers. That customer might decide that breakfast sandwich is the best way to start their day — and come back for more. Or breakfast may be inconvenient for them, but this simple, personal communication earns their respect that your brand appreciates their business.

Either way, the operator has an opportunity to reward a loyal customer, advertise a second daypart to a frequent user and, potentially, increase check averages. This is the power of "little data."

The real gold from all this mining comes from the combination of big and little. Just look at Amazon.com's "Recommended for You" and "Better Together" features. Both are seemingly simple suggestions made during the flow of a typical transaction on the site. But behind the scenes is a powerful combination of individual customer data and "big" data on customer buying trends and preferences. First, little data tells Amazon's algorithm who you are and what you like by aggregating the items purchased in the past and what you are searching for now. Then big data takes over, analyzing other customers who share your preferences, comparing that to what you are NOT about to buy, and encouraging you to buy it. The result is a higher likelihood of an incremental purchase, driving extra revenue and profit.

The bottom line: For restaurant CMOs, CFOs and CEOs who strive to sell more food to more people more often, little data is a big opportunity.