A store's local visibility is decided product by product. 'Running shoes', 'phone repair' and 'sofa showroom' can each show a different set of stores, chains and independents share the same Map Pack, and for retailers that share their local inventory with Google, products in stock nearby can appear before a store is listed at all. For an independent the question is which searches you are missing; for a chain it is which stores. SearchOps answers both, and shows what ChatGPT and Gemini recommend when shoppers ask where to buy.
The problem
Google asks chains to use the same name and category at every location, so a national retailer's stores look alike on the map, and independents take them on search by search. For a chain, the risk is a brand average that hides the stores that have dropped out of their local searches. For an independent, the opportunity is the product and category searches where a more specific offer can win.
Category and product searches can each show a different set of stores within the same town.
Attributes such as in-store pickup, delivery and accessibility show on your profile, so missing or wrong details can cost a visit.
Google's 'open now' filter reads your opening hours, which matters for late-night and weekend searches.
When a shopper asks an AI assistant where to buy locally, the answer names only a few stores and draws on the sites it trusts.
Questions SearchOps answers
For a store owner or a regional manager, these five questions show where to act first. Each one is answered by data SearchOps collects for every store.
01Products
Track category, product and brand searches for each store's town, such as 'outdoor clothing store Denver', 'iPhone repair near me' or 'wedding dress shop Leeds'. Geo-grid scans show where each store appears on Google Maps and in the local pack for each one, and whether an AI Overview names it.
Visibility for the searches that bring people through the door
Used in this step
02Catchment
Geo-grid scans show each store's Google Maps position across its catchment, from a high street to a whole metro area, with the stores ahead of it at each point. Geo-Grid Insights compares you with those leaders on categories, reviews and listing details.
The ground each store holds, and where shoppers go instead
Used in this step
03Store estate
Every store is its own tracked location, so you can compare map coverage, rankings, reviews and profile results across the estate. Connected profiles show direction requests, calls and website clicks for each store, and the searches that showed it.
A list of stores to support, not an average
Used in this step
04AI answers
SearchOps asks ChatGPT and Gemini questions like where to buy a good mattress in Manchester or which bike shops in Portland do repairs. You see how often your store is recommended, the retailers named instead, and the review sites, marketplaces and guides the answers cite.
Your share of AI recommendations in each market
Used in this step
05Reviews
Google reviews, plus Trustpilot on Pro and above, arrive in one feed with sentiment grouped by topic, so staff, prices or waiting times show up as trends rather than one-off complaints. On connected profiles the agent drafts replies for you to check and send.
Store-level reputation you can act on
Used in this step
The toolkit
Product, brand and category rankings, map coverage for each store, ChatGPT and Gemini, store profiles and reviews, in one place, from a single shop to 200 stores, with Enterprise for larger estates.
Also working for you
Before and after
Use cases
Illustrative examples from independent shops and multi-store retailers.
Outdoor clothing chain, 30 storesUnited States
Scans for 'hiking boots near me' across each store's catchment show most stores in the top three near their doors, and six dropping out within a mile, where a rival chain's stores appear instead. Those six have fewer recent reviews, which gives regional managers a short, specific list to work on.
Independent bookshopCork, Ireland
A scan for 'bookshop' across the city shows the shop holding the top three in the streets around it and disappearing a short walk away, where a chain store appears. Tracking the same search as reviews and profile details improve shows whether that boundary moves.
Furniture showroomPerth, Australia
AI visibility checks ask ChatGPT and Gemini where to buy a good sofa in Perth. The showroom appears in some answers, two national retailers appear in most, and the answers cite a local home guide the showroom isn't featured in. That is a specific, winnable gap.
Phone repair chain, eight shopsBirmingham, UK
Connected profiles show direction requests, calls and website clicks for each shop. Two shops earn most of the requests, and scans for 'iPhone screen repair' in each town show the others appearing across far less of their areas. The gap is visibility, not demand.
Choosing a plan
Plans scale with the stores you track, from an independent with a couple of rivals to watch to a national chain. Every plan includes every tracking tool.
For an independent store or a few shops
For regional chains
For national chains and their agencies
FAQ
The same platform, set up for a different kind of business.
