This article outlines:
The three numbers that drive restaurant sales
What the highest-performing brands do differently
Where AI fits today
More than 100 years ago, E. I. du Pont de Nemours and Company, now known simply as DuPont, began breaking its most important financial metric, return on investment, into two parts: net profit margin ✕ asset turnover. While the math is simple, the key insight is that an operator can't manage "return" directly. They can manage its two drivers: margin and turnover.
Today, restaurant operators have an ever-expanding set of reports, dashboards, and KPIs. Now more than ever, it's critical to go back to the basics and focus on the three numbers that drive sales: number of guests ✕ visit frequency ✕ average check. A recent survey of 150 restaurant leaders by Olo and Restaurant Dive's Studio by Informa TechTarget shows what the highest-performing brands do on each.
Step 1: Build a baseline you can trust
"What gets measured gets managed" may be a management cliché, but our survey backs it up. Among brands extremely confident in measuring visit frequency, 91% say it improved over the past year, compared with 46% of less-confident brands. The same pattern held for guest acquisition and average check. Yet nearly four in 10 leaders say data spread across systems makes it hard to see guest behavior, and another 20% still rely on manual reports and spreadsheets.
With a guest data foundation in place, start with five questions:
- How many unique guests ordered in the last 12 months?
- How many times a year does your average guest order?
- How many of your guests visited only once last year?
- What share of first-time guests order again within 90, 180, and 360 days?
- How many guests were active last year but aren't now?
Context matters, because category and service model influence guest behavior. Starbucks CEO Brian Niccol said in April 2026 that a growing number of customers visit four or more times a week, which works out to 200+ times per year. In contrast, one industry estimate puts the average guest at about 1.3 visits a year to a given hospitality venue.
Step 2: Pull the right levers
Once you know where you stand, the next move is acting on it. Here's what that looks like across all three metrics.
Guests: Make first-timers recognizable. Nearly two-thirds of brands keep fewer than one in five first-time guests past 90 days. Surveyed brands actively running loyalty and win-back programs were nearly three times as likely to beat that mark.
Frequency: Act when behavior changes. Surveyed brands that improved frequency were more than twice as likely to treat it as a priority metric (46% vs. 18%). Nearly 80% of brands reach out when a guest's visits drop below that guest's usual pattern, which only works if you know your own guests rather than an industry average.
Check: Know your guests. Our survey didn't find a one-size-fits-all tactic for building check, but guest data helps. It makes cross-sell recommendations more relevant, and it shows where you can ease up on loyalty promotions, which reduces discounting and raises net check.
Step 3: Execute, measure, learn, repeat
First-party digital channels offer a unique level of guest visibility. Take advantage of this increased guest data by building your baseline, identifying an opportunity, running a test, and measuring the result. Keep what works and drop what doesn't.
Where AI fits
Nearly half of leaders (47%) haven’t yet found the right use case for AI, and 45% struggle to connect it to existing systems. When looking to apply AI to drive sales growth, connect it to the three key metrics: use AI to identify at-risk guests, flag when a regular's pattern changes, and recommend what a guest is likely to add to their basket.
The data and tools will keep multiplying, but the formula won't change. Just like DuPont more than a century ago, break your goal into the drivers you can manage—guests, frequency, and check—and focus your effort where the gap is biggest.
Get the full picture
These are just the highlights. The full report breaks down all three metrics in detail, including the complete benchmarking data on loyalty and win-back tactics, the behaviors that separate brands catching guest drop-off early, and more on where AI is (and isn't) paying off yet.
