I’ve been reading Seven-Eleven Japan’s results as part of learning about a country I hope to call home. My Japanese is still developing, but I can find my way around a grocery sales report.
Three numbers made me stop. Comparable-store sales increased 1.1%. Customer counts declined 1.7%. Spending per customer increased 2.8%. Ryutsu News, October 8, 2026
I wondered what the people still shopping there would make of those results. Would they recognize the growth as something positive? Or would they say their usual purchases were simply costing more?
My read is that retailers are putting more pressure on loyal shoppers to spend more as other customers leave or visit less often. We keep asking the people who stay to support more of the business. I think that may be slowly breaking them.
These figures don’t identify individual shoppers or explain why their spending changed. They do show higher sales from fewer visits. I want to understand what that feels like from the customer’s side.
I’ve spent much of my career on the other side of that question.
I started at a grocery checkout, then worked in buying, pricing, category management and customer insights. Much of that work involved finding ways to increase spending: improve an assortment, change a promotion, suggest something else a customer might want.
There are good reasons to do those things. A store can introduce someone to a product they enjoy or offer a discount on something they need. I’ve also sat with enough shopping data to know how easily a person becomes a growth target.
When a customer already visits frequently, we ask what else they could buy. When they buy across several departments, we look for the one they haven’t tried. When they respond to offers, we send another.
Each decision can look reasonable on its own. The customer pays for the combined result.
Still shopping doesn’t mean nothing has changed
There’s probably a store you visit because it fits easily into your day. You know where everything is. You can get lunch without thinking too hard. Stopping somewhere else would take longer.
You might keep going even as you become less happy with the cost.
Perhaps you stop buying a drink with lunch. Perhaps you buy the same thing but notice the price every time. You start comparing it with another option, although you haven’t changed your routine yet.
The retailer still sees you shopping.
That is what interests me about loyalty data. Someone can continue using their card while changing how much of their shopping they do with that business. Their account remains active, but the relationship may already be weakening.
A weekly visit becomes fortnightly. The full shop becomes a few essentials. They still buy the coffee, but lunch comes from somewhere else now.
I’d want to notice those changes before sending them another offer designed to make their basket bigger.
The Japanese word I’m learning
客数（きゃくすう）, kyakusū, means customer count.
It’s worth checking how a retailer defines it. A count based on transactions won’t tell us how many different people visited. Someone buying coffee every morning could appear five times in a week.
Here’s my practice sentence:
客数の変化を調べます。
With readings: 客数（きゃくすう）の変化（へんか）を調（しら）べます。
Romaji: Kyakusū no henka o shirabemasu.
English: “We will examine the change in customer count.”
I hadn’t expected my Japanese studies to involve questions about how transactions are counted, but this was probably predictable.
What I’d want to know
If I were reviewing these results with a customer insights team, I’d begin with the people who had been visiting most often.
Are they coming in as regularly? Are they buying more items, or paying more for the same number? Have they stopped buying something that used to be part of their usual shop? Are they waiting for discounts?
Then I’d look at what they come to the store to do. Someone who stops buying an occasional snack presents a different problem from someone who no longer comes in for lunch. Losing lunch could also mean losing the drink, dessert and something picked up for later.
The data won’t answer every question. It only includes the purchases we can see, and identified customers may differ from those who never use a loyalty card. We would still need to investigate why behavior changed.
But it could help us avoid an uncomfortable mistake: seeing a customer spend more because prices have risen and deciding they are a good candidate to spend even more.
I don’t think that requires a cynical team or a particularly aggressive retailer. It can happen because everyone has a target and the same shoppers keep appearing as the best people to help meet it.
There’s a supplier in this conversation, too
My work now includes helping retailers build paid data and insights programs for consumer brands. Those programs can give suppliers a better understanding of who buys their products and help them work with buyers on pricing, promotions and assortment.
They also give us a reason to be careful about what we call success.
A brand might pay for an offer aimed at its regular buyers and see sales increase. The retailer might report a successful promotion. But did anyone buy something they wouldn’t otherwise have bought? Did they stock up early? Did they switch from another brand? Will they need to buy less next week?
And did the offer help the customer, or just give several businesses a result they could report?
I want supplier data programs to help answer those questions. Their value should come from improving decisions, including the decision to stop repeating an offer that produces little benefit.
There is a lot of interest in identifying the customers most likely to respond. I’m equally interested in whether we’re asking too much of them.
The same household might be valuable to the retailer, several brands and an advertising program. None of those teams necessarily sees everything the others are asking that household to buy.
I understand why retailers keep asking
Running a store is expensive, and higher sales don’t necessarily cover the increase in costs.
U.S.M.H reported first-half revenue growth of 14.0% alongside an operating loss of ¥3.283 billion. Its October disclosure described pressure from demand, pricing and operating expenses, as well as sales contributed by its expanded business. U.S.M.H results, October 9, 2026
That is a separate business with its own circumstances. It does, however, help explain why getting more sales from existing customers can feel so urgent.
I understand the request. I’ve worked on it. What concerns me is how often the answer depends on someone who is already spending regularly with us.
A promotion’s response rate is easy to put in a report. A shopper thinking, “I can’t keep doing this,” is harder to see.
By the time they stop coming, there may have been plenty of smaller signs.
What I want to understand next
I’m bringing years of retail experience to these questions, but I’m still learning how they play out in Japan. I don’t want to assume that a shopping habit, a promotion or a loyalty program means exactly what it would in the markets where I’ve worked.
That’s part of why I’m writing this series. It gives me a way to explore Japan through something familiar while noticing where that familiarity stops being useful.
For this first piece, I keep thinking about the loyal shopper who is still coming in and paying a little more. How long can a retailer depend on that before the customer starts looking for a different place to shop? My expectation is that higher spending per visit becomes a less convincing growth story if customer visits keep falling.
Next, I want to look more closely at Seven-Eleven, Lawson and FamilyMart. Their stores fit into everyday routines in ways I’m curious about: breakfast, lunch, coffee, a quick stop on the way home.
I want to understand what they’re doing to bring people back, and whether the people coming back feel they’re getting enough in return.
