We Checked 284 Google Maps Results. 1 in 4 Was Not the Business We Searched For.

How we measured it

We took 12 English-language keyword searches already in our corpus and sampled up to 30 random businesses from each, one per distinct domain so that a chain with forty branches could not dominate a keyword. For every business we fetched the homepage, stripped it to visible text, and judged it against the keyword with a four-way rubric. Every verdict required a verbatim quote from the page as evidence, so no judgement rests on a business name alone.

• Match — the business primarily is the thing searched for.
• Adjacent — a related trade that is not it. Roof cleaning for "roofing contractor". A supplier to the trade rather than someone practising it. A generalist listing the service among twenty others.
• Mismatch — a different business entirely, or a directory or aggregator rather than an operating company.
• Unclear — the page never says what the business does.

The rubric explicitly refuses to downgrade a business for being small, for calling itself a studio or a practice rather than an agency, or for specialising in one industry. An earlier version did all three, and it understated the match rate, so we fixed it and re-ran.

Sites we could not read were recorded separately and excluded from the denominator, because that is a fact about the website, not about whether the business matched. It is a large fact on its own: 76 of 360 sampled sites, 21.1 percent, were dead, blocked or empty, which is consistent with our earlier website churn study.

Finding one: the keyword decides everything

A precise trade name lands. A broad or ambiguous one falls apart. "Home remodeling contractors" returned house cleaning services, a hotel, a pest control company, a mold remediation firm, a commercial real estate brokerage and an apartment complex. "Staffing agency" returned two theatres, a car rental branch, a UPS Store and a Marine Corps recruiting office.

Finding two: the obvious fix works better than we expected

We built this study expecting to show that the fields cannot save you, and that only reading the website can. That is not what the data said, and it would have been easy to leave this section out.

Every Google Maps result carries a business category. Filter the results down to the categories that the genuine businesses actually carried, and almost all of the junk disappears: only about 4 percent of what survives is still the wrong kind of business. A theatre does not carry the category "Employment agency". If you are building a list and you are not filtering on category, start.

Finding three: that fix quietly deletes real businesses

It is not free, and the cost is invisible, which is the worst kind. The same category filter also discarded 24 of the 205 genuine businesses, 11.7 percent. We read all 24 by hand. They are real, and several are exactly the customer you were looking for:

• Big Brand Tire & Service, whose own page says "Tire Shop & Auto Repair in Phoenix, AZ", is categorised Tire shop. Dropped from an auto repair list.
• J & J Remodeling Team LLC, "a locally owned remodeling company", is categorised Remodeler. Dropped from a home remodeling list, because the category that dominated the genuine results was Home builder.
• RSU Contractors, "expert kitchen remodeling, bathroom renovations, and home additions", is categorised General contractor.
• A pediatric dentist, an orthodontist and a periodontist all dropped from a dentist list, because Google files each specialism as its own category.
• Econo Lube N' Tune & Brakes, doing "automotive repair and maintenance work", is categorised Oil change service.
• A plumber categorised Home help. Nobody would have guessed that one in advance.

This is the trap: the category is one self-chosen label from a list of thousands, and it frequently describes a specialism rather than a trade. Dentist, Orthodontist, Pediatric dentist and Dental implants periodontist are four separate Google categories for what a dental supplier would call one market. To filter without losses you would need to know the whole family of categories in advance, for every trade you sell into. Some of that family is guessable. Home help for a plumber is not.

So both things are true at once, and only saying the first one would be a sales pitch rather than a finding. Category filtering is a good, cheap, underused tool that removes most irrelevant results. It also silently removes about one in nine of the businesses you wanted, and you will never see the ones it took.

What we will not conclude from this

We would like to tell you that this proves reading the website beats filtering on the category. This study cannot prove that, and here is exactly why.

The judgements in this study were made by a language model reading each homepage. That means the model both defined the answer key and is the method being compared against it. Measuring the category filter's mistakes against the model's verdicts and then concluding the model wins is circular, and we are not going to do it. What the study does establish is narrower and still useful: a mechanical category filter deletes real businesses at a measurable rate, and we verified all 24 losses by hand rather than taking the model's word for it.

Establishing the other half honestly needs a second, independent rater scoring the same pages blind. That is a cheap experiment and we will run it. Until we do, the number in this post that we would defend is 72.2 percent, and the sentence we would defend is that category filtering trades recall for precision without telling you.

What to actually do with this

Three things follow, none of which require our product.

Use precise trade keywords, not category words. "Roofing contractor" is a trade. "Home remodeling contractors" is a category of work that dozens of unrelated trades touch, and it returned a list that was 72 percent noise. If you must run a broad keyword, expect to qualify by hand.

Filter on category, then look at what you dropped. The filter is worth running. Pull the excluded rows into their own view instead of deleting them, and you will find a tire chain and three dental specialists sitting in it.

Judge the business by its website, not by its label. Every claim in this study came from a verbatim sentence on the company's own homepage, because that is the only place a business says what it actually does. It is also why we enrich every result from its live website rather than trusting a category field, and why every field we ship records how we know it.

Methodology notes for anyone citing this: 12 English-language Google Maps keyword searches, up to 30 US businesses sampled per keyword, deduplicated to one row per registrable domain, 360 sampled and 284 judged; homepages fetched in a single pass on August 9, 2026 with a plain-HTTP fetcher; judgements by gpt-4o-mini at temperature 0 with a four-way rubric requiring a verbatim quote as evidence; 76 unreachable sites excluded from the denominator and reported separately; all 75 non-match verdicts and all 24 category-filter losses read by hand. Errors were found in both directions and roughly cancel, so treat the headline as roughly 7 in 10, plus or minus 3 points, not as 72.2 percent to one decimal. Cite freely with a link.