What one month of store openings data says about your trade area

A typical franchise site selection report is a snapshot: a single month, a single view of how many Starbucks are within 5 km, what brands are co-tenants, what the demographic band is. You get one still frame.

That snapshot is useful. But a still frame of a changing market is misleading. If a neighborhood added six new coffee shops in the past month, the "12 competitors" number doesn't tell you whether you're entering saturation or capturing the front of a boom.

Real insight comes from comparing snapshots across months. When you watch the same 1-km trade area in May and then in June, you see which brands opened, which closed, whether competition is flooding in or staying stable, and how fast the market is reacting to the location.

What the monthly data reveals

Suppose you're evaluating a coffee location in downtown Toronto. One report says "49 coffee shops in a 1-km radius, up from 46 last month." Three opened. Zero closed. That's +3 net in a month. Annualize it: roughly +36 coffee shops per year in that same circle. At that rate, the market is densifying fast. You need to know why—is the neighborhood booming, is coffee saturation visible on Google, are you entering the top of the wave?

The alternative report says "49 coffee shops, same as last month." Stable market. Different strategy: you're holding market share, not chasing growth.

These are different bets. Vantlens publishes monthly snapshots so you can compare.

The honest limit: POI query caps

When we report "1,000 places in this trade area," we mean we queried the Overture Maps database for all POI within the 1-km radius and the response came back capped—Overture hit its result limit. We flag this openly in the Data Quality section. The real number might be 1,200 or 2,000. We don't know.

Why does this matter for month-over-month? Because if May's query capped at 500 places and June's capped at 1,000, you can't compare them. The increase is partly real growth and partly "we ran a better query this time." We have to be honest: "POI counts reported as a lower bound when hitting the source cap—and flagged as such."

This is why openings data is more reliable than raw category counts. If May showed Starbucks x10 and June shows Starbucks x12, we're confident in the +2. The caps affect the totals, not the brand-specific deltas.

Why you need to see the churn, not just the net

Month-over-month also shows closures. If May→June brought +3 coffee openings but +4 closures, the market is contracting. That's a red flag—the neighborhood may be losing foot traffic, leases are going dark, and competition is exiting. If May→June brought +3 openings and zero closures, the market is growing. You're not just holding; the tide is rising.

Closures are harder to measure than openings because Overture Maps captures current locations, not history. When a store closes, it drops out of the database. We infer closures by comparing snapshots: sites that were present last month but absent this month are counted as closed, with a caveat that Overture's data lag might account for some of the gap.

Real-time closure data doesn't exist in free, open sources. Paid foot-traffic vendors sell it. We use observable deltas: month-to-month snapshots. It's imperfect but it's honest.

Example: downtown Toronto, May→June 2026

Downtown Toronto shows the pattern:

• Tim Hortons: 16 locations in June. Stable (was 16 in May). No new openings, no closures. The coffee behemoth isn't expanding there; it's holding.


• Starbucks: 12 locations in June. Up from 10 in May. +2 new units. A smaller brand, but actively deploying capital in the market. You're entering a neighborhood where Starbucks sees opportunity—but not so much opportunity that Tim Hortons is chasing it.


• Independent coffee: ~27 locations in June (coffee shops minus chains). Distribution scattered. No visible brand clustering. A fragmented market is harder to win in—you're not riding a brand's expansion wave, you're betting on your own differentiation.



The takeaway: if you're opening a specialty coffee brand (cold brew, pour-over, third-wave), the downtown Toronto trade area is growing (Starbucks +2) but not flooded (only 2 new units). If you're opening a commodity coffee location, Tim Hortons' stability might mean the market is saturated—there's no expansion room at scale.




Compounding insight: three months of data




One month is a signal. Three months is a pattern.




May: +3 coffee shops
June: +2 coffee shops
July: +4 coffee shops




+9 over three months is a clear growth trend. The market is densifying. The question shifts from "is there room?" to "who succeeds in a crowded market?" You start evaluating your differentiation, your lease, your margin—because traffic exists, but you're not alone.




Flip it:




May: +3 coffee shops
June: -1 (net: 3 closures, 2 openings)
July: -2 (net: 3 closures, 1 opening)




That's a market contracting. Traffic may be leaving. Brands are exiting. A new entrant is fighting against the trend, not riding it.




This is why Vantlens pins the Overture Maps release date and vintage in every report. You can hand last month's report and this month's report to your broker or attorney, compare them side by side, and see whether your market is moving.




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Sources:


• Overture Maps Foundation, monthly releases (pinned to each report)


• Trade area: 1-km radius, downtown Toronto (43.650°N, -79.381°W)


• Coffee shop query: category = coffee_shop (Overture taxonomy)