Local SEO: the complete guide

Local SEO is not a smaller version of regular SEO. It runs on a different mechanic entirely: Google computes a local result relative to where the searcher is standing, which means there is no single ranking for “plumber” — there’s a ranking at one street corner, a different one four blocks away, and a different one again in the next suburb.

Most advice in this category ignores that mechanic and treats local SEO as regular SEO with a city name attached.

This guide doesn’t. It’s organised around the three questions a customer actually answers, in order, before they ever contact a local business — can I find you, do I believe you, can I reach you right now — and every claim that can be checked against real evidence links to where that evidence comes from, including the places where the industry’s confidence outruns its data.

Where a specialist topic — Google Business Profile, Maps, citations, schema, reviews, AI search — has its own dedicated guide on this site, this page covers what a business owner needs to make the right call, and points to the longer guide for implementation depth.

It’s also worth being honest about what “search” means before working through any of it, because the surface has fragmented faster than most reporting has kept up with. BrightLocal’s consumer research puts Google at 70% of general online search among US consumers — still dominant, but not the whole picture.

One in five US consumers now say they run local searches directly inside a maps app rather than a search box, a surface most rank trackers never touch. A quarter of Gen Z consumers say social media is their primary way of finding a local business, a figure worth reading directionally rather than precisely, given the size of the subgroup it’s drawn from.

A local SEO effort measured only against google.com is measuring one of at least three real surfaces. The FOUND section below covers the one with the deepest evidence base — the local pack — while flagging where the evidence for the others runs out.

Local SEO is three questions, not ten tactics

A local buying decision collapses into three questions, asked in that order: does this business exist for my search, do I believe what I’m looking at, can I act on it right now.

This site calls it the FOUND → TRUSTED → CHOSEN framework, and it organises the rest of this guide the same way it organises everything else here — because it’s the structure the evidence itself falls into, not a device imposed on top of it.

Almost the entire local SEO industry sells against the first question and reports on it obsessively — rank trackers, visibility scores, share-of-voice charts, all pointed at FOUND. The other two stages decide whether that visibility turns into a customer, and the evidence throughout this guide points at the same uncomfortable pattern repeatedly: most local businesses buy FOUND, are sold FOUND, and lose the money at CHOSEN.

A business ranking first with 4.9 stars that takes eleven hours to return an enquiry converts worse than a competitor ranking fourth who answers in four minutes — and almost nothing in conventional local SEO reporting would ever show you that. The full argument, and the scoring model behind it, is on this site’s FOUND, TRUSTED, CHOSEN framework page.

What follows works through each stage in turn, then covers what the evidence says is currently not worth the time — which is, on the record, rarer content than it should be in this category.

FOUND: what actually decides whether you exist in someone’s search

Google names three factors that decide local pack placement in its own guidance on improving local ranking — relevance, distance and prominence — without publishing their relative weights, and saying explicitly that it keeps the algorithm’s details confidential. That gap is exactly what the industry’s expert-opinion surveys try to fill, and understanding the difference between what Google says and what practitioners estimate is the single most useful piece of scepticism a business owner can bring to this topic.

The ranking-factor consensus is expert opinion, not measurement

The most-cited source here, Whitespark’s annual Local Search Ranking Factors report, surveys 47 local search practitioners who score 187 individual factors across local pack, local organic, conversion and — new for the 2026 edition — AI search visibility.

It is a careful, well-documented aggregation of professional judgement, and it says so itself. It is not a correlation study of Google’s actual ranking data. A factor scored highest means 47 experienced people believe it matters most — real evidence, but of a different kind than a measurement, and almost every site quoting the report drops that distinction.

With that caveat stated plainly, the panel’s 2026 scoring of the highest-weighted individual local pack factors reads like this:

Aggregated 0–5 expert-panel scores across 47 respondents. Source: Whitespark, Local Search Ranking Factors 2026, published 6 November 2025.

Five of the top seven are Google Business Profile fields a business controls directly. The practical implication: you cannot outrank proximity by working harder on content alone — a business four miles from a searcher is fighting real geography a page full of keywords doesn’t overcome — but almost everything else on that list is a profile field, not a content strategy.

One caveat on the third item: keywords in the business title score highly with the panel, and Google’s guidelines for representing your business on Google require the name to reflect the real-world name used on the storefront and website, without added taglines or keywords. The two are only compatible where the trading name genuinely contains the service. Full implementation detail for each of these lives in this site’s Google Business Profile optimisation guide and Google Maps SEO guide.

The finding that should redirect where most businesses spend an hour: completeness rose, content volume fell

Whitespark has now run this survey long enough to show trend rather than a single snapshot, and the movement between 2023 and 2026 is more informative than any individual year’s ranking. Three of the four fastest-rising factors on the entire 187-factor list have nothing to do with content or links, and everything to do with whether a profile has been filled in and kept current:

• 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.

The same panel moved three factors down over the same period, 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 falling factors vanished — they’re still scored, and still worth doing for reasons beyond local pack placement — but the same panel that once ranked them meaningfully now scores them as mattering considerably less to local pack placement than it did three years ago.

Read together, the pattern is unambiguous: Google Business Profile completeness rose, and generic on-site signal-stacking fell. For a business with an hour to spend, that argues for finishing the profile — correct category, complete services list, accurate hours — before writing another service page nobody asked for.

This is a panel’s aggregated judgement about what correlates with placement, not a measured causal test. Treat it as a strong prior for where to start rather than a guarantee of what happens once you do.

Position 1, 2 and 3 in the local pack pull nearly identical clicks

Once a business clears the bar to appear in the three-result local pack at all, the fight for the very top slot matters less than most owners assume. First Page Sage’s click-through data — a real limitation worth stating upfront: the organisation doesn’t disclose its sample, so treat the shape of the finding as more reliable than the precise decimals — puts position 1 at 17.6% of local pack clicks, position 2 at 15.4%, and position 3 at 15.1%.

That’s a spread of 2.5 percentage points across all three positions. Standard organic results behave completely differently: organic position 1 pulls roughly 39.8% of clicks against 10.2% for position 3, close to a four-to-one gap.

The practical implication: getting into the local pack at all does more for total clicks than winning first place once inside it, and chasing the top slot in a competitive category is frequently the wrong fight to pick.

The exception is voice assistants and some map-app surfaces, which typically read out or surface only a single top result — that scenario isn’t covered by this dataset and shouldn’t be assumed to follow the same narrow spread. Full detail, including how AI recommendation behaves entirely differently again, is on this site’s Google Maps statistics page.

The technical basics that quietly decide whether any of the above matters

None of the profile or ranking-factor work above helps if the underlying site has structural problems standing in front of it. Three are worth checking specifically, because their absence is common enough to still be worth naming rather than assumed solved.

Mobile usability — per this site’s local business website statistics, 16% of US adults are now smartphone-only internet users, which makes a poorly-rendering mobile site not an underperforming segment but an unusable one for a real, growing share of the market.

Page speed, particularly on mobile, where the evidence people quote is frequently older than they realise. Google’s own headline mobile-abandonment study is now roughly a decade old and shouldn’t be cited as a current figure, though the direction — slow costs visitors — hasn’t reversed. This site’s website conversion guide covers the more current controlled evidence.

HTTPS and a clean heading structure are table stakes rather than advantages at this point, but checking them costs nothing and their absence is still more common than it should be.

TRUSTED: reviews, citations and schema — proof, not presence

Being found gets a business into consideration. Whether that consideration turns into trust is a separate, evidenced question, and the evidence has moved faster here in the past year than almost anywhere else in local search.

The review bar is rising faster than most review programmes are

Per this site’s local review statistics, the share of consumers requiring at least 4.5 stars before they’ll consider a business nearly doubled year over year, from 17% to 31%.

Recency compounds the pressure: 74% of consumers say they only weigh reviews from the last three months, and the share weighing only the last two weeks specifically rose from 20% to 32% in a single year. A business with two hundred excellent reviews from three years ago and nothing recent is, by this evidence, closer to invisible on trust than the raw count suggests.

Responding matters as much as generating: 80% of consumers say they’re more likely to use a business that responds to all its reviews, not only the negative ones, and 50% say they actively avoid businesses whose responses read as generic and templated. A response that names something specific from the review, rather than repeating identical wording across dozens of them, is doing real work — not politeness for its own sake.

There’s a compliance dimension here that most review-request advice skips entirely, and it is routinely overstated in both directions. The FTC’s Rule on the Use of Consumer Reviews and Testimonials took effect on 21 October 2024 and is enforceable with civil penalties — the FTC Act maximum, adjusted for 2025, is $53,088 per violation.

What the Rule does not do is worth stating plainly, because a great deal of published advice gets it wrong. The FTC’s own questions and answers on the Rule say a business may ask for reviews only from customers it believes are happy. Simple review gating is not itself banned by this Rule, though the FTC notes it can still be deceptive under the broader FTC Act.

What the Rule does ban, at §465.7, is review suppression: using unfounded legal threats, physical threats, intimidation or false public accusations to get a review removed, and displaying a filtered set of reviews while materially misrepresenting that they represent most or all of the reviews submitted. The exposure sits in what a business shows, and in how it treats an unhappy reviewer — not in who it happens to ask.

The platform risk is separate and older. Google’s Maps user-generated content policy prohibits pressuring customers for reviews, requesting specific content, and incentivising reviews, and enforcement is visibly active: Google reports blocking or removing 292 million policy-violating reviews globally in 2025, against more than a billion published — roughly 22% of everything submitted.

The straightforward alternative — asking every customer the same way, at the same moment, regardless of the job’s outcome — sidesteps both risks, and is also the version consumers say they trust more once they notice a business’s reviews look suspiciously uniform. This site’s local review strategy guide covers the practical system for building that habit.

Citations: consistency now has to satisfy two different measurement systems

Citation building spent years being sold as a volume game, and the current evidence rejects that framing decisively — in two separate ways.

Whitespark’s 2026 panel scores twelve individual citation- and NAP-related factors, and a pattern holds without a single exception: every consistency factor outscores every pure quantity factor.

The single highest-scoring citation factor of all — ahead of every count-based factor on the list — is simply whether the NAP printed in a business’s own website HTML matches its Google Business Profile: a same-business accuracy check, not a measure of how many external directories list it.

Separately, and independently, a 2026 BrightLocal study of 60,970 structured prompts checked against 1,355 real business locations across Google AI Overviews, Google AI Mode and ChatGPT logged 1.9 million citations across 116,670 unique domains — a direct measurement of where AI systems actually pull business information from, not a guess. The finding: 93% of all domains cited across the three platforms were individual business websites, not directories or aggregators at all.

Two independent methods — a practitioner panel scoring ranking correlation, and an actual measurement of AI citation behaviour — arrive at the same place: a business’s own site accuracy is the highest-leverage citation asset it controls, for both systems.

Where the two systems diverge is worth knowing specifically. Google’s local pack and Google’s own AI surfaces lean heavily on Google’s own data, so Business Profile completeness carries real weight in both.

ChatGPT currently behaves differently — it draws disproportionately on Yelp through a confirmed 2026 OpenAI data-licensing partnership rather than an organic crawl of the wider web. A business that’s never actively claimed and maintained its Yelp listing is leaving a real, specific gap in how it appears to ChatGPT users, regardless of how complete its Google Business Profile is.

This site’s local citation building guide covers the full priority order this data actually supports, and documents several specific citation statistics — a “35% of Prominence” figure, a “2.3 positions lower” claim — that circulate attached to credible organisations’ names but don’t trace to any study either organisation has published.

Schema does a narrower job than most advice about it implies

Structured data has one genuine function: describing, in a format a machine can parse reliably, what a human visitor can already see. It is not, on the current evidence, a ranking lever or an AI-citation lever, and treating it as either is where most schema advice goes wrong.

Google’s own documentation frames it as an eligibility mechanism rather than a ranking one. Its local business structured data reference describes what marking a business up makes it eligible for — a knowledge panel with business details, a carousel of businesses related to the query — not a position it earns.

Whitespark’s 2026 panel scored “website content marked up in schema” at 49 out of a possible top score, in the bottom third of all 187 factors rated for local pack impact.

Two rich results local businesses were commonly told to chase are now gone entirely: FAQPage stopped producing a rich result in Google Search from 7 May 2026, and a self-serving AggregateRating built from curated testimonials on a business’s own homepage has never been eligible for the star review feature, by policy, regardless of how accurately it’s coded.

For AI citation specifically, the evidence is more direct and considerably less convenient for anyone selling schema as an AI-visibility service. A controlled Ahrefs test added JSON-LD schema to 1,885 pages already receiving 100+ AI Overview citations, tracked against 4,000 matched control pages over the following month, and found a small statistically significant decline in AI Overview citations, with changes on AI Mode and ChatGPT statistically indistinguishable from zero.

Google’s own Search Central guidance on appearing in AI features backs this directly: “There’s also no special schema.org structured data that you need to add.”

A widely repeated “44% AI citation lift from schema” figure, usually attributed to BrightEdge, does not trace to any locatable BrightEdge study — the real 44% figure from that organisation describes something entirely unrelated.

None of this makes schema worthless; it makes it a foundation to get accurate, not a growth lever to invest in expecting an AI-citation return. This site’s local business schema guide covers what to implement and, just as usefully, what to stop expecting from it.

CHOSEN: getting recommended, and getting answered

Being found and being trusted still leave the most commonly skipped question: does the business actually convert that trust into contact, and does someone answer when it does.

AI recommendation is a far harder filter than the local pack

SOCi’s Local Visibility Index 2026 ran a standardised prompt — “Can you recommend businesses of X type in Y market?” — across roughly 350,000 locations belonging to 2,751 multi-location brands. ChatGPT recommended 1.2% of the locations tested. Google’s local 3-pack featured 35.9% of the same locations for equivalent queries — a business appearing in Google’s local results roughly thirty times more often than it gets named by ChatGPT.

Gemini, grounded directly in Google Maps and Business Profile data, was the most generous of the three assistants tested at 11%, and the most accurate — 100% business-data accuracy against verified records, versus 68% for both ChatGPT and Perplexity.

The scope limit matters more than usual here: this dataset covers multi-location brands with existing digital infrastructure, not independent single-location businesses, and whether an independent business faces the same roughly-30× selectivity gap is unmeasured.

What the finding does establish, within its own scope, changes what “optimising for AI search” should mean. A 30× selectivity gap between what an assistant recommends and what the local pack shows means AI recommendation behaves like a harder, later filter, closer to being chosen than to being found.

Getting a profile into local-pack shape earns a place among the field Google surfaces; it doesn’t automatically earn a mention from an assistant choosing which one or two businesses to name out of everything it retrieved. This site’s local SEO for AI search guide works through the full evidence, including which factors the same Whitespark panel found actually correlate with AI citation — and it isn’t schema.

Getting recommended is worthless if nobody can act on it

None of the FOUND or TRUSTED work above produces a customer if the resulting click, call or message goes nowhere. Independent call-tracking data shows 56% of callers to a local business reach an actual person, and 38% of those become a qualified lead — meaning a website’s form conversion rate alone systematically understates total conversion wherever a meaningful share of visitors are tapping to call instead of filling anything in.

On the response side, the best available evidence on speed to lead — a study of 6 companies and over 100,000 call attempts — found businesses 100 times more likely to make contact with a lead responding within 5 minutes rather than 30, and 21 times more likely to qualify it.

This is the stage most local SEO reporting doesn’t measure at all, which is precisely why it’s the one this site’s framework names explicitly rather than leaving implicit. A business ranking first, with a strong rating, that takes hours to answer an enquiry is losing customers to a lower-ranked competitor who answers in minutes — and a rank tracker will never show you that loss, because it isn’t measuring that stage.

This site’s local business website conversion guide and lead response and follow-up guide cover the mechanics in full; the local business conversion rate statistics and lead response time statistics carry the underlying data. If you want to put a number on what a slow reply is costing, the lead value calculator does that arithmetic.

What not to waste time on

Most “complete guide” content in this category recycles the same recommendations because it’s summarising other guides rather than checking the evidence directly.

Two independent bodies of evidence — the same Whitespark panel used throughout this guide, and this site’s own tracing of the statistics that circulate about local SEO — point at a specific, non-obvious set of things that are lower priority than the industry’s default effort allocation suggests.

Generic content volume on service pages, per the movers-down data above, fell 40 places in the same panel scoring that saw profile-completeness factors rise. Linking out to authority sites fell 64 places. Internal links from the GBP landing page fell 65 places.

None of these are worthless — they’re still scored, and still contribute somewhere — but a business allocating its limited hours to writing another generic service page before finishing its Business Profile is optimising against the panel’s own measured direction of travel, not with it.

Chasing a specific citation count is a milder version of the same mistake. The one real correlation study on citation volume — an 85-citation average among businesses in local pack positions 1 through 3, from a 2018 BrightLocal study — measured an association between successful businesses and citation count, not a causal target. Building 85 citations on directories nobody uses won’t reproduce the reviews, relevance and links the businesses in that sample also had.

And a specific set of statistics — genuinely the most-quoted numbers in this entire category — shouldn’t be quoted at all, because none of them trace to a real, checkable source:

• “46% of Google searches have local intent” traces to a Google employee’s remark at a 2018 conference. No paper, no sample, no method, no population.
• “76% of smartphone ‘near me’ searchers visit a business within a day” is a real 2014 study, now routinely published without its date — it predates mobile-first indexing, the local pack shrinking to three results, and AI Overviews entirely.
• “88% of local searchers visit or call within a day” — origin not established in the sources reviewed for this guide. Circulates constantly, credited to nothing checkable.
• “2.7× more likely to consider a business reputable with a complete profile” is attributed to Google with no published study behind it — a vendor claim about the vendor’s own product.
• “900%+ growth in ‘near me’ searches” genuinely traces to Google, but the underlying window is July–December 2015 against July–December 2017 — a comparison ending nine years ago, now recycled without the dates that would reveal how old it is.
• “93% of local-intent searches show a local pack” appears on BrightLocal’s own site with no citation, sample or methodology even from BrightLocal itself, and no independent study anyone quoting it can produce.

Full detail on each, including how they’re worded and where they were actually traced to, is on this site’s local SEO statistics page. A statistic with no working link to its original source should be treated as untraceable, not merely unverified — the absence of a link is the finding, not an oversight to forgive.

Why this guide is built differently

Most “complete guide to local SEO” content on the open web is a summary of what other guides say, several layers removed from any original measurement.

This one is built the other way: every ranking-factor claim above traces to Whitespark’s published panel data, not a paraphrase of it; every citation claim traces to either that same panel or BrightLocal’s actual prompt-panel measurement of AI citation behaviour, not a repeated vendor line; every review statistic carries its sample size and date.

The section above exists specifically to name the numbers that don’t survive that standard, rather than quietly leaving them out and hoping nobody notices they’re missing from a “complete” guide.

That standard has a cost worth stating honestly. Several genuinely popular local SEO claims — a fixed timeline for results, a precise ranking-boost percentage from schema, a universal AI-search selectivity figure for single-location businesses — are excluded from this guide entirely, not because they’re necessarily false, but because no source using them discloses a method a reader could check.

Where that’s the case, this guide says so directly rather than repeating the number with a hedge attached. A page with fewer, honestly-sourced claims is more useful to a business owner making a real decision than one with more claims and no way to check any of them.

What to do first, in order

1. Audit and complete the Google Business Profile — primary category, hours, services, photos — because the evidence above says this is where practitioner-scored ranking weight has moved, not where it’s moving away from.
2. Fix NAP consistency between the website and the Business Profile specifically, before chasing directory volume — it’s the single highest-scoring citation factor measured, and it separately predicts AI citation.
3. Build a review request habit into the actual workflow, asked the same way of every customer regardless of outcome — both because consumer expectations on recency have moved fast, and because a uniform ask keeps you clear of Google’s platform policy and of the FTC’s suppression provisions at the same time.
4. Check the site works on mobile and loads reasonably fast, and that a phone number is a genuine tappable link — this blocks everything downstream if it’s broken, regardless of how well the steps above are done.
5. Claim and maintain Yelp specifically, given its outsized and currently confirmed role in ChatGPT’s citation behaviour, alongside the Google Business Profile work that already covers the local pack and Gemini.
6. Build genuine service and location pages only where a real difference exists to describe — content volume for its own sake is exactly the factor the current evidence says matters less than it used to, not more.
7. Fix response time and the mechanics of contact — click-to-call, form friction, a defined follow-up sequence — because visibility and trust both go to waste against a business that doesn’t answer.
8. Track visibility from within the areas actually served, using a grid rather than a single point, and track it against enquiry and response data, not rank position alone — a business scoring well on FOUND while losing at CHOSEN is the single most common, least measured failure this guide’s evidence points to.

Working through that list in order is itself the three-stage diagnostic in miniature: establish where visibility actually stops, then where belief stops, then where contact stops.

None of it is a project with an end date. Categories drift, competitors add reviews, and the response habit decays the month nobody owns it — which is why this is the kind of work that runs as an ongoing programme rather than a one-off engagement. If you would rather model the return before committing to that, the local SEO ROI calculator takes your own numbers.

For multi-location specifics — tracking without a national average hiding the branch in trouble, building location pages that don’t compete with each other — see local SEO across multiple locations.

Questions

What is local SEO?

The practice of making a business more visible for searches tied to a place — a city, a neighbourhood, or 'near me' — across Google's local pack, Maps, standard organic results and, increasingly, AI-generated answers. It differs from general SEO in one structural way: Google resolves a local result relative to where the searcher is standing, so there is no single ranking for 'plumber', only a ranking that varies by the searcher's location.

How is local SEO actually different from regular SEO, beyond 'it has a map on it'?

The mechanic. Regular organic search computes one ranking per query, roughly consistent for everyone who types it. Local search computes a different ranking for every point a search happens from, weighted heavily by proximity — a factor no amount of content or link-building can move. That single difference is why local SEO needs its own playbook rather than a general SEO guide with a city name inserted.

How long does local SEO take to show results?

There's no reliable published study answering this precisely for local businesses. Most of what circulates as a fixed timeline — three months, six months — is folklore rather than measurement, and no source that quotes a specific figure discloses a method behind it. What's structurally true: Google Business Profile and citation fixes can show up within days to weeks, because they change what's already indexed, while content and link-building effects compound more slowly, over months. Treat any source quoting a single fixed number with real scepticism.

Is local SEO worth it for a small business?

For most businesses that depend on customers finding them locally, rather than through referral, foot traffic or a marketplace app, yes — the realistic alternative is paying for every customer through ads indefinitely, or being invisible to search behaviour that increasingly starts inside a maps app or a social platform rather than a search box. See this site's local search behaviour statistics for the underlying consumer data.

Do I need a website for local SEO, or is a Google Business Profile enough?

A Google Business Profile alone limits what you can rank for and what you can prove — pricing detail, credentials, service-specific pages, proof of work. Per this site's local business website statistics, 40% of US small businesses report having no dedicated website at all, and that gap correlates with limited visibility beyond the local pack itself. A profile gets you found; a website is most of what lets someone decide to trust and act.

What actually decides local pack rankings, and how much of it can a business control?

Google names three factors itself — relevance, distance and prominence — without publishing their relative weights. Distance can't be moved: a business four miles from a searcher is working against real geography. Relevance (an accurate, complete, well-categorised profile) and prominence (reviews, citations, links, overall web authority) are both controllable, and between the two, profile completeness has risen sharply in what practitioners believe matters most since 2023.

Are the ranking-factor lists and statistics that circulate about local SEO reliable?

Some are, most aren't, and the difference is traceability. The best of them, Whitespark's annual practitioner survey, is a genuine, well-documented aggregation of expert judgement — clearly labelled as opinion by the people who publish it. A large share of the rest, including the most frequently quoted local-SEO statistic of all (46% of searches have local intent), trace to a conference remark, a nine-year-old study, or nothing at all. This site's local SEO statistics page documents six specific examples with their origins traced.

Does schema markup improve local SEO or help a business get cited by AI assistants?

It doesn't move rankings directly, by Google's own guidance, and Whitespark's 2026 practitioner panel scored it in the bottom third of 187 local ranking factors. For AI citation specifically, a controlled Ahrefs test that added schema to 1,885 already heavily-cited pages found a small decline for Google AI Overviews and no measurable effect on AI Mode or ChatGPT. Schema still matters for what it's actually built for — helping a machine correctly parse content that's genuinely on the page — see this site's schema markup guide for what that means in practice.

How important are reviews to local SEO in 2026, compared with a few years ago?

The consumer bar has moved faster here than almost anywhere else in local search. The share of consumers requiring at least 4.5 stars before they'll consider a business nearly doubled year over year, from 17% to 31%, and 74% now weigh only reviews from the last three months. Reviews also feed the prominence factor in ranking directly. A review programme that produces a trickle occasionally is falling behind consumer expectations faster than most businesses realise.

Should I optimise for AI search separately from Google's local pack?

Yes, as an additional surface, not a side-effect of good local SEO. ChatGPT recommends roughly thirty times fewer businesses than appear in Google's local pack for equivalent searches, and fewer than half of the businesses leading Google's local rankings also turn up in AI-generated recommendations for the same query. What predicts AI citation — third-party mentions, expert 'best of' lists, review-site authority — is a genuinely different priority list from what predicts a local pack placement, and it sits closer to the TRUSTED and CHOSEN stages than to FOUND.

What's the single biggest mistake local businesses make in local SEO?

Treating the Google Business Profile as a one-time setup task instead of a maintained asset, while spending disproportionate effort on content volume the evidence increasingly says matters less. The practitioner data behind this guide shows profile-completeness factors rising sharply in weight between 2023 and 2026 while generic on-site content volume and outbound linking fell — the opposite of where most local SEO effort still concentrates.

How do I know if my local SEO is actually working?

Track visibility from within the area you actually serve, using a grid of points rather than a single check from your own office, because a local ranking has a shape rather than one position. Then track it against what happens after someone finds you — enquiry rate, response time, close rate — not rank position alone, since a business that ranks first and answers slowly loses to a business that ranks third and answers in minutes. See this site's FOUND, TRUSTED, CHOSEN framework for the full diagnostic.