Guests don't search from your lobby. They search from the airport, the station and the conference centre.
"Hotel near me" means something completely different typed at the airport, outside the convention centre, or three streets from your own front door — and a ranking check run once from your property's address says nothing about the map pack a guest actually sees standing at the train station. SeoMap simulates that search from every point guests actually search from — one grid per landmark or district — and colours the result so you see exactly where you hold your own against the OTAs and chain hotels, and where you don't.
Built around what you actually do all day.
- 01
A grid built around landmarks, not your front desk
Centre the scan on the train station, the airport, the convention centre or the historic district instead of your own address — those are the coordinates guests are actually standing at when they type "hotel near me". A configurable 7×7 to 13×13 grid covers a downtown core tightly or a whole airport corridor more loosely, whichever matches the trip your guests are on.
- 02
One booking intent per scan, not one blended guess
"Hotel near me", "hotel near [convention centre]", "boutique hotel [city]" and "hotel near [airport]" can each surface a different set of properties at the very same coordinate. Scan each term you actually get booked from separately instead of assuming one ranking check covers every kind of trip.
- 03
Multi-property groups and franchise-branded hotels, kept apart
Every project is matched by Google CID/Place-ID, not by name — so two branch hotels carrying the same flag across town, or your own group's second property a few blocks away, never get confused with each other. Groups running several properties in one city can compare every listing side by side.
- 04
Ratings and review counts at every point, not just position
Click any grid point for the full top 20 at that coordinate, including each competing property's star rating, review count and whether it's running paid ads there. In hospitality, a lower position with a stronger review count still wins bookings — the point detail shows you both, not just the rank.
- 05
Proving a push ahead of a trade show or peak season actually worked
Before a conference, a festival or a seasonal surge, scan comparison lays the old and new grid side by side and shows the delta per point — improved, dropped, new, lost. That's the evidence a revenue manager or ownership group wants before the next budget gets approved.
What a hotel’s grid actually shows
Hospitality search is landmark-shaped, not address-shaped. A guest typing “hotel near me” while standing at the train station, another one outside the convention centre, and a business traveller doing the same search from the airport corridor can each land on a completely different set of properties, because the map pack recalculates per coordinate — and a single “we rank well” check, run once from your own address, says nothing about what any of them actually see. A grid scan puts that on the map instead of leaving it to guesswork: centre it on the landmark your guests are actually travelling from, run it on the terms they actually type, and watch which properties turn up green next to you and which ones — OTA listings, chain hotels, a competing boutique property — already own that landmark’s map pack.
That matters twice over for a revenue or marketing team deciding where to spend. First, it shows which landmark actually needs attention — a downtown core that’s already solid green doesn’t need the same push as an airport corridor sitting at amber or red ahead of a trade show. Second, ATRP (Average Total Rank Position) counts the grid points where you didn’t show up at all, not just the ones where you did — the blind spot that makes a property think its visibility around the city is wider than it actually is.
For groups running several properties, the same grid run separately per property — matched by CID/Place-ID so two flags carrying the same brand name never get confused — turns into a straightforward comparison: which property actually reaches furthest from its own landmark, and which one needs a push before the next event calendar fills up.
Prepare your measurement
Questions we actually get asked.
We rank #1 near our own address — why do we disappear for "hotel near [convention centre]"?
Google Maps recalculates the map pack per coordinate based on proximity, relevance and your profile's own signals — ranking well next to your property says nothing about a search typed a few kilometres away at a landmark. A grid scan centred on that landmark is the only way to see it directly instead of assuming it matches your own-address ranking.
Can we track airport, downtown and convention-centre searches separately?
Yes — run one scan per term ("hotel near [airport]", "hotel near [convention centre]", "hotel near me" from downtown). Each can surface a different set of competing properties at the same coordinate, so treating them as one ranking hides real gaps.
We run several properties in the same city, some under the same brand flag — will they get mixed up?
No. Every project is matched by Google CID/Place-ID rather than name, so two same-flagged properties, or your own group's second location, stay cleanly separate even when the listing names are near-identical.
Does SeoMap show competitor ratings and review counts, not just where they rank?
Yes — the point detail view shows the full top 20 at that coordinate including star rating, review count and ad presence for every competing property, so you can weigh position against review strength the way a guest actually would.
Is there a way to try this before committing budget ahead of a trade show or peak season?
Yes — 500 free credits on signup, no credit card. Enough to run a real scan around the landmark that matters for your next event before you commit a marketing budget to it.
Can I pull the data into another tool, or do I need to read every scan myself?
Both are covered. A read-only REST API ships with every plan — self-managed, revocable keys, endpoints for projects, scans and individual grid points — so you can wire results into Zapier, n8n or your own reporting. Every completed scan also gets a short AI-generated analysis paragraph automatically, on top of the existing rule-based breakdown, so you're not staring at a raw grid trying to figure out what changed.
Lay the map over your service area.
The first scan takes under three minutes. After that you’ll see your visibility the way your customers do.