# /blog/google-business-profile-audit-guide - Home - Blog - How to audit a Google Business Profile: the seven-category method # How to audit a Google Business Profile: the seven-category method The seven-category audit method behind PlaceOptimizer — the checks that power the operator console, and what still needs a human. Vinayak Kulkarni · 6 Jul 2026 · updated 21 Jul 2026 audit gbp playbook Most Google Business Profile "audits" are a screenshot and a gut feeling. That does not scale past one store, and it misses the issues that actually move local-pack rankings. This is the method we run in production for multi-location Indian brands: an audit checklist across seven categories, each tied to a visibility or conversion outcome, with some checks fully automated and others flagged for manual review. ## Why audits matter for the local pack Google's local ranking guidance names three factors, relevance, distance, and prominence, and states that complete, accurate information helps Google match your business to the right searches ( Improve your local ranking on Google , accessed July 2026). You cannot move distance, but relevance and prominence are largely a function of listing quality: complete data, accurate categories, healthy review velocity, and consistency across your locations. Google encourages businesses to keep their profile complete and up to date, because a complete profile is easier to match with the right searches and gives customers the information they need to choose you ( Improve your Business Profile on Google , accessed July 2026). For a forty-store chain, an unmanaged listing estate quietly leaks customers in every city. ## The seven categories we check We organise the checklist into seven categories. Six run per listing; the seventh compares your listings against each other. Under each, we are explicit about what our engine automates today and what still needs a human, because an audit tool that pretends everything is automated is not being straight with you. ### 1. Basic information Phone number present and in valid +91 format, full street address, website URL, and a description of at least 50 characters. A missing phone number is a critical trust gap, since customers calling ahead is still the dominant pre-visit behaviour in Indian retail. Automated: phone presence and +91 format, address presence, website presence, description length. Manual: whether the address components are structured the way Google prefers, and whether the website link resolves to a live page. ### 2. Business hours Hours set for all seven days, and no stale holiday overrides. "Hours unknown" listings get demoted in the local pack, and wrong hours generate the angriest review category there is: the customer who travelled to a closed door. Automated: presence of hours and whether all seven days are populated. Manual: holiday and special-hours overrides, which Google supports ( Edit your Business Profile hours , accessed July 2026) but a stale override is not something we detect yet. ### 3. Ratings and reviews Automated: the engine reads the two signals in the data Google returns, star rating and review count , each as a severity ladder that fires at most one tier (a sub-3.5 rating is Critical, 3.5 to 4.0 is Warning; fewer than 10 reviews is Warning, 10 to 50 is Info), plus a heuristic flag for probable unanswered negative reviews. Manual: star rating versus category median, review recency, and owner response rate. Those are among the strongest prominence factors and response rate is one of the few you control directly, but reading them correctly needs a human in the review stream, so we mark them manual rather than pretend the score computes them. ### 4. Media At least ten photos per location, with fresh uploads. Listings with recent photos earn more clicks to the website and more direction requests. Automated: photo count against thresholds (zero is Critical, fewer than 5 Warning, fewer than 10 Info). Manual: photo freshness , which Google encourages you to keep current ( Add photos or videos to your Business Profile , accessed July 2026) but whether your newest photo is 30 days or 3 years old is not in the automated pass yet. ### 5. Categories and attributes Primary category matches what the location actually is, and secondary categories cover real services without spam. Wrong primary category is the single most common reason a listing ranks for nothing. Automated (with a scope limit): the "generic primary category" check today uses a mattress-and-furniture allowlist, because our first design partners are in that vertical, plus a secondary-category-presence check. Manual or roadmap: category correctness for any non-furniture vertical, and comparison against the category most competitors use. If you run a restaurant or clinic network, we would tell you on the call that this specific check is not meaningful for you yet rather than let a false Warning mislead you. ### 6. Listing health Automated: a listing marked PERMANENTLY_CLOSED flags Critical, and an abandonment heuristic (zero photos and almost no reviews) flags Warning. Manual: suspension risk and edit-conflict history, which are not exposed in the public data. ### 7. Cross-location consistency Name format drift ("Brand Name Baner" vs "Brand Name - Baner Pune"), category mismatch across the estate, and proximity-based duplicate candidates , all of which only surface when you compare listings side by side, which is exactly why manual audits miss them. Automated: four consistency axes (business name, primary category, website hostname, phone format) plus a proximity-based duplicate-candidate detector that surfaces same-brand pins within about a kilometre for human review. Manual: address-structure consistency, how each listing captures its city, and confirming any duplicate candidate before a merge. Because a candidate is never a confirmation, the detail lives in how duplicate detection works across an estate and the four consistency dimensions . ## Scoring: from checklist to one number Every location starts at 100 and loses points per issue the audit raises, weighted by severity: Critical costs the most, then Warning, then an Info note. Per-location scores roll up to a single Brand Health Score, with extra deductions for cross-location drift such as name fragmentation and duplicate candidates. One honesty note worth repeating: the rating, review-count, and photo-count checks are severity ladders, so each contributes at most one issue rather than stacking. The exact point weights, formulas, and a worked example are laid out in the Brand Health Score methodology . The point of one number is organisational, not technical: it gives the marketing lead something the whole team can track monthly, and the ranked issue list underneath tells operations exactly what to fix first. It is a PlaceOptimizer diagnostic, not a Google metric, and it reflects the automated checks only. ## An honest note on what this audit does and does not do The automated pass is fast, repeatable, and consistent across every location, which is its whole advantage over a manual eyeball. What it is not: a live-ranking checker, a review-sentiment reader, or a substitute for opening a flagged listing and looking. A clean score means your public data passes the automated checks; it does not certify that every review is answered or every photo is current. Those are the items we mark manual, on purpose. The full automated-versus-manual inventory is in what the audit actually checks today . ## Run it yourself You can run this checklist by hand with our free GBP audit checklist , budget about ten minutes per location. Or run the free automated audit , which applies every automated check above to each location Google shows for your brand and returns a scored report in about a minute. ## Put this playbook on autopilot. The free audit runs every check in this post across all your locations — no card required. Get a free audit Book a demo