Statistics
Local search behaviour statistics, traced to source
The consumer decision journey from search to contact — multi-channel sequencing, what changes between browsing and choosing, and why more than half of searchers examine a business and walk away without a word.
Local search behaviour research answers a different question from ranking-factor research: not 'what makes Google show a business' but 'what does a person actually do before they call someone.' This page's territory is specifically the decision journey: which channels a search actually touches, what changes between a person's first look and their final choice, and why a large share of searches end in silence rather than contact.
Where a search starts is covered in more depth on this site's local SEO statistics page; this page picks up from there. Almost everything reliable on the decision-journey question comes from one recurring BrightLocal survey programme, now in its 2026 edition — split into two companion reports rather than one combined page, both drawn from the same 1,227-person panel.
The findings below cluster around one theme: the single-channel, single-session model of local search that most tools are built to measure describes a minority of real consumer behaviour, and what gets a business noticed is measurably not always what gets it chosen.
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Do not cite
Untraceable, undated, or superseded by later changes to the thing it measured.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.
Consumers rarely use just one channel to find a local business
The single-channel model most reporting is built on — a customer searches Google, clicks, converts — describes a minority of the actual journey, and is the assumption the complete local SEO guide works against throughout. The channel a search starts on and the channels it actually touches before a decision gets made are two different questions, and the gap between them is the more useful number.
52%
Grade Bof consumers say their most recent local business search started on Google Search, with a further 9% starting directly on Google Maps.
What it does not say Social media (9%) and AI tools (8%) are the next-largest single starting channels, accounting for a further 17% between them. The remaining roughly fifth of searches start on review sites, Apple Maps or voice search, none of which is broken out individually at this sample size — treat 'a small residual cluster' as the honest description rather than inventing a precise split.
75%
Grade Bof consumers say they used more than one channel during their most recent local business search.
What it does not say This is the finding most single-channel attribution models can't account for. Three in four consumers are checking Google, then a review site, then possibly Instagram or a business's own site, before ever converting. Attributing the resulting lead to whichever channel happened to be last is a common and material distortion.
43% and 39%
Grade Bof consumers who started their search on an AI tool went on to check Google (43%) or look at social media (39%) before deciding — only 2% used the AI tool as their sole channel.
What it does not say Read against the industry narrative that AI assistants are quietly replacing search: this survey's own respondents describe the opposite behaviour. Starting on ChatGPT or a similar tool overwhelmingly means starting there, then verifying somewhere else — the same pattern BrightLocal separately measures on the local reviews side, where a large share of AI users say they fact-check a recommendation against native reviews before acting on it.
What this means for how you measure a channel's contribution
A rank tracker or ad dashboard built around last-click attribution is answering a narrower question than most businesses think it is answering.
If three in four searches touch more than one channel, and a plurality of AI-tool starters end up back on Google before deciding, crediting the final click with the whole outcome routinely misattributes work done earlier in the sequence — the AI mention that got the business considered at all, or the Google Maps listing that made it plausible before the review site made it trusted.
The practical fix is not a bigger attribution tool; it is treating each channel's job as different from the others' rather than competing for the same credit — one earns consideration, another builds trust, a third closes the enquiry, and a dashboard that only counts the third is blind to the first two.
One question this page could not answer with sampled data is whether the same consumer switches devices — researching on a phone, say, then converting on a desktop — during a single local-business search specifically.
General e-commerce research on cross-device switching exists, but the figures circulating for it vary sharply by source (from roughly two-thirds to over 90% of shoppers, depending on which report is quoted), none of it segmented for local-business search specifically, and none meeting this site's sourcing bar for a precise, citable number.
No substantial, sampled study measuring device-switching within a single local business search specifically was identified in the sources reviewed on 8 September 2026. What's measurable instead, and used throughout this page, is which named channels a search touches — which is a real and different question from which physical device it happens on.
Maps, AI tools and voice search behave as different surfaces — and voice search's real 2026 footprint is smaller than the figures still being quoted for it
This section covers two separate things: surfaces most rank-tracking tools don't watch, and one specific category of statistic — voice search — that circulates constantly at figures an actual 2026 survey no longer supports. Both are cases of the measurement problem set out in how to tell if your SEO is working.
9%
Grade Bof consumers say their most recent local search started directly inside Google Maps, rather than a search engine box.
What it does not say A business tracking only its web-search rankings has no visibility into this slice of the market — Maps-native search behaves differently and isn't captured by a standard rank tracker pointed at Google's web results. Among consumers who started on Google Search itself, a further 29% also checked Google Maps during the same journey, so the two surfaces overlap as much as they compete.
8%
Grade Bof consumers say their most recent local search started on an AI tool such as ChatGPT.
What it does not say This is a narrower, more specific measurement than 'have you ever used AI to find a business' figures quoted elsewhere (see the AI local search statistics page), because it asks about the actual starting channel of one specific recent search rather than usage in general. The two kinds of question produce different numbers for a reason — general-usage questions tend to run higher than specific-instance questions, in this category as in most self-reported survey data.
What voice search actually looks like in the newest available data
Voice search for local business is the category most likely to be quoted at a figure nobody currently measuring it would recognise.
The two numbers still circulating everywhere — that roughly 58% of consumers have used voice search to find a local business, and that 46% do so daily — trace to a real, named BrightLocal study, not a fabrication. The problem is the date: that study ran in April 2018, on a sample of 1,012 US consumers, and BrightLocal has not repeated it at that scale since.
Eight years of AI Overviews, smart-speaker market maturation and search-behaviour change separate that number from 2026, and almost none of the "2026 voice search statistics" pages currently citing 58%/46% mention the year the underlying data was collected. It is documented in full, with its origin traced, in the do-not-cite section below.
What the current, actually-2026 data shows instead: in BrightLocal's own newest survey (n=1,227, July 2026), voice search doesn't even register a large enough starting-channel share to be broken out individually — it sits inside a small residual cluster with review sites and Apple Maps, together accounting for a minority of first searches. The channel absorbing attention instead is covered on this site's AI local search statistics page.
That a rigorous, well-resourced 2026 survey no longer isolates voice search as its own line item is itself informative: it suggests the behaviour either never reached the scale the 2018 figures implied, or has receded since as search habits consolidated around typed and AI-chat queries. Either way, a business budgeting specifically for "voice search optimisation" against an 8-year-old 46%-daily-usage figure is very likely solving a problem with a size that no current study supports.
Search device use varies more by age than by generation label — and the gap is wide
'Gen Z searches differently' is the popular framing. The actual 2026 data breaks cleanly by age band, and the pattern inside it is less a story about young people preferring newer channels than about the middle of the age range being the most mobile-committed of all.
86%
Grade Cof 30–44 year-olds say their most recent local search happened on a mobile device — the highest of any age band, ahead of 18–29 year-olds.
What it does not say Graded down because the per-age-band subgroup size isn't disclosed, per this site's standard for any subgroup finding — the same caveat applied to every age-segmented figure below. The full breakdown: 18–29 at 71% mobile, 30–44 at 86%, 45–60 at 77%, and 60+ at 57%, against a 73% overall average. The 30–44 band, not the youngest one, is where mobile-only search behaviour is most concentrated.
25%
Grade Cof US Gen Z consumers say social media is their primary method for searching for a local business, against a 14% average across all consumers.
What it does not say Graded down specifically because the Gen Z subgroup size within the 1,227-person total sample is not disclosed. Directionally consistent with the age-band mobile-use data above and with last year's edition of the same finding, which strengthens confidence in the direction even without a published subgroup n.
What this means for who a mobile-first design actually serves
Treating "mobile-first" as a concession to younger customers specifically gets the shape of the data backwards. The 30–44 age band is the most mobile-committed of the four measured, ahead of 18–29-year-olds, and even the 60+ band — the least mobile of the four — still runs a majority mobile share at 57%.
A business's mobile experience is not a youth-outreach line item; across every age band this survey measured, it is closer to the default channel than to an alternative one, which changes the calculation for anywhere a business still treats its desktop site as the primary version and mobile as an afterthought. What a mobile visit then has to do is the subject of the local website conversion guide.
Most consumers decide which business to contact faster than businesses assume
This has a direct practical implication: the content and proof a business shows in the first few seconds of a visit is disproportionately what decides the outcome, because there usually isn't time for a second impression to correct a bad first one.
30 minutes
Grade Bis the window within which most consumers say they decide which local business to use, once they start looking.
What it does not say More than a quarter of respondents decide in under five minutes — the 30-minute figure is the outer bound most people fall within, not the typical experience, which for a substantial minority is considerably faster.
72%
Grade Bof consumers say they look at three or fewer businesses before deciding.
What it does not say Combined with the local-pack click-through data on the Google Maps statistics page, this suggests the effective competitive set for most local searches is genuinely small — often the pack of three, not page one of ten results.
What this means for what a page needs to prove, and how fast
A 30-minute outer bound and a shortlist of three or fewer together describe a narrow, fast-closing window in which a business either supplies the specific proof a visitor is looking for or loses the decision to whichever competitor did. How often that window closes in a business's favour is measured on the local conversion rate statistics page.
The next section breaks down exactly what that proof consists of — and shows that what a person checks first is not always what actually decides the outcome.
What gets a business shortlisted is not quite what gets it chosen
BrightLocal's 2026 decisions report asks the same panel two related but distinct questions: what do you check first when researching, and what actually made you pick the business you contacted. The two rankings share the same handful of factors, but the factors move places between them — and one factor's collapse is the most useful single finding on this page.
| Factor | At research stage | At final decision |
|---|---|---|
| Address / proximity | 44% | 27% |
| Star rating | 38% | 27% |
| Number / quality of reviews | 37% | 30% |
| Complete, accurate listing information | 34% | 32% |
| Clear pricing or a deal/offer | 30% | 29% |
n=1,227 US adults, published 15 July 2026. 'Research stage' asks what consumers look at first when scanning results; 'final decision' asks what actually made them contact the business they chose. The two questions have different full answer sets (research stage also includes photos, category and search position; final decision also includes referrals, response speed and website quality) — this table shows only the five factors both questions measured directly, to make the comparison exact rather than approximate. Source: BrightLocal, Consumer Search Behavior 2026: Decisions
25%
Grade Bof consumers cite a friend or family recommendation as a reason they chose the business they contacted — a factor the research-stage question doesn't ask about at all, because it happens outside any search platform.
What it does not say A quarter of final decisions carry an offline referral component that no amount of on-platform optimisation touches directly — though a strong online presence is plausibly what lets a referral get confirmed rather than second-guessed once someone actually searches the name.
22%
Grade Bof consumers cite the business responding quickly to an initial enquiry as a reason they chose it — tied with simply recognising the business name.
What it does not say This is a factor a consumer can only judge after making first contact, which means it operates entirely downstream of everything else on this page — the business already had to be found, trusted enough to contact, and then it had to actually answer.
What this means: proximity gets you noticed, it doesn't get you chosen
Proximity is the single largest factor at the research stage, cited by 44% of consumers scanning initial results — comfortably ahead of star rating and review count. By the final decision, it has fallen to 27%, tied for fourth alongside star rating, and behind both review count (30%) and complete listing information (32%), which barely moved at all between the two stages.
The pattern across all five shared factors is the same: proximity is the only one that loses meaningful ground between being noticed and being chosen — reviews and complete information hold their weight, or gain it.
The practical reading is not that proximity stops mattering — it is still cited by more than a quarter of consumers at the point of decision, and Whitespark's practitioner-ranked local-pack factors, covered on the local SEO statistics page, still place proximity of address near the very top of what determines whether a business appears at all.
What this data adds is the next step: getting into someone's initial shortlist because you're nearby does not carry through to being the one they contact, if the listing that comes up next to yours has better reviews and more complete information — the completeness half of which is what the Google Business Profile optimisation guide is for.
Proximity is closer to an entry ticket than a deciding vote — and a business a few streets further away with a stronger profile is, by this data, a live competitive threat even inside what feels like a locked-in local geography.
More than half of consumers examine a business and decide not to contact it — mostly for reasons that are fixable
Everything above describes who wins a search. This section describes the more common outcome for any individual business shown to a searcher: not being contacted at all, for a specific, nameable reason.
52%
Grade Bof consumers say they've looked at a local business online and then decided not to contact it.
What it does not say This reframes what a business appearing in search results is actually up against: being found is table stakes, and for a slight majority of consumers, being found has already led to a silent rejection at least once.
62%
Grade Bof consumers who were put off by a business cite a reason connected to review inactivity — negative reviews (33%), a low star rating (30%), too few reviews (24%), or out-of-date reviews (21%).
What it does not say The four reasons summing to 62% are counted separately in the underlying survey and a single respondent can cite more than one, so this is a category-level read rather than a strict percentage of respondents citing exactly one cause — the underlying pattern (review-related signals dominating the reasons people walk away) is what the figure is meant to convey.
| Reason cited | Share of consumers |
|---|---|
| Negative reviews | 33% |
| Unclear pricing or no offers | 32% |
| Low star rating | 30% |
| Few or no reviews | 24% |
| Out-of-date reviews | 21% |
| Missing or incorrect listing information | 20% |
| Couldn't find a website | 18% |
| Listing looked abandoned or unclaimed | 16% |
n=1,227 US adults, published 15 July 2026. Respondents could cite more than one reason, so columns do not sum to 100%. Source: BrightLocal, Consumer Search Behavior 2026: Decisions
What this means for where to spend an afternoon
Every reason in the table above is a maintenance failure, not a strategic one — nothing on the list requires a new campaign, a rebuilt website or a bigger budget. Six of the eight are directly about reviews (negative, low-rated, too few, out of date) or about basic listing hygiene (missing information, no findable website, a profile that reads as abandoned).
This site's local reviews statistics page covers the review-management side of this in full — how fast a response needs to land, how quickly old reviews stop counting toward a consumer's judgement — and the overlap with the reasons people walk away here is not a coincidence; it is the same underlying behaviour measured from two different angles.
A business asking "why aren't more people contacting us" rarely needs a new acquisition channel before it has ruled out the possibility that people are finding it and quietly leaving.
Checking that costs nothing but an honest look at your own listing through a stranger's eyes: are the reviews current, is the pricing information visible without a phone call, does the profile look actively run — the FOUND → TRUSTED → CHOSEN framework sets out the order to check them in.
Fixing what's on this list is a smaller, cheaper, faster project than most of the alternatives a business considers instead.
What decides a search varies by what's actually being searched for
A locksmith at 11pm and a couple choosing a kitchen remodeler are both 'local searches', and treating them as the same behaviour is one of the more common category errors in local search advice. The clearest available evidence segments by industry rather than by urgency directly — but the pattern that emerges lines up closely with what an urgency-based split would predict.
48%
Grade Cof consumers searching in food & drink or health & medical categories cite proximity as a top decision factor — the highest of any industry segment measured, and well above the 27% cross-category average.
What it does not say Graded down because, as with the age-band breakdowns above, per-industry subgroup sizes aren't disclosed. Both categories share a plausible mechanism for proximity mattering more: a meal or a same-day appointment is usually wanted nearby and soon, which is a reasonable, though not directly tested, proxy for search urgency.
40%
Grade Cof consumers searching for professional services cite the number of reviews as a top factor — the highest weighting of any category — while proximity drops to just 29%, the lowest of the segments measured.
What it does not say Professional services — the report's examples run toward accountants, lawyers and consultants — sits at the opposite end of the proximity spectrum from food & drink and health & medical, and is the category where review volume carries the most weight of any segment measured.
What this means for tailoring a profile to what's actually being bought
Trades and home-services searches complete the pattern from a third angle: BrightLocal's report describes star rating and review count as carrying more weight for this category than for any other measured, and pricing clarity as a specifically elevated factor too, with 36% of trades customers citing it against a lower cross-category average — though the exact review-weight percentage for this category isn't published as a number, only described qualitatively as the highest of the set.
Read together, the three segments sketch a rough but sensible spectrum: proximity-and-speed dominated at one end (food & drink, health & medical — the categories closest to genuinely urgent, same-day need), and price-and-trust dominated in the middle (trades and home services, where the job is often needed soon but the choice of who does it still gets weighed).
Review-and-reputation factors dominate at the far end (professional services, the category with the longest relationships and the least tolerance for getting the choice wrong). Reading a category's dominant factor as a statement about what the searcher actually wants is the argument made in search intent is a business question.
No study identified in the sources reviewed on 8 September 2026 segments local search behaviour by urgency directly — emergency call-out versus considered purchase, measured as its own variable rather than inferred from industry category.
The industry-level data above is the closest verifiable proxy available, and the direction is consistent with what an urgency-based framing would predict, but a business drawing a precise conclusion about, say, same-day plumbing search behaviour specifically should treat this as a reasonable inference from adjacent data, not as a direct measurement of urgency itself.
A similarly unanswered question is whether local-intent search volume itself follows a predictable time-of-day or day-of-week pattern — whether, for instance, searches for emergency services cluster in evenings and weekends while considered-purchase searches cluster in weekday business hours.
Phone-tracking platforms such as CallRail publish tools that let an individual business see its own call-volume pattern by day and hour, but no publicly published, sampled study aggregating that pattern across local businesses or industries was identified in the sources reviewed on 8 September 2026.
A business wanting this answer for itself currently has to measure it directly from its own call and enquiry data — there isn't yet a published industry benchmark to check it against.
What the evidence covers
Every figure on this page describes US consumer behaviour. Search behaviour in markets where WhatsApp, Instagram and vertical directories carry more of the discovery load — India prominent among them — is not represented in any study cited here, and no equivalent published research for those markets was identified in the sources reviewed on 8 September 2026.
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.
58% / 46%
Do not citeof consumers have used voice search to find a local business (58%), and use voice search for local business information daily (46%).
Traced to BrightLocal, Voice Search for Local Business Study, published 26 April 2018, based on a representative sample of 1,012 US-based consumers surveyed that same month.
A real, named, sampled study — the failure here is entirely about the date, not the source. Eight years on, this remains the single most-quoted voice-search figure in local SEO content, almost always presented without its year. BrightLocal has not repeated the study at this scale since, and the organisation's own newest local-search-behaviour survey (2026, n=1,227) doesn't even break voice search out as an individually reported starting channel — it folds into a small residual cluster with review sites and Apple Maps. A study that size no longer isolating voice search on its own is itself evidence against treating a 2018 daily-usage figure as current.
78%
Do not citeof local-mobile searches result in an offline purchase, usually within a few hours.
Traced to comScore, Neustar Localeze and 15 Miles, 7th annual Local Search Study, survey of roughly 5,000 US adults conducted December 2013, reported via Search Engine Land in 2016.
A thirteen-year-old figure recirculated in current 'local search statistics' roundups without its collection date attached. It is one of at least three closely related zombie figures measuring roughly the same claim at different values — this site's local SEO statistics page separately documents a 76% version (Google/Ipsos MediaCT, 2014) and an untraceable 88% version of what is functionally the same underlying question. That the same claim drifts between 76%, 78% and 88% depending on which decade-old syndication is quoted is itself a sign none of the specific percentages should be treated as precise, whatever the shared direction of the finding might once have been.
79–90%
Do not citeof consumers switch between devices during a purchasing journey.
Traced to Circulates across marketing blogs citing each other, with the specific figure moving between roughly 67% and 90% depending on the source, none of them specific to local-business search.
No version of this claim traced to a named, dated, local-search-specific study during the research for this page. The figures that do exist are general e-commerce cross-device statistics, several years old, without a consistent methodology or sample disclosed at the point the number is quoted — the same drift pattern documented elsewhere on this site's do-not-cite lists. Directionally plausible that some cross-device switching happens during local searches; not a number this page's sourcing bar allows citing as a fact about local search specifically.
How this page is made and how to cite it
Most figures on this page trace to BrightLocal's 2026 Consumer Search Behavior programme, published as two companion reports — 'Channels' (9 July 2026) and 'Decisions' (15 July 2026) — both drawn from the same representative panel of 1,227 US adults who had searched for a local business in the prior three months. Where a subgroup figure (age band, industry category) doesn't disclose its own sample size within the total, that is stated explicitly and the grade reflects it.
Last verified: 8 September 2026. Reviewed quarterly, and re-checked in full whenever the underlying survey publishes a new edition.
Preferred citation Parashar, S. (2026). Local search behaviour statistics, traced to source. shrutiparashar.com/statistics/local-search-behaviour/
Questions
- Do consumers use more than one channel to find a local business?
- Yes — 75% of consumers say they used more than one channel during their most recent local business search, per BrightLocal's Consumer Search Behavior 2026: Channels report (n=1,227 US adults, published 9 July 2026). This is a significant problem for last-click attribution models, which credit whichever channel happened to be used last rather than the combination that actually influenced the decision.
- Where do most local searches actually start?
- 52% of consumers say their most recent local search started on Google Search directly, with a further 9% starting on Google Maps, 9% on social media and 8% on an AI tool, per BrightLocal's 2026 survey (n=1,227). The remaining roughly one-fifth starts across review sites, Apple Maps and voice search, none large enough on its own to be reported as a separate figure at this sample size.
- Do people who start a search on ChatGPT or another AI tool go anywhere else afterwards?
- Almost always. Only 2% of consumers who started their local search on an AI tool used it as their only channel — 43% went on to check Google and 39% looked at social media before deciding, per BrightLocal's 2026 survey (n=1,227). Starting a search on an AI assistant appears to function as a first step in a longer journey rather than a replacement for it.
- Is voice search still a meaningful way people find local businesses?
- The specific figures still being quoted for it — 58% of consumers have used voice search for local business information, 46% use it daily — trace to a real BrightLocal study, but one run in April 2018 on 1,012 US consumers and never repeated at that scale since. BrightLocal's own current 2026 survey (n=1,227) doesn't report voice search as an individually measured starting channel at all — it sits inside a small residual cluster with review sites and Apple Maps. Treat any 2026 content quoting the 58%/46% figures without their 2018 date as working from stale data.
- How many businesses do consumers actually compare before deciding?
- 72% look at three or fewer, and most decide within 30 minutes of starting to look — more than a quarter decide in under five minutes — per BrightLocal's Consumer Search Behavior 2026: Decisions report (n=1,227, published 15 July 2026). The practical implication is that whatever a business shows in the first few seconds of a visit carries outsized weight, because there usually isn't a second visit to correct a bad first impression.
- Does what people check first when researching a business match what actually makes them choose it?
- Not exactly, and proximity is where the two diverge most. 44% of consumers cite address or proximity as a top factor when first scanning results, but only 27% cite it as a reason they actually chose the business they contacted — a bigger drop than any other shared factor, per BrightLocal's 2026 Decisions report. Reviews and complete listing information, by contrast, hold roughly steady or grow between the research stage and the final decision. Being nearby earns a look; it doesn't reliably earn the contact.
- How often do people look at a business online and then decide not to contact it?
- 52% of consumers say they've done this, and 62% of those cite a reason connected to reviews — negative reviews, a low rating, too few reviews, or reviews that look out of date — per BrightLocal's 2026 Decisions report (n=1,227). Being found is not the same as being chosen; for a slight majority of searchers, being found has already led to at least one silent rejection.
- Does what decides a search vary by industry?
- Yes, in a pattern that roughly tracks urgency. Food & drink and health & medical searches weight proximity most heavily (48%, against a 27% cross-category average for the final decision), professional services weight review count most heavily (40%) while proximity drops to its lowest measured share (29%), and trades/home services weight star rating, review count and pricing clarity above average. No study identified in the sources reviewed on 8 September 2026 segments local search behaviour by urgency directly — this industry-level data is the closest verifiable proxy, and the direction is consistent with what an urgency-based split would predict, but it isn't a direct measurement of urgency itself.
- Is there good data on what time of day or day of week local searches happen?
- No substantial, published, sampled study aggregating local-intent search or call volume by time of day or day of week across businesses or industries was identified in the sources reviewed on 8 September 2026. Individual phone-tracking platforms let a business see its own call pattern by hour and day, but there isn't yet a public benchmark to compare that pattern against. A business wanting this answer currently has to measure it from its own enquiry data.
- Does research show people switch devices — say, phone to laptop — during a single local search?
- Not with a number this page can verify. General e-commerce research on cross-device switching exists, but the figures quoted for it vary widely by source (roughly two-thirds to over 90%, depending on which report is cited), none of it specific to local-business search or meeting this page's sourcing bar for a precise figure. What is measurable, and used throughout this page instead, is which named channels — Google, Maps, social, AI tools — a search touches, which is a related but different question from which physical device it happens on.
Related reading: our research methodology , Local SEO statistics , local reviews statistics , Google Maps statistics .
Every figure here is graded the same way as the rest of the research archive — source, sample, method and date.
