Somebody asked me a great question the other day: “What’s something you used to believe as a restaurant marketer that you no longer believe?”
It’s a great question because one of my defining traits is conviction. Once I believe something, it’s pretty hard to get me off it. But I’m also a student of the game, and I’m always willing to be shown a better way, even if it’s a way I created.
Here’s my answer, and you’re about to hear that conviction kick in. As an industry, we’ve been optimizing the wrong problem for a very long time. Now that I’ve seen a better way, it’s amazing how obvious it seems in hindsight.
You’ve probably seen the statistic hundreds of times that 70% to 80% of guests only ever visit a restaurant once. Depending on where you see it, the number changes a little, but the takeaway is always the same. Roughly one out of every five guests is going to return.
Thanks Hamed!
We hear that stat in every marketing meeting and immediately go into battle mode. Everyone starts thinking, “If I could just convert 10% of those one-time guests into second-time guests, that would be magic.”
You’re not wrong.
And you should absolutely spend some time thinking about it. But that thinking has a major flaw.
If this happens across every restaurant, regardless of concept, then it doesn’t matter how clever your email subject line is or where you place the emoji. We’re talking about a macro human behavior. None of us are smart enough to rewrite human nature on that scale.
That doesn’t mean it’s not a worthy pursuit or that you shouldn’t try to influence it. It just means you need to approach the problem differently.
I realized this earlier this year, and once I started figuring out what to do instead, the results across every restaurant brand I work with changed dramatically. The challenge was that we didn’t have the tools to figure this out until now. And now that we do... oh boy.
So here’s the framework.
ANALYZE TOP GUESTS: Analyze the patterns, behaviors, and purchase decisions of the guests who generate your top 5% to 10% of revenue. If you’re a higher-frequency concept, I’d start with guests who have made 10 or more visits. If you’re a lower-frequency concept, like fine dining or upscale full service, maybe start around five visits.
ANALYZE ONBOARDING GUESTS: Next, analyze guests with roughly half that purchase frequency. I wouldn’t use two-visit guests, and I’d even caution against using three. I’d start around five visits. Again, if you’re a lower-frequency concept, maybe three or four.
COMPARE THE TWO GROUPS. I guarantee you’ll find fewer than five meaningful differences. Every restaurant brand I’ve done this with has had five or fewer, and they’re usually much more obvious than you’d expect. That’s actually a good thing.
PICK ONE PATTERN: Pick one, maybe two, of those patterns or behaviors and build marketing that gets the lower-frequency guests to take those same actions.
One thing I’d caution when building your segments is to test guests who are lapsed, but haven’t churned. Once somebody has churned, you’re solving a very different problem. But if they’re simply overdue for another visit, you’re still top of mind. Sometimes they just need the right reason to come back.
As a quick example, we recently learned at Salad House that guests who try our Cauliflower Bites have something like a 56% higher chance of becoming a high-frequency guest. They’re really good. I mean, it’s deep-fried vegetables tossed in sweet chili sauce and sesame seeds. It’s like being healthy and cheating in the same dish!
We identified guests in that pre-churn stage and sent them an offer for free Cauliflower Bites.
From email alone, that campaign generated nearly $300,000 in sales, and 23% of those guests went on to make another purchase within a couple of weeks.
Not only did we get them to come back, we reignited their journey. That’s now becoming an always-on automation.
There’s a lot more nuance to this, but for the sake of a newsletter I wanted to share the framework so you can start thinking about how it applies to your brand.
The tricky part isn’t the segmentation, it’s the analysis. If you don’t have an AI-powered customer analytics platform like Bikky or Hang, you can still do this.
On the data.
Export everything your POS and loyalty platform will give you. Don’t pre-summarize it, and don’t pull a report. You want raw transaction and item-level detail with a guest ID attached to every row. That join, connecting POS orders to loyalty profiles, is the real work here.
You can only analyze guests you can identify. If most of your transactions are anonymous, fix that first.
Then compare your two groups on things like:
Are they in loyalty, and can you contact them?
What day parts and days do they visit?
Which fulfillment channels do they use, and how much of their business is third party?
What do they actually order, at the item level, not the category level?
How many different menu items have they tried?
What’s their average basket size, and are they paying full price?
Two final rules
First, analyze at the item level. Category rollups will tell you both groups order salads, and you’ll conclude there’s nothing there. The magic is almost always hiding one level deeper.
Second, run every comparison twice: once across their full history and once using only their first 90 days. Lifetime averages mostly prove that loyal guests have simply been around longer. You’re trying to identify the behaviors that created loyalty, not the ones that happened because they were already loyal.
Once you understand that data, you can start making the moves above. I would test a segment, see what happens, make it better, and only then turn it into an always-on automation.
If you'd like to take me up on an order of Cauliflower Bites at Salad House, I'd love to make that happen. If you'd like help finding your own "Cauliflower Bites," shoot me an email. That's what I do. [email protected]
P.S. It was Caleb Clark from Hook + Ladder Digital who asked me that original question, and I honestly think it’s one of the best questions I’ve been asked. I’ll share that podcast episode soon.
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- Rev Ciancio
WHAT DOES REV DO?
I help restaurants to build guest marketing programs.
I help hospitality tech companies with lead generation and content marketing.
