Statistics
Local SEO statistics, traced to source
Every number below is graded on where it came from, when it was collected, who it measured and how. The ones that failed are listed too.
Most local SEO statistics describe American consumers, were produced by asking people what they do rather than observing what they did, and a few of the most-quoted ones cannot be traced to a study at all. That is not an argument for ignoring them. It is an argument for knowing which is which before you put one in a pitch deck.
This page is the result of tracing the numbers that circulate in local search back to the organisations that produced them.
Where a figure survives that trace, it is here with its sample, its geography, its method and the year the data was actually collected — which is frequently not the year of the article quoting it. Where a figure does not survive, it is in the section near the end, with an explanation of what went wrong.
Each section below also separates what the data shows from what to do about it. The figures are measured or surveyed findings, attributed and graded.
The short 'what this means' passage after each one is this site's interpretation and recommendation, not a further measurement — and it is written that way deliberately, because the two get blurred everywhere else this data is quoted.
How the grading works
The grading is deliberately unforgiving. A statistic from a good organisation still earns a C if the sample size is not published beside the number, because a reader cannot check what they cannot see.
Cite freely
Primary source, dated, with sample and method published. Quote it, with its scope attached.
Cite with scope
Real research with a published sample, but narrower than the way it is usually quoted — self-reported, or one country, or one kind of business.
Cite with caution
Named source and plausible method, but the sample size or methodology is not published where the number is. Attribute it, do not lean on it.
Do not cite
Untraceable, undated, or superseded by later changes to the thing it measured. These are the numbers keeping the roundups alive.
Most local businesses are less online than the industry assumes
The most useful numbers in local search are not about consumers. They are about how little of the basic infrastructure actually exists, and they come from asking business owners directly rather than surveying the people searching for them. What that infrastructure is supposed to look like when it is complete is set out in the complete local SEO guide.
40%
Grade Bof US small and medium businesses say they have a dedicated business website.
What it does not say Self-reported, and BrightLocal flags the obvious risk itself: some owners count a social media page as a website. No crawl-based study measuring this rather than asking was identified in the sources reviewed.
35%
Grade Bof US SMBs say they have a Google Business Profile.
What it does not say Also self-reported, and awkward against the next number down: profiles are frequently auto-generated, so an owner can have one without knowing it. Treat this as a measure of awareness, not of existence.
89%
Grade Bof US SMBs say they invest in organic SEO.
What it does not say Read alongside the 40% above, this is the most revealing pair in local search: far more businesses believe they are investing in SEO than own the asset SEO runs on.
What this means for how you plan
Read together, these three figures describe a specific and common situation rather than a general one: a business that believes it is investing in organic search while missing one of the two assets search runs on.
Ranking activity — content, links, reviews — cannot act on a website that does not exist or a profile nobody has claimed. A meaningful share of the market reporting SEO investment does not yet own either. The local business website statistics set out how thin that layer is across the market as a whole.
Checking which side of that gap your own business sits on takes five minutes: search the business name and category together, and see whether a website you control appears, and whether the Business Profile shown is one you can sign into. The audit almost always finds an unclaimed or half-built asset before it finds a content problem. This is a recommendation drawn from the pattern above, not a separate measurement.
How people actually search for local businesses
All of the consumer numbers below are surveys of what people say they do, in one country. That is worth stating plainly, because they are quoted everywhere as though they were observed behaviour everywhere.
70%
Grade Bof general online searches by US consumers use Google.
20%
Grade Bof US consumers say they run local searches directly inside a maps app rather than a search box.
What it does not say One in five is the number that should change reporting behaviour: a rank tracker pointed at the web results is not watching where a fifth of the demand starts.
25%
Grade Cof US Gen Z consumers say social media is their primary way of searching for a local business.
What it does not say Graded down because the Gen Z subgroup of a 1,000-person sample is small, and the subgroup size is not published. Directionally useful, statistically thin.
47%
Grade Cof the first ten organic results for local searches were business websites, with 31% directories, 16% business mentions and 7% forums.
What it does not say A measurement rather than a survey, which is rarer than it should be — but the sample and query set are not published where the number is quoted.
What this means for how you measure visibility
A rank tracker pointed only at google.com is watching one of at least three surfaces these figures describe. One in five local searches, by BrightLocal's own count, starts inside a maps app rather than a search box — a surface with its own ranking behaviour and no shared reporting with most web rank trackers.
A quarter of Gen Z consumers say social platforms are their primary search surface, which is directional rather than precise but points the same way: visibility is fragmenting across surfaces faster than most reporting setups have kept up with. The wider set of figures on how people find businesses sits on the local search behaviour statistics page.
Before adding a fourth channel, most businesses would learn more from checking whether the two or three surfaces they already occupy are being measured at all.
The ranking factors everyone quotes are opinions, not measurements
This is the most consequential misunderstanding in local SEO, and it is not the fault of the people who publish the research. They are clear about what it is. The industry quoting them is not. The 2026 edition also, for the first time, shows the same panel scoring the same factors three years apart — which is more informative than any single year's ranking, because it shows what practitioners now believe matters more or less than they did in 2023.
47
Grade Blocal search practitioners are surveyed to produce the Local Search Ranking Factors report, scoring 187 factors across local pack, local organic, conversion and — new for 2026 — AI search visibility impact.
What it does not say The report is a careful aggregation of professional judgement and is presented as such. It is not a correlation study of ranking data, and a factor ranked first means 47 experienced people believe it matters — which is evidence, but of a different kind than a measurement. Published 6 November 2025.
| Factor | Score |
|---|---|
| Primary GBP category | 227 |
| Proximity of business address to the searcher | 225 |
| Keywords in the GBP business title | 223 |
| Physical address in the same city as the search | 213 |
| Business open at the time of the search | 189 |
| High numerical Google star rating | 181 |
| Address displayed on the GBP listing | 176 |
Aggregated 0–5 expert-panel scores across 47 respondents, not a measured ranking correlation. The report publishes an exact score per factor but does not publish category-level percentage weightings as text, only as an unlabelled chart image — those percentages are not reproduced here for that reason. Source: Whitespark, Local Search Ranking Factors 2026
What actually moved between 2023 and 2026
Whitespark has run this survey long enough to show trend, not just a snapshot, and the movement is more informative than any single year's ranking. Presence of GBP predefined services climbed 59 places, from 81st to 22nd. Keywords in GBP services rose 75 places. Proper hours set on GBP rose 64 places.
Business open at time of search is new to the top five entirely — three of the four fastest-rising factors have nothing to do with content or links and everything to do with whether a Business Profile has been filled in completely and kept current.
The same panel moved three factors down by a similar margin. Internal links from the GBP landing page fell 65 places to 110th. Linking out to authority sites fell 64 places to 177th. Volume of quality content on service pages fell 40 places.
None of the three vanished — they are still scored, and still worth doing for reasons beyond local pack placement — but the panel scored them as mattering meaningfully less to the local pack than it did three years earlier. Whitespark's own commentary alongside the data notes that review and behavioural signals grew in weight over the same period, while citation signals continued a slow decline.
What this means for where to spend an hour
The pattern across both sets of moves is the same: Google Business Profile completeness rose, and generic on-site signal-stacking fell. For a business with limited time, that argues for finishing the Business Profile — correct category, complete services list, accurate hours, a title that states what the business does — before writing another service page nobody asked for. The order to work through is set out in the Business Profile optimisation guide.
This is a panel's aggregated judgement about what correlates with placement, not a measured causal test, so treat it as a strong prior for where to start rather than a guarantee of what happens if you do it.
Position 1, 2 and 3 pull almost identical clicks — position 4 does not exist
Once a business is inside the three-result local pack, the fight for the very top slot matters less than most owners assume. The click data below is the clearest evidence of that, with a real limitation worth stating upfront: the organisation publishing it does not disclose its underlying sample.
17.6%
Grade Cof local pack clicks go to the position 1 listing, against 15.4% for position 2 and 15.1% for position 3 — a far smaller spread between the three than most owners assume.
What it does not say First Page Sage publishes the figures without a sample size, collection window or vertical breakdown, so treat the shape of the finding — three top positions clustered closely together — as more reliable than the precise decimal points.
Local pack click-through rate by position
Positions 1 through 3 pull within 2.5 percentage points of each other — the meaningful cliff is between position 3 and position 4, which this dataset does not track at all.
Scale 0–20%. Internal data; sample size, date range and vertical mix not published. Source: First Page Sage, Google Click-Through Rates by Ranking Position
What this means for where you compete
If position 1, 2 and 3 pull similar shares of clicks, chasing the top slot in a competitive category is frequently the wrong fight to pick. Getting into the pack at all — through category accuracy, proximity and profile completeness, the same factors driving the movement in the table above — does more for total clicks than winning first place once inside it. The equivalent figures for the map surface itself are collected on the Google Maps statistics page.
The exception is voice assistants and some map-app surfaces, which typically read out or surface only a single top result; that scenario is not covered by the dataset above, and is worth treating as a separate, unmeasured case rather than assuming the same narrow spread applies to it.
AI recommendations are far more selective than the local pack
The newest numbers in local search are also the best-documented, because the organisations producing them had to invent and publish a method. The scope limit matters more than usual here.
1.2%
Grade Aof locations were recommended by ChatGPT, against 35.9% appearing in Google's local 3-pack — roughly thirty times more selective.
What it does not say The scope is the catch, and it is a large one: these are multi-location brands, not independent local businesses. Whether a single-site business faces the same 30× selectivity is unmeasured, and it is not safe to assume it does.
58%
Grade Cof sources ChatGPT Search drew on for local queries were business websites, with 27% business mentions and 15% directories.
What it does not say Assistant behaviour changes with every model and retrieval update, so a 2024 citation-mix finding is closer to history than to a current benchmark.
45%
Grade Cof consumers say they have used ChatGPT or another generative AI tool to find or choose a local business.
What it does not say Self-reported AI usage is among the least reliable categories of survey data — people over-report novel technology use, and “have used once” and “rely on” collapse into the same answer.
What this means inside the FOUND → TRUSTED → CHOSEN framework
A 30× selectivity gap between what an AI assistant recommends and what the local pack shows means AI recommendation currently behaves like a harder, later filter — closer to being chosen than to being found — the distinction the FOUND → TRUSTED → CHOSEN framework is built on.
Optimising a Business Profile earns a place in the pack; it does not automatically earn a mention from an assistant deciding which single business to name out of the three or four it shows. What is currently known about influencing that decision is collected in the guide to local SEO for AI search.
Until a study measures independent, single-location businesses rather than multi-location brands, the safest reading is that AI recommendation adds a fourth surface to compete on, not a replacement for the first three.
What the evidence covers
Read the sample lines above in sequence. The consumer research is 1,000 US adults. The business research is 778 US owners and managers. The AI visibility research is predominantly US multi-location brands. The ranking factors survey is 47 practitioners weighted towards North America.
For a business in Jaipur or Pune, that is not a rounding error. Local discovery in India runs substantially through WhatsApp, Instagram and vertical intermediaries like JustDial and Practo — channels that do not appear in any of the studies above, because the surveys were not asking.
A US-derived figure for how consumers find local businesses is not slightly imprecise outside the US. It is measuring a different channel mix.
No substantial dataset on Indian local business digital presence was identified in the sources reviewed on 8 September 2026. That gap is the reason this site is running its own research, and the first studies are aimed directly at it.
The numbers that did not survive the trace
These appear in current statistics roundups. Each one fails on provenance, and quoting them transfers the failure to you.
46%
Do not citeof Google searches have local intent.
Traced to A Google employee's remark at the Secrets of Local Search conference, 2018.
The single most-quoted statistic in local SEO is a conference aside. There is no paper, no sample, no method and no population. BrightLocal, to its credit, attributes it exactly this way — everyone downstream drops the attribution and keeps the number.
76%
Do not citeof people who search for something nearby on a smartphone visit a business within a day.
Traced to Google / Ipsos MediaCT / Purchased, “Understanding Consumers' Local Search Behavior”, May 2014.
Twelve years old, and published in “2026 statistics” lists without a date. It predates mobile-first indexing, the local pack shrinking to three results, the Maps redesign and AI Overviews. Whatever it measured, it was not this search environment.
88%
Do not citeof consumers who run a local search on a smartphone visit or call a business within a day.
Traced to Origin not established in the sources reviewed on 8 September 2026.
Circulates constantly, usually uncredited or credited to another roundup. We could not trace it to a published study. That does not prove it is wrong; it does mean nobody quoting it can show their working, which is the same thing as unciteable.
2.7×
Do not citemore likely that customers consider a business reputable if it has a complete Business Profile.
Traced to Attributed to Google, no date or study published.
Google has published the claim but not the research behind it — no sample, no year, no method. It may well be true and it is directionally sensible. It is still a vendor claim about the vendor's own product, and should be quoted as one.
900%+
Do not citegrowth in mobile searches for phrases like “___ near me today/tonight”.
Traced to Think with Google, “How near me shopping searches have changed”, comparing July–December 2015 against July–December 2017.
This one genuinely traces to Google — the problem is the date, which almost nobody quoting it in a 2026 list includes. The underlying comparison is two years, ending in 2017, now recycled without its window for nine years running. It predates mobile-first indexing, the pandemic-era shift to online ordering, and AI Overviews; whatever “near me” search behaviour looked like across 2015–2017, it is not evidence about 2026.
93%
Do not citeof Google searches with local intent will include a Local Pack in the results.
Traced to BrightLocal's own Local Pack explainer page states the figure directly, with no citation, sample size or methodology given — even by BrightLocal itself.
Reproduced as an authoritative figure across dozens of “local SEO statistics” roundups, none of which can produce the underlying study, because the organisation that coined the number never published one. The Local Pack's dominance for local-intent queries is real and easy to observe by searching; the precise “93%” is not something anyone quoting it can currently show.
How this page is made and how to cite it
Each statistic was traced from the page quoting it to the organisation that produced it, and recorded only if that organisation could be identified. The full procedure, including how grades are assigned, is written up in the research methodology.
Where a study page publishes a sample size, survey window or method, those are reproduced above verbatim in substance. Where it does not, the entry says so rather than estimating.
Grades are assigned on provenance, not on whether the finding seems plausible. A number can be entirely correct and still be a C here, because the grade describes what a reader is able to verify.
Last verified: 8 September 2026. Reviewed quarterly, and figures are re-checked against their primary sources at each review rather than carried forward.
Preferred citation Parashar, S. (2026). Local SEO statistics, traced to source. shrutiparashar.com/statistics/local-seo/
Questions
- What percentage of Google searches have local intent?
- The widely-quoted figure is 46%, but it should not be cited. It traces to a remark by a Google employee at the Secrets of Local Search conference in 2018, with no published paper, sample size, methodology or population behind it. No substantial published study establishing a local-intent share was identified in the sources reviewed on 8 September 2026.
- How many small businesses have a website?
- In BrightLocal's SMB Marketing Report 2025, 40% of 778 surveyed US small and medium business owners and managers said they have a dedicated business website. The figure is self-reported rather than measured by crawling, and BrightLocal notes that some owners may count a social media page as a website. No large-scale crawl measuring actual website presence among local businesses was identified in the sources reviewed.
- Are local SEO ranking factors based on real ranking data?
- Mostly no. The industry's canonical reference, Whitespark's Local Search Ranking Factors, is an opinion survey of 47 invited local search practitioners scoring 187 factors. Whitespark presents it accurately as aggregated expert judgement. It is not a correlation study of ranking data, so a factor ranked highly means experienced practitioners believe it matters, which is a different kind of evidence from a measurement.
- What are the most important local pack ranking factors in 2026?
- By expert-panel score in Whitespark's 2026 report, the top individually-scored factors are primary GBP category, proximity of the business address to the searcher, keywords in the GBP business title, a physical address in the same city as the search, being open at the time of the search, a high numerical star rating, and the address being displayed on the profile. All seven are Business Profile and location signals rather than website content or backlinks.
- Do backlinks matter less for local pack rankings than they used to?
- According to the same expert panel, yes, relative to other factors. Between the 2023 and 2026 editions of Whitespark's survey, 'linking out to authority sites' fell 64 ranking-factor positions and 'volume of quality content on service pages' fell 40 positions, while three Google Business Profile completeness factors rose 59–75 positions over the same period. This is a shift in what 47 experts believe matters most, not a measured causal test — but it is a consistent enough pattern to change where a time-constrained business starts.
- What is the click-through rate for each position in the Google local pack?
- First Page Sage's internal data puts position 1 at 17.6%, position 2 at 15.4% and position 3 at 15.1% — a gap of only 2.5 percentage points across all three visible positions. The organisation does not publish its sample size or collection method, so the figures should be read as directionally reliable rather than precise, but the pattern — that reaching the pack matters more than which of the three spots you land in — is the more defensible takeaway.
- Is it true that 93% of local searches trigger a Google local pack?
- The figure circulates constantly, but its origin is BrightLocal's own Local Pack explainer page, which states it as a bare claim with no citation, sample size or methodology attached — including by BrightLocal itself. The Local Pack's dominance for local-intent queries is real and easy to observe directly; the precise 93% figure is not something any source repeating it can currently substantiate.
- Have 'near me' searches really grown by 900%?
- The figure traces to a genuine Google source — a Think with Google article comparing mobile searches for phrases like '___ near me today/tonight' across July–December 2015 against July–December 2017. It is real data, but it is a decade-old comparison window still being quoted in '2026' statistics roundups without its date attached, which makes it read as current growth rather than as history from before mobile-first indexing, AI Overviews or the pandemic-era shift to online ordering.
- Is it harder to get recommended by AI than to rank on Google?
- For multi-location brands, substantially. SOCi's Local Visibility Index 2026 analysed roughly 350,000 locations across 2,751 multi-location brands and found 1.2% were recommended by ChatGPT against 35.9% appearing in Google's local 3-pack — about thirty times more selective. The study covers multi-location brands rather than independent local businesses, so whether a single-location business faces the same selectivity is unmeasured.
- Why are most local SEO statistics from the United States?
- Because almost all of the primary research is commissioned by US-based software vendors surveying US consumers and US businesses. The major consumer studies in this field typically sample around 1,000 US adults. Applying those figures to markets where local discovery runs through WhatsApp, Instagram or regional directories is not a small imprecision — it measures a different channel mix entirely.
Related reading: how each grade on this page was assigned , local SEO across multiple locations , how to tell whether SEO is working , Google Business Profile statistics , Google Maps statistics .
For the numbers on adjacent topics, see the rest of the archive.
