Water damage restoration: what we measured in 50 US metros
In our October 2026 study, ChatGPT (the OpenAI API with web search) named 45 of the 149 water damage restoration businesses at the top of Google Maps across 50 US metros, and 46 of the 148 in Google's local pack. This page brings together the study's water damage restoration figures, city by city, each with its base.
By Youssef Hodaigui, Mindflow Marketing · Data collected October 3–17, 2026
- 1
A homeowner has a job to do
emergency plumber near me - 2
They look in three places
Google resultsThe mapAn AI answer - 3
They check before they call
Reviews, photos of real work and a page that answers their question.
- 4
They request an estimate
Your form or phone number, working on their phone.
Not an actual ranking, listing or result.
| Maps top three named by ChatGPT | 45 of 149 |
|---|---|
| Maps top three also in the local pack | 46 of 149 |
| Local pack named by ChatGPT | 46 of 148 |
| On all three lists | 16 businesses |
How did we check water damage restoration businesses?
In each of 50 metros, on one day, we searched Google Maps for "water damage restoration" at a fixed map point in the city and kept the top three listings, took the three businesses in Google's local pack for the service and the city, and listed every business ChatGPT named in five answers to "Which [trade] companies in [City], [State] should a homeowner call? Name the companies and the sources." A business counts as named if it appeared in at least one of the five answers. The full rules are on the methodology page.
In how many metros did ChatGPT name a water damage restoration Maps leader?
In 31 of the 50 metros, ChatGPT named at least one of the three water damage restoration businesses at the top of the map; in 19 it named none, and in 1 it named every one of them. Each row below is one check of three listings, so read single cities with care; the totals are the steadier figure. Each metro links to our page for that city.
| Metro | Maps top three named by ChatGPT | Maps top three also in the local pack | Local pack named by ChatGPT | On all three lists |
|---|---|---|---|---|
| Atlanta | 0 of 3 | 0 of 3 | 0 of 3 | 0 |
| Augusta | 2 of 3 | 0 of 3 | 1 of 3 | 0 |
| Austin | 0 of 3 | 1 of 3 | 0 of 3 | 0 |
| Baltimore | 1 of 3 | 1 of 3 | 2 of 3 | 1 |
| Boston | 0 of 3 | 0 of 3 | 0 of 3 | 0 |
| Charleston | 2 of 3 | 0 of 3 | 0 of 3 | 0 |
| Charlotte | 0 of 3 | 1 of 3 | 1 of 3 | 0 |
| Chicago | 1 of 3 | 0 of 3 | 0 of 3 | 0 |
| Cincinnati | 2 of 3 | 1 of 3 | 2 of 3 | 1 |
| Cleveland | 0 of 3 | 2 of 3 | 1 of 3 | 0 |
| Columbia | 0 of 3 | 2 of 3 | 1 of 3 | 0 |
| Columbus | 2 of 3 | 1 of 3 | 1 of 3 | 0 |
| Dallas | 0 of 3 | 2 of 3 | 1 of 3 | 0 |
| Denver | 1 of 3 | 1 of 3 | 2 of 3 | 1 |
| Detroit | 0 of 2 | 1 of 2 | 0 of 3 | 0 |
| Durham | 2 of 3 | 2 of 3 | 3 of 3 | 2 |
| Fort Worth | 0 of 3 | 0 of 3 | 1 of 3 | 0 |
| Greenville | 2 of 3 | 1 of 3 | 0 of 3 | 0 |
| Houston | 1 of 3 | 1 of 3 | 0 of 3 | 0 |
| Indianapolis | 1 of 3 | 1 of 3 | 1 of 3 | 0 |
| Inland Empire (Riverside) | 0 of 3 | 0 of 3 | 0 of 3 | 0 |
| Jacksonville | 2 of 3 | 1 of 3 | 1 of 3 | 0 |
| Kansas City | 0 of 3 | 1 of 3 | 0 of 3 | 0 |
| Knoxville | 3 of 3 | 2 of 3 | 2 of 3 | 2 |
| Las Vegas | 1 of 3 | 0 of 3 | 0 of 3 | 0 |
| Los Angeles | 0 of 3 | 1 of 3 | 0 of 3 | 0 |
| Miami | 0 of 3 | 1 of 3 | 0 of 3 | 0 |
| Minneapolis | 2 of 3 | 1 of 3 | 2 of 3 | 1 |
| Nashville | 1 of 3 | 0 of 3 | 1 of 3 | 0 |
| New York | 1 of 3 | 0 of 3 | 0 of 3 | 0 |
| Orlando | 0 of 3 | 1 of 3 | 1 of 3 | 0 |
| Philadelphia | 2 of 3 | 2 of 3 | 1 of 3 | 1 |
| Phoenix | 0 of 3 | 1 of 3 | 1 of 3 | 0 |
| Pittsburgh | 1 of 3 | 2 of 3 | 1 of 3 | 1 |
| Portland | 0 of 3 | 0 of 3 | 1 of 3 | 0 |
| Providence | 2 of 3 | 1 of 3 | 2 of 2 | 1 |
| Raleigh | 0 of 3 | 0 of 3 | 2 of 3 | 0 |
| Richmond | 1 of 3 | 1 of 3 | 0 of 3 | 0 |
| Sacramento | 1 of 3 | 2 of 3 | 2 of 3 | 1 |
| Salt Lake City | 1 of 3 | 1 of 3 | 0 of 3 | 0 |
| San Antonio | 1 of 3 | 2 of 3 | 1 of 2 | 1 |
| San Diego | 1 of 3 | 1 of 3 | 1 of 3 | 0 |
| San Francisco–Oakland | 1 of 3 | 1 of 3 | 3 of 3 | 1 |
| San Jose | 0 of 3 | 0 of 3 | 1 of 3 | 0 |
| Savannah | 2 of 3 | 1 of 3 | 3 of 3 | 1 |
| Seattle | 1 of 3 | 2 of 3 | 0 of 3 | 0 |
| St. Louis | 1 of 3 | 2 of 3 | 2 of 3 | 1 |
| Tampa | 0 of 3 | 1 of 3 | 0 of 3 | 0 |
| Virginia Beach | 1 of 3 | 0 of 3 | 0 of 3 | 0 |
| Washington, DC | 2 of 3 | 0 of 3 | 1 of 3 | 0 |
| All 50 metros | 45 of 149 | 46 of 149 | 46 of 148 | 16 |
Source: Mindflow Home-Service Visibility Study, collected October 3–17, 2026. Bases below 3 mean a written ruling removed a listing, for example one in the wrong trade or outside the metro. Names that couldn't be tied to a single listing were left out, not guessed; the main study page notes them by metro. Detroit's figures leave out 1 listing across the border in Windsor, Ontario.
What did ChatGPT cite when asked about a named water damage restoration company?
We also asked ChatGPT about 750 water damage restoration businesses by name, two answers each: "A friend recommended [Business] in [City, ST]. What can you tell me about them? Are they legit and good to hire?" Of 1,500 answers, 1,259 cited the BBB, 1,113 the company's own website and 1,243 a government or licensing site. Of the same answers, 931 cited a manufacturer, certification or trade body, most often the IICRC.
| Source | Answers citing it (of 1,500) |
|---|---|
| Any review site or directory | 1,406 |
| BBB | 1,259 |
| Government or licensing site | 1,243 |
| The company's own website | 1,113 |
| Other sites (other businesses, media, blogs) | 1,036 |
| Manufacturer, certification or trade body | 931 |
| Birdeye | 636 |
| A national franchise brand site | 335 |
| BuildZoom | 184 |
When we asked which water damage restoration companies a homeowner should call, without naming one, other businesses', media and blog sites came up in 249 of the 250 answers. Leaving those out, the answers cited these most often:
| Source | Answers citing it (of 250) |
|---|---|
| A national franchise brand site | 249 |
| Any review site or directory | 90 |
| BBB | 86 |
| Manufacturer, certification or trade body | 37 |
Source: Mindflow research, OpenAI API with web search, October 3–17, 2026. Counts the links attached to each answer, not every page the tool read; one answer can cite several groups. The government and licensing group counts any .gov or .us site plus a fixed list of license boards and business registries. How the source figures are calculated. All trades side by side: what ChatGPT checks before recommending a contractor.
What do water damage restoration websites carry?
Almost every saved homepage stated emergency service (430 of 445); few showed any online booking signal (55). We saved 445 water damage restoration homepages and crawled up to 100 pages of 601 sites. Features were found by matching text, which can miss some and over-count others: "book now" counts as a booking signal even without a scheduler.
| On the homepage | Homepages (of 445) |
|---|---|
| Click-to-call link | 412 |
| A form | 229 |
| A free estimate or inspection offer | 172 |
| Emergency service stated | 430 |
| Any online booking signal | 55 |
| Financing mentioned | 99 |
| "Licensed" stated | 190 |
| A review widget | 141 |
| LocalBusiness schema | 189 |
| On the site | Sites (of 601) |
|---|---|
| Five or more service pages | 378 |
| Any location or service-area page | 336 |
| Three or more location pages | 209 |
| A reviews page | 141 |
| A blog | 363 |
Source: Mindflow research, saved homepages and site crawls, October 2026, from the saved files as collected, before the rulings that later adjusted listings in 23 metros. Large sites hit the 100-page limit, so their page counts are floors.
How many Google reviews do water damage restoration businesses have?
Across the 531 water damage restoration businesses in the sample with Google reviews, the median business had 87 reviews in total and 5 new reviews in the 90 days before we collected it; its newest review was a median 14 days old. Among businesses in the Maps top three, the 40 that ChatGPT named had a median of 2 new reviews in 90 days, and the 89 it didn't name had 3. So in this trade, recent reviews didn't separate the two groups. The named group had more reviews in total (median 48.5 against 29). An association, not a cause.
| Google reviews | Median |
|---|---|
| Total reviews, all 531 with reviews | 87 |
| New in the last 30 days | 1 |
| New in the last 90 days | 5 |
| Days since the newest review | 14 |
| Maps top three named by ChatGPT (40): total / new in 90 days | 48.5 / 2 |
| Maps top three not named (89): total / new in 90 days | 29 / 3 |
Source: Mindflow research, Google review data, October 2026, from the saved files as collected, before the rulings that later adjusted listings in 23 metros. The 90-day count comes from each business's newest 100 reviews; for 20 of these businesses all 100 fell inside 90 days, so their count is a floor (in the comparison: 0 of the 40 named and 0 of the 89 not named). Medians include every business, so they differ from our city pages, which leave capped businesses out. The comparison groups come from the saved files, so they cover the 129 Maps top-three businesses with review data and won't match the 45 of 149 above. Detroit's Maps top-three listings are left out of these review figures, because some were across the border in Windsor, Ontario.
How many people search for water damage restoration services, and when?
These are Google's estimates of average monthly US searches for the water damage restoration terms we tracked. Nationally, these searches don't follow a steady season. One month, September 2025, had about ten times a typical month's searches, which lifts the four-year September average to about 4 times June's. City figures move the same way, so we read them year by year rather than as a calendar. City patterns differ; see our restoration marketing page.
| Search (US) | Average monthly searches |
|---|---|
| Water damage restoration | 90,500 |
| Water mitigation | 5,400 |
Source: Mindflow research, Google Ads search-volume estimates: average monthly searches for the 12 months to September 2026, and monthly figures from October 2022 to September 2026 for the season. Searches aren't booked jobs.
What can't these figures tell you?
They can't tell you why a business was named, how the ChatGPT app behaves, or what happens next month.
- Not random.We chose the 50 metros; they don't represent every US market.
- Not the app."ChatGPT" here means the OpenAI API with web search (model `gpt-5-2025-08-07`).
- Five answers per check."Named" means named at least once in five.
- One snapshot.Google and AI answers change.
- Association, not cause.No figure here shows why a business was or wasn't named.
- No names.We report totals only and don't identify any business in the sample.
Can you use or cite this data?
Yes. Download the 50 water damage restoration checks as a CSV with no business names or identifiers: water damage restoration counts by metro. You can reuse it with credit and a link to this page (CC BY 4.0). All eight trades are on the main study page.
Suggested citation: Mindflow Marketing, "Home-Service Visibility Study (October 2026): Water damage restoration," mindflowmarketing.com/benchmark/water-damage-restoration/, data collected October 3–17, 2026.
Spotted an error? Email youssef@mindflowmarketing.com. Our editorial standards explain how we correct pages.
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