Local SEO Statistics UK 2026

Statistics 21–30 — Reviews, Star Ratings, Review Freshness & Local Trust

Reviews sit between visibility and conversion.

A local business may rank prominently in Google Search or Google Maps, yet consumers can still reject it because its rating is too low, its reviews are too old, there are too few reviews or the business appears unresponsive to customer feedback.

The 2026 evidence also shows that consumer expectations around reviews are increasing rather than becoming less important.

21. 97% of consumers read online reviews for local businesses

Online reviews are now close to universal within the measured local-business research journey.

This means reputation is visible to almost every consumer who researches the business online.

Local SEO implication: Review management should be treated as part of local search performance rather than as a separate customer-service activity.

Source: BrightLocal, Local Consumer Review Survey 2026.

22. 41% of consumers always read reviews when browsing for businesses

The proportion of consumers treating reviews as a routine part of local-business research increased substantially within one year.

Local SEO implication: Businesses should assume that reviews will be inspected, not hope that consumers will overlook a weak review profile.

Source: BrightLocal, 2026.

23. Consumers use an average of six review platforms when choosing businesses

Consumer verification increasingly extends beyond a single Google review profile.

People may compare information across Google, Facebook, industry-specific review platforms, social media, video platforms and other recommendation environments.

Local SEO implication: Reputation consistency across the wider web matters. Strong Google reviews combined with weak or outdated profiles elsewhere can create conflicting trust signals.

Source: BrightLocal, 2026.

24. 92% of consumers care about star ratings when choosing a business

Only a small minority said star ratings did not matter to their decision.

This helps explain why rating differences between businesses appearing in the same local pack or Maps result can affect which listing receives attention.

Local SEO implication: Ranking beside stronger-rated competitors can reduce the commercial value of the ranking itself.

Source: BrightLocal, 2026.

25. 31% will only use a business with a rating of 4.5 stars or higher

This increased sharply from 17% in the previous year’s study.

Consumer expectations therefore moved upwards within only one year.

Local SEO implication: A rating that once looked competitive may become less effective as consumer expectations rise.

Source: BrightLocal, 2026.

26. 68% will only use businesses rated four stars or higher

That compares with 55% in the previous year’s survey.

The increase reinforces the broader trend towards higher minimum expectations.

Local SEO implication: Review generation should focus on delivering genuinely strong customer experiences rather than merely increasing review volume.

Source: BrightLocal, 2026.

27. 74% seek reviews written within the previous three months

Review recency became more important in 2026.

Within the same study:

• 18% were only influenced by reviews written within the previous week.
• 32% looked for reviews written within the previous two weeks.

Local SEO implication: Review acquisition should be continuous. A large historical review count cannot fully compensate for a profile that appears inactive today.

Source: BrightLocal, 2026.

28. 47% will not use a business with fewer than 20 reviews

Consumers are not only looking at the average star rating.

They also use review quantity to judge whether the rating is supported by enough customer experiences to appear credible.

Local SEO implication: Businesses with very small review profiles may struggle to convert local-search visibility even when their average rating is excellent.

Source: BrightLocal, 2026.

29. 56% value a review more when other reviews report similar experiences

Other important signals included:

• 46% — the written review describes a positive experience.
• 44% — the review was posted within the last month.
• 42% — the review has a high star rating.
• 37% — the business owner responded.

This suggests consumers look for patterns across customer experiences rather than relying on one exceptional review.

Local SEO implication: A sustainable reputation programme needs repeated evidence of good service, not a small number of unusually positive testimonials.

Source: BrightLocal, 2026.

30. 89% expect businesses to respond to reviews

The same research found:

• 80% were more likely to use a business that responds to every review.
• 42% were unlikely to use a business that ignores reviews completely.
• 19% expected a response on the same day.
• 32% expected a response by the following day.
• 81% expected a response within one week.
• 50% said generic or templated responses could make them less likely to choose the business.

Review responses are therefore visible evidence of how the organisation handles customers after a transaction has taken place.

Local SEO implication: Review management should include response quality and response speed, not only acquisition volume.

Source: BrightLocal, Local Consumer Review Survey 2026.

Statistics 31–40 — AI Recommendations, ChatGPT, Social Media, Video & Multi-Platform Local Discovery

Local discovery is beginning to extend beyond the traditional Search → Maps → Website journey.

Consumers are increasingly using generative AI, social media, video platforms and review environments alongside Google when deciding which local businesses to investigate.

The change does not mean Google has stopped mattering.

The evidence instead points towards a more fragmented discovery journey in which different platforms contribute at different stages.

31. 45% of consumers used AI tools for local-business recommendations in 2026

BrightLocal’s Local Consumer Review Survey found that generative AI had moved rapidly into mainstream local-business discovery.

The increase from 6% in 2025 to 45% in 2026 represents a 7.5-fold increase in the proportion of consumers using AI for local recommendations.

Local SEO implication: AI visibility has moved from an experimental consideration to a measurable part of the local discovery journey.

Source: BrightLocal, Local Consumer Review Survey 2026 — AI Recommendations.

32. ChatGPT was used by 31% of consumers for local-business recommendations

ChatGPT was the most-used individual generative AI tool for business recommendations in BrightLocal’s 2026 survey.

Google AI Mode ranked second at 23%, with Gemini also appearing among the leading AI recommendation tools.

Local SEO implication: Local AI visibility should not be measured only within Google’s ecosystem. ChatGPT represents a separate discovery environment.

Source: BrightLocal, March 2026.

33. 64% of consumers aged 30–44 had asked AI for a local-business recommendation

AI adoption is not evenly distributed across age groups.

Adults aged 30–44 were the most likely group in the study to use AI for local-business recommendations, while usage among consumers aged over 60 was substantially lower.

Local SEO implication: The commercial importance of AI local visibility will vary by audience demographics and sector.

Source: BrightLocal, 2026.

34. 63% of active AI users trusted AI-generated local-business recommendations

Trust was significantly lower among consumers who had not used AI tools.

Among active AI users, 64% said they trusted AI tools such as ChatGPT as much as traditional reviews when making local-business recommendations.

Local SEO implication: AI recommendations can already influence commercial consideration among consumers who actively use the technology.

Source: BrightLocal, March 2026.

35. 50% of consumers trusted AI-generated summaries of customer reviews

AI is increasingly being used not only to recommend businesses but also to summarise large volumes of review content.

BrightLocal found:

• 23% were willing to rely on the AI summary alone.
• 59% checked the underlying review profile for more information.
• 18% skipped AI summaries entirely.

Local SEO implication: Patterns across customer reviews may increasingly be surfaced automatically before a consumer reads individual reviews.

Source: BrightLocal, 2026.

36. 88% of AI users checked the legitimacy or source of reviews referenced by AI

The study found:

• 51% checked whether the review was legitimate.
• 37% checked the source itself.
• 97% of AI users sometimes double-checked recommendations against real reviews.
• 42% always checked reviews on native review platforms.

Local SEO implication: AI visibility does not eliminate the need for strong reviews and accurate third-party profiles. Consumers often verify the recommendation elsewhere.

Source: BrightLocal, 2026.

37. 23% used AI during their most recent search for a local business

BrightLocal’s July 2026 search-behaviour research also found that 31% used AI tools for local-business recommendations at least monthly.

However, only 18% of consumers already using AI felt ready to contact the recommended business immediately without further research.

Local SEO implication: AI currently appears particularly important for discovery and shortlisting, while other channels remain important for verification and conversion.

Source: BrightLocal, Consumer Search Behavior 2026.

38. 30% used social media during their most recent local-business search

Consumers frequently move between discovery environments rather than completing the entire journey within one platform.

Among consumers who began their search using an AI tool:

• Only 2% used AI as their only channel.
• 43% subsequently checked Google.
• 39% subsequently checked social media.

Local SEO implication: Consistent business information, imagery, reputation and branding across Search, Maps, AI and social platforms can reduce friction during verification.

Source: BrightLocal, July 2026.

39. Repeating the same local AI query produced only 21–33% average overlap between business recommendation sets

BrightLocal analysed 200,085 localised searches across ChatGPT, Google AI Mode and Google AI Overviews, covering 1,300 business locations.

When a business appeared once, it reappeared in approximately:

• 50% of subsequent ChatGPT runs.
• 50% of Google AI Mode runs.
• 58% of AI Overview runs.

The same study found that 71–80% of businesses appeared in half of the attempts or fewer.

Local SEO implication: AI local visibility is probabilistic. One successful recommendation should not be treated as the equivalent of a permanent local ranking.

Source: BrightLocal, What 200k Local AI Searches Tell Us About What Businesses Get Recommended, September 2026.

40. YouTube reached 94% of UK online adults in May 2025

Ofcom reported that YouTube reached approximately 46.3 million UK online adults and averaged 51 minutes per person per day in May 2025.

Facebook/Messenger reached approximately 45.9 million UK adults, while Instagram reached approximately 38.5 million.

These figures measure overall platform reach rather than specifically local-business searches.

Local SEO implication: Video and social platforms operate at sufficient UK scale to influence local brand discovery, reputation and verification even when Google remains the primary search environment.

Source: Ofcom, Online Nation 2025; Ipsos iris.

Statistics 41–50 — Google Maps, AI Sources, Proximity, Websites & Local Directories

The final ten statistics show where traditional local SEO and AI-powered local discovery overlap — and where they begin to separate.

Google Maps remains a more consistent local visibility environment than current generative AI systems, but AI recommendations still depend heavily on familiar local-search assets including business websites, Google Business Profile, directories, reviews and location information.

41. Google Maps surfaced tracked businesses in 66% of searches, compared with only 32–38% across AI surfaces

Ranking successfully in Maps did not automatically translate into equivalent visibility across generative platforms.

The measured businesses appeared approximately twice as often in Google Maps as they did on several AI surfaces.

Local SEO implication: Businesses should track Google Maps visibility and local AI recommendations separately rather than assuming success in one guarantees success in the other.

Source: BrightLocal, What 200k Local AI Searches Tell Us About What Businesses Get Recommended, September 2026.

42. Google Maps showed 99% agreement across repeated checks, compared with 91–96% for AI platforms

AI results change more frequently between repeated requests than traditional Maps results.

This supports the wider finding that generative visibility should be treated as probabilistic rather than as a permanent fixed ranking.

Local SEO implication: One successful ChatGPT or AI Mode result is insufficient to prove durable local AI visibility.

Source: BrightLocal, September 2026.

43. Google AI Mode and AI Overviews shared only 29.3% of named businesses

Even Google’s two generative search environments frequently recommended different local businesses for comparable prompts.

ChatGPT’s overlap was lower still:

• 20% with Google AI Overviews.
• 19% with Google AI Mode.

Local SEO implication: There is no single universal local AI ranking. Businesses may have significantly different visibility across ChatGPT, AI Mode and AI Overviews.

Source: BrightLocal, September 2026.

44. ChatGPT recommended an average of 4.1 local businesses per response

Median business counts were:

• 4 for ChatGPT.
• 4 for Google AI Mode.
• 3 for Google AI Overviews.

AI Overviews therefore produced the tightest local-business shortlist among the three measured platforms.

Local SEO implication: Generative local search often creates a very small consideration set, making inclusion itself commercially significant.

Source: BrightLocal, September 2026.

45. Around one in ten local AI searches returned no business recommendation

Generative systems do not necessarily recommend a business every time a localised commercial prompt is submitted.

This further differentiates AI visibility from a conventional Local Pack, where Google normally presents a defined result set.

Local SEO implication: AI recommendation share should be measured against eligible prompts, not assumed to exist on every query.

Source: BrightLocal, September 2026.

46. Moving across the same town changed most of the businesses recommended by AI

When the same prompt was run from different points within a city, fewer than half of the recommended businesses remained consistent across the measured platforms.

Only:

• 3.5% of ChatGPT results were always present across map points.
• 8.8% of AI Mode results were always present.
• 25.0% of AI Overview results were always present.

Local SEO implication: Geographic measurement still matters in AI search. Testing one city-centre coordinate cannot represent visibility across an entire town or service area.

Source: BrightLocal, September 2026.

47. Between 52.8% and 59.3% of AI-recommended businesses were within 5km of the searcher

Proximity therefore remains highly relevant in local generative search.

However, the platforms differed substantially in their wider geographic reach.

The radius containing 90% of recommendations was approximately:

• 287km for ChatGPT.
• 64km for Google AI Mode.
• 38km for Google AI Overviews.

Local SEO implication: ChatGPT may cast a substantially wider geographic net than Google’s generative surfaces, but accurate address and location information remain important across all three.

Source: BrightLocal, September 2026.

48. 93% of unique domains used as local AI sources were individual business websites

Business websites represented approximately 42% of all individual citations within the wider dataset of almost two million local AI citations.

This is one of the strongest pieces of evidence against the idea that websites are becoming irrelevant in AI-powered local discovery.

Local SEO implication: Businesses still need clear websites containing accurate location, service, expertise, contact and trust information that both users and AI systems can interpret.

Source: BrightLocal, September 2026.

49. Google Business Profile accounted for 28.63% of all citations in a 1.9-million-citation local AI dataset

Google Business Profile information appeared among the citation sources associated with 94.17% of the measured businesses.

Its importance was particularly strong within Google’s own AI surfaces.

Local SEO implication: Claiming and maintaining Google Business Profile remains important not only for Search and Maps but also for Google’s generative local-search ecosystem.

Source: BrightLocal, Top Sources and Directories for Local AI Search, August 2026.

50. Yelp generated 187,599 citations across the local AI dataset

The same research identified 415 directories used as local AI sources.

Other frequently cited environments included:

• Facebook.
• Tripadvisor.
• OpenTable.
• MapQuest.
• Better Business Bureau.
• Angi.
• Trustpilot.
• Industry-specific directories.

ChatGPT showed particularly heavy dependence on Yelp, which appeared as a source in approximately 80% of its measured local answers.

Local SEO implication: Local citations and directories have not disappeared in the AI era. They are becoming part of the source infrastructure used to verify local businesses.

Source: BrightLocal, August 2026.

CGO Media Analysis — What the 50 Local SEO Statistics Tell Us About UK Local Search in 2026

Taken together, the 50 statistics show that local SEO is becoming broader rather than less important.

Google Search and Google Maps remain central to UK local discovery, but the customer journey now extends across reviews, business websites, directories, social platforms, video and AI-generated recommendations.

The strategic challenge is therefore no longer simply to rank a page for a town, city or “near me” search.

The challenge is to make the business consistently discoverable, credible and verifiable wherever local consumers or AI systems look for evidence.

1. Google Still Dominates UK Local Discovery

Google remains the strongest foundation for UK local search.

Its search-engine market share remains above 90%, while Google Search and Google Maps both reach large majorities of UK online adults.

This means businesses should not interpret the rise of AI or social discovery as a reason to deprioritise Google.

The stronger interpretation is that Google remains the centre of local discovery while additional channels increasingly influence verification and choice.

2. Google Maps Has Become a Major Discovery Environment in Its Own Right

Google Maps is no longer simply a navigation application.

Its UK reach has increased materially, and it now sits among the most widely used smartphone applications in the country.

For local businesses, Maps can influence:

• Discovery.
• Directions.
• Telephone calls.
• Opening-hours checks.
• Review inspection.
• Website visits.

3. Local Search Is Fundamentally Mobile

UK online behaviour is already heavily smartphone-led, and current consumer research shows that local-business searches frequently begin on mobile devices.

This makes mobile usability part of local SEO performance.

Critical actions should work immediately on a smartphone:

• Calling.
• Requesting directions.
• Booking.
• Completing a form.
• Viewing prices.
• Checking opening hours.

4. The Local Customer Journey Is Fast

A large proportion of consumers make local-business decisions within minutes rather than days.

This means businesses have very little time to overcome weak first impressions.

The customer may decide before reading a long website page.

The information visible directly within Search or Maps can therefore become commercially important.

5. The Local Consideration Set Is Small

Most consumers consider only a handful of businesses before making a decision.

This changes the strategic objective.

The business does not need to outperform every competitor simultaneously.

It needs to enter the small shortlist that the consumer seriously evaluates.

6. Ranking First Does Not Guarantee the Customer

Only a small minority of consumers simply select the first result.

Once several businesses are visible, other factors become important:

• Distance.
• Star rating.
• Review volume.
• Opening hours.
• Complete information.
• Pricing.
• Photos.

This means rankings and conversion signals must be improved together.

7. Proximity Remains Structurally Important

Both consumer research and local AI recommendation data show a strong relationship between location and business choice.

For many categories, consumers prefer nearby providers.

AI platforms also frequently recommend businesses within a relatively small radius of the searcher.

This reinforces the importance of accurate:

• Addresses.
• Service areas.
• Location pages.
• Map coordinates.
• Local business information.

8. Google Business Profile Is Both a Ranking Asset and a Conversion Asset

Google Business Profile is frequently discussed only as a technical local SEO listing.

The evidence suggests it has a broader role.

Profile information can influence:

• Discovery.
• Trust.
• Directions.
• Telephone calls.
• Review inspection.
• AI source selection.

Profile completeness is therefore part of both visibility and customer conversion.

9. Reviews Are an Operating System for Local Trust

Reviews influence several different stages of local discovery.

They affect whether a consumer:

• Clicks a listing.
• Shortlists the business.
• Trusts the organisation.
• Rejects the business.
• Acts on an AI recommendation.

This makes reputation management inseparable from local SEO.

10. Review Quality Is Multi-Dimensional

Consumers do not evaluate reviews through one number.

They look at:

• Average rating.
• Review volume.
• Review recency.
• Consistency of experiences.
• Business responses.

A business can therefore have a strong rating but still appear weak if the latest reviews are old or too few customers have contributed feedback.

11. Review Expectations Are Rising

Minimum star-rating expectations increased materially in the current consumer data.

That means reputation is a moving benchmark.

A rating that looked competitive several years ago may no longer be enough to remain within the consumer shortlist today.

12. Review Freshness Is Becoming More Important

Consumers increasingly seek recent reviews.

This makes sustained review acquisition more important than accumulating a large historical total and then stopping.

The strongest review profile demonstrates that the business:

• Is still active.
• Still serves customers regularly.
• Still provides the quality represented by its overall rating.

13. Review Responses Are Part of the Public Reputation Signal

Consumers increasingly expect businesses to respond to reviews.

The response itself can communicate:

• Professionalism.
• Attentiveness.
• Customer care.
• Problem resolution.

Generic automated responses can weaken that signal if they appear repetitive or insincere.

14. AI Has Entered Local Discovery Faster Than Many Businesses Expected

The increase in AI usage for local recommendations is one of the most significant changes in the dataset.

ChatGPT, Google AI Mode and other AI systems are now participating in local-business shortlisting for a meaningful proportion of consumers.

This creates another discovery surface that businesses need to monitor.

15. AI Currently Looks Strongest as a Discovery and Shortlisting Layer

Current behaviour suggests that many consumers use AI to identify businesses before verifying them elsewhere.

The journey increasingly looks like:

16. Local AI Visibility Is More Volatile Than Google Maps Visibility

Repeated AI searches can return substantially different business recommendation sets.

Maps results are currently more stable.

This means one successful ChatGPT screenshot should never be treated as evidence that a business consistently ranks in AI.

17. There Is No Single Local AI Ranking

ChatGPT, Google AI Mode and Google AI Overviews frequently recommend different businesses for similar searches.

Even Google’s own AI products show relatively low overlap.

Local AI visibility therefore needs platform-specific measurement.

18. The Business Website Remains Central

One of the strongest findings in the local AI source research is the continued importance of individual business websites.

Business websites represented the overwhelming majority of unique source domains in the measured dataset.

This directly contradicts the idea that AI local search makes websites unnecessary.

The website remains the organisation’s best first-party source for:

• Services.
• Locations.
• Expertise.
• Pricing.
• FAQs.
• Contact information.
• Evidence.

19. Directories Remain Relevant in the AI Era

Hundreds of directories appeared within local AI citation datasets.

This suggests that directory consistency still contributes to the external evidence environment surrounding a local business.

The strategic role of citations may therefore be evolving from:

Directory Listing → Local Ranking Signal

towards a broader model:

Directory Listing → Entity Verification → Search / Maps / AI Evidence

20. Local SEO Is Becoming Local Entity Optimisation

The combined evidence points towards a broader local-search model.

The business increasingly needs to be represented consistently across:

• Its own website.
• Google Business Profile.
• Maps.
• Reviews.
• Directories.
• Social platforms.
• AI systems.

The Strategic Shift

Traditional local SEO asked:

Can this business rank in the Local Pack?

Local discovery in 2026 adds:

Can this business be discovered, verified and trusted across Search, Maps, reviews, directories and AI recommendations?

What UK Businesses Should Do in 2026 to Improve Local Search, Maps & AI Visibility

The 50 statistics show that local visibility now depends on more than conventional rankings.

UK businesses need to maintain a consistent local presence across Google Search, Google Maps, Google Business Profile, reviews, websites, directories, social platforms and emerging AI recommendation systems.

1. Treat Google Business Profile as a Core Business Asset

Google Business Profile remains one of the most important local discovery assets.

Businesses should ensure that the profile contains accurate:

• Business name.
• Primary and secondary categories.
• Address.
• Telephone number.
• Website URL.
• Opening hours.
• Service areas.
• Services.
• Products where relevant.
• Photos.

Incomplete or outdated profile information can create friction before a customer reaches the website.

2. Audit Business Information Across the Web

Name, address, telephone number and other entity information should be consistent across major directories and third-party platforms.

Priority sources should include:

• Google Business Profile.
• Apple Maps.
• Bing Places.
• Yelp.
• Facebook.
• Trustpilot where relevant.
• Industry directories.
• Professional associations.

The objective is consistency rather than maximum listing volume.

3. Build Strong Location Pages

Businesses serving several locations should create genuinely useful location pages rather than duplicating the same content with different place names.

Strong location pages can include:

• Local services.
• Areas served.
• Directions.
• Local photographs.
• Location-specific reviews.
• Local FAQs.
• Team information.
• Opening hours.
• Relevant local evidence.

This helps both conventional search and AI systems understand where the business operates.

4. Strengthen Geographic Relevance

Google continues to identify relevance, distance and prominence as major factors within local ranking.

Businesses cannot change physical distance, but they can improve how clearly their location and service area are represented.

Useful signals include:

• Accurate addresses.
• Local landing pages.
• Service-area information.
• Local content.
• Local links.
• Local citations.

5. Build a Continuous Review Programme

The strongest review strategy is continuous rather than campaign-based.

Businesses should request feedback consistently from genuine customers rather than creating periodic bursts of activity.

Track:

• Average rating.
• Review volume.
• Review frequency.
• Recent-review count.
• Response rate.

6. Respond to Reviews Properly

Consumer research shows that review responses matter.

Responses should be:

• Personalised.
• Professional.
• Timely.
• Relevant to the customer’s feedback.

Avoid repetitive template responses that make the business appear automated or indifferent.

7. Monitor Review Freshness

A profile with a strong historical review count can still look inactive when the newest review is several months old.

Businesses should monitor the number of reviews received over:

• 30 days.
• 90 days.
• Six months.

The objective is to demonstrate that the business is still active and consistently serving customers.

8. Improve the Mobile Conversion Journey

Local discovery is heavily mobile.

Businesses should test whether a mobile user can easily:

• Call.
• Get directions.
• Make a booking.
• Complete a contact form.
• View prices.
• Read reviews.
• Find opening hours.

Every extra step can create unnecessary abandonment.

9. Make Contact Information Impossible to Miss

Because local decisions are frequently made quickly, key information should be visible without requiring extensive navigation.

Display clearly:

• Telephone number.
• Address.
• Opening hours.
• Email or contact form.
• Booking options.

10. Use Clear Local Service Pages

A business website should explain exactly what is offered and where.

Avoid relying on vague corporate language.

Each important service page should make clear:

• What the service is.
• Who it is for.
• Where it is available.
• How much it costs where appropriate.
• How to contact or book.

11. Build Local Authority, Not Just Local Keywords

Repeatedly inserting a town or city into headings is not a substitute for demonstrating real local relevance.

Businesses can strengthen local authority through:

• Local partnerships.
• Local press coverage.
• Local sponsorship.
• Professional associations.
• Community participation.
• Local case studies.
• Regional research.

12. Earn Relevant Local Links

Local links can reinforce prominence and local relevance.

Useful sources may include:

• Local newspapers.
• Trade organisations.
• Business associations.
• Partners.
• Suppliers.
• Event websites.
• Community organisations.

Relevance and legitimacy matter more than volume.

13. Publish Useful Local Evidence

Original local data can create authority beyond ordinary service content.

Examples include:

• Regional surveys.
• Local market statistics.
• Pricing studies.
• Local trend analysis.
• Customer-behaviour research.

This can support search visibility, digital PR and future AI citation opportunities.

14. Make the Website a Strong First-Party Source

Current AI research shows that individual business websites remain important sources in local generative search.

The website should therefore contain reliable first-party information about:

• Locations.
• Services.
• Experience.
• Team.
• Pricing.
• Customer questions.
• Policies.

15. Monitor AI Recommendations Separately From Google Maps

Do not assume that strong Google Maps visibility automatically produces strong ChatGPT or AI Mode visibility.

Businesses should test important local prompts across:

• ChatGPT.
• Google AI Mode.
• Google AI Overviews.
• Gemini where relevant.
• Perplexity where relevant.

Track whether the business is:

• Mentioned.
• Recommended.
• Cited.

16. Repeat AI Tests Rather Than Taking Screenshots Once

Local AI results are volatile.

The same query can return different businesses between runs.

A reliable test should use:

• Several repetitions.
• Several locations.
• Stable prompt wording.
• Several AI platforms.

17. Test Local Visibility From Several Geographic Points

Both traditional local rankings and AI recommendations can change significantly across a town or city.

Businesses should avoid measuring only from one central postcode or coordinate.

Use a grid covering the actual service area.

18. Audit Local Directories That AI Systems Actually Use

The local AI citation research identified hundreds of directories appearing as evidence sources.

Businesses should prioritise directories that are:

• Relevant to the sector.
• Visible in search.
• Used by customers.
• Referenced by AI systems.

Avoid indiscriminate submission to low-quality directories.

19. Build Consistency Across Search, Maps, Reviews and AI

The strongest local visibility comes from repeated agreement across the web.

Ideally, the business should present the same core information across:

• Website.
• Google Business Profile.
• Maps.
• Directories.
• Review sites.
• Social profiles.

This reduces ambiguity for both consumers and machine systems.

20. Measure Commercial Outcomes, Not Only Rankings

The final objective of local SEO is customer acquisition.

Businesses should measure:

• Calls.
• Direction requests.
• Bookings.
• Form submissions.
• Store visits where measurable.
• Leads.
• Revenue.

The Practical Priority

Local SEO Measurement Framework — What UK Businesses Should Track Each Month

Local SEO performance should not be reduced to one map ranking or one organic position.

A business can improve visibility while losing calls, improve reviews while losing map coverage, or gain AI mentions without generating any measurable commercial outcome.

The strongest monthly reporting framework separates discovery, trust, conversion and commercial impact.

1. Google Maps Visibility

Track how often the business appears across the actual service area.

Measure:

• Average map position.
• Share of top-three visibility.
• Geographic coverage.
• Grid points gained.
• Grid points lost.

One central postcode is not enough for businesses serving a wider town or region.

2. Local Pack Visibility

Track whether the business appears within Google’s local results for high-value commercial searches.

Important metrics include:

• Local Pack appearances.
• Top-three frequency.
• Query coverage.
• Competitor overlap.

3. Local Organic Rankings

Track location-specific organic rankings separately from Maps.

Monitor:

• Service + location queries.
• Problem-led local queries.
• Branded local queries.
• Comparison searches.

A business can improve in Maps while declining organically, or vice versa.

4. Google Business Profile Discovery

Monitor how often users find the profile through Google Search and Maps.

Track changes in:

• Search visibility.
• Maps visibility.
• Profile views.
• Search terms where available.

5. Google Business Profile Actions

Profile activity is more commercially useful than visibility alone.

Track:

• Telephone calls.
• Website clicks.
• Direction requests.
• Bookings.
• Messages where applicable.

6. Review Rating

Track average rating monthly.

Do not evaluate it in isolation.

A 4.8-star rating based on ten reviews carries a different level of evidence from the same rating across several hundred reviews.

7. Review Volume

Track:

• Total review count.
• New reviews this month.
• Reviews in the last 90 days.
• Review growth versus competitors.

8. Review Freshness

Track the age of the latest reviews.

A useful monthly dashboard can show:

• Reviews received in the last 30 days.
• Reviews received in the last 90 days.
• Days since the most recent review.

9. Review Response Rate

Measure the percentage of reviews receiving a business response.

Where operationally realistic, also track response time.

This creates visibility into whether customer feedback is being actively managed.

10. Reputation Gap Versus Competitors

Compare the business against the leading competitors appearing in the same local results.

Track:

• Average rating.
• Review count.
• Recent-review count.
• Response activity.

11. Business Information Accuracy

Maintain a monthly or quarterly audit of important business information.

Check:

• Name.
• Address.
• Telephone number.
• Opening hours.
• Website URL.
• Categories.
• Services.

12. Directory Consistency

Monitor the important directories and industry platforms where the business appears.

Track:

• Correct listings.
• Duplicate listings.
• Missing listings.
• Outdated information.

13. Local Landing Page Performance

For each priority location page, track:

• Organic impressions.
• Clicks.
• Rankings.
• Engagement.
• Conversions.

This helps distinguish pages generating real local demand from pages that exist only for keyword coverage.

14. Local Search Conversion Rate

Measure the percentage of local organic and Maps traffic producing a meaningful action.

Possible conversions include:

• Telephone calls.
• Forms.
• Bookings.
• Transactions.
• Direction requests.

15. AI Recommendation Visibility

Track important local prompts across the AI systems relevant to the market.

Measure whether the business is:

• Mentioned.
• Recommended.
• Cited.

Do not combine these three outcomes into one number.

16. AI Recommendation Stability

Because AI local results can vary significantly, repeat key prompts several times.

Track:

• Consistent appearances.
• Occasional appearances.
• One-off recommendations.

17. Cross-Platform Local Visibility

Compare performance across:

• Google Search.
• Google Maps.
• Google AI Overviews.
• Google AI Mode.
• ChatGPT.

Where relevant, add Gemini and Perplexity.

18. Local Competitor Share

Measure how frequently major competitors appear across the same query set.

Useful metrics include:

• Local Pack share.
• Maps top-three share.
• AI recommendation share.
• Review strength.

19. Leads and Revenue

Connect local visibility with commercial outcomes.

Track:

• Local leads.
• Qualified enquiries.
• Bookings.
• Transactions.
• Revenue.

Where possible, identify the location, channel and landing page associated with the conversion.

20. Local Search-to-Revenue Funnel

Recommended Monthly Reporting Table

The Measurement Rule

Local SEO Trends UK 2026–2027 — How Search, Maps, Reviews, AI Recommendations & Local Discovery Are Evolving

The 50 statistics in this report point towards a local search environment that is becoming broader, more fragmented and more dependent on consistent evidence across multiple platforms.

The following trends are evidence-led directions rather than guaranteed forecasts.

They are based on current UK platform usage, local-search behaviour, review research and large-scale testing of AI-generated local business recommendations.

1. Google Maps Will Remain a Core UK Local Discovery Surface

Google Maps continues to grow in UK reach while remaining one of the country’s most widely used smartphone applications.

That makes Maps an increasingly important destination in its own right rather than simply a secondary feature attached to Google Search.

Through 2027, businesses should expect map visibility, directions, reviews, profile interactions and geographic coverage to remain central local SEO metrics.

2. Google Search Will Remain Foundational Even as Local Discovery Fragments

Google Search still reaches the large majority of UK online adults and Google remains dominant within the UK search-engine market.

The growth of AI, social and video discovery therefore looks more like an expansion of the journey than a wholesale replacement of Google.

3. Local Search Will Become More Mobile and More Immediate

UK adults already spend most of their online time on smartphones.

Current local-search research also shows mobile devices dominating the start of local-business searches.

This will continue to favour businesses that make high-intent actions immediate:

• Call.
• Book.
• Get directions.
• Check opening hours.
• View prices.
• Complete a form.

4. Google Business Profile Will Remain a Critical Entity Source

Google Business Profile is already important to Search and Maps and appears heavily within Google’s local AI source ecosystem.

That suggests profile accuracy will remain foundational as Google’s conventional and generative local experiences become more connected.

Businesses should expect increasing value from maintaining accurate:

• Categories.
• Opening hours.
• Services.
• Photos.
• Locations.
• Contact information.

5. AI Will Become a Larger Local Shortlisting Channel

Consumer use of generative AI for local-business recommendations has risen rapidly.

The most likely near-term role is not replacing every stage of local search but influencing the shortlist before the user verifies the business elsewhere.

6. AI Visibility Will Need Its Own Reporting Layer

Google Maps visibility and AI recommendation visibility are not equivalent.

Current testing shows businesses can appear strongly in Maps and much less frequently within ChatGPT, AI Mode or AI Overviews.

Businesses will increasingly need separate reporting for:

• Maps visibility.
• Organic local rankings.
• AI mentions.
• AI recommendations.
• AI citations.

7. Local AI Results Will Remain More Volatile Than Traditional Maps Results

Repeated local AI queries frequently produce different recommendation sets.

This will make one-off screenshots increasingly inadequate as evidence of performance.

Reliable monitoring will require:

• Repeated prompts.
• Several geographic points.
• Consistent query sets.
• Platform-specific tracking.

8. There Will Not Be One Universal Local AI Ranking

ChatGPT, Google AI Mode and AI Overviews already show relatively low overlap in the businesses they recommend.

This means future local GEO reporting should avoid statements such as “we rank number two in AI”.

The more accurate question is:

How consistently is the business recommended across each AI platform and location?

9. Geographic Granularity Will Become More Important

AI recommendations vary substantially as the simulated searcher’s location moves across the same town or city.

Traditional local rankings behave similarly.

Measurement will therefore increasingly shift from single-location testing towards geographic grids covering the genuine service area.

10. Proximity Will Remain Important Even in Generative Search

Most AI-recommended local businesses in current research remain relatively close to the searcher’s location.

This suggests generative search does not remove geography from local discovery.

Businesses will still need strong location signals, including:

• Accurate addresses.
• Service areas.
• Location pages.
• Local relevance.

11. Reviews Will Become an Even Stronger Filtering Mechanism

Consumers increasingly expect higher ratings, more reviews and fresher feedback.

This raises the threshold required simply to remain within the consideration set.

Review management will increasingly influence whether visibility turns into a contact or visit.

12. Review Freshness Will Matter More Than Historical Volume Alone

Large review totals remain valuable, but consumers increasingly want evidence from recent customers.

The implication is a shift from:

How Many Reviews Do We Have?

towards:

How Strong, Recent and Consistent Is Our Review Evidence?

13. AI-Generated Review Summaries Will Become More Influential

Consumers are already encountering AI-generated summaries of review sentiment.

This means individual negative or positive comments may increasingly be interpreted within broader patterns extracted automatically across many reviews.

Businesses should therefore focus on improving the underlying customer experience rather than trying to optimise isolated review wording.

14. Review Responses Will Become Part of Brand Evaluation

Consumers increasingly expect businesses to acknowledge feedback.

Response quality can signal:

• Professionalism.
• Responsiveness.
• Customer care.
• Accountability.

Generic mass responses are likely to become less effective as users become more sensitive to automation.

15. Business Websites Will Remain Important in AI Local Search

Current local AI citation data gives business websites a major role in source selection.

That makes the business website important for both users and machine systems.

The website should increasingly function as the definitive first-party source for:

• Who the business is.
• Where it operates.
• What it provides.
• Why it is credible.
• How customers can engage.

16. Local Directories Will Gain a Second Life as AI Verification Sources

Hundreds of directories appear in current local AI citation datasets.

This suggests that local citations will remain relevant, although their function is broadening.

The emphasis will move away from submitting to every possible directory and towards maintaining presence on sources that:

• Consumers trust.
• Rank in search.
• Are relevant to the industry.
• Are used by AI systems.

17. Social and Video Platforms Will Become More Important Verification Layers

YouTube, Facebook and Instagram already have enormous UK reach.

Consumer behaviour research also shows social platforms appearing within local-business research journeys.

Through 2027, local businesses should expect customers to use social and video content to verify:

• What the business looks like.
• Whether it is active.
• What customers experience.
• Whether the organisation appears credible.

18. Entity Consistency Will Become More Important Than Raw Listing Volume

As search engines and AI systems pull information from multiple sources, conflicting business information becomes increasingly problematic.

A modern local optimisation programme should prioritise agreement across important sources rather than accumulating hundreds of low-value listings.

The core entity should remain consistent across:

• Website.
• Google Business Profile.
• Maps.
• Directories.
• Review platforms.
• Social profiles.

19. Local SEO and GEO Will Continue to Converge

Many of the strongest assets for conventional local SEO are also useful for AI discovery:

• Clear location information.
• Strong business websites.
• Google Business Profile.
• Reviews.
• Trusted directories.
• External authority.

This suggests local GEO will develop as an extension of strong local search foundations rather than as an entirely separate discipline.

20. Commercial Measurement Will Move Beyond Rankings

Businesses increasingly need to connect local search visibility with real customer outcomes.

The strongest measurement model will combine:

• Search visibility.
• Maps coverage.
• Review strength.
• AI recommendation presence.
• Calls.
• Directions.
• Bookings.
• Leads.
• Revenue.

What This Means for UK Businesses

The direction is not towards abandoning traditional local SEO.

It is towards making local authority portable across more discovery systems.

Research Methodology & Limitations

This report brings together 50 measurable data points relating to UK local search, Google Maps, mobile discovery, local-business selection, reviews, Google Business Profile, directories, AI recommendations and emerging multi-platform local discovery.

The objective is not to imply that one dataset can describe the entire UK local-search environment.

Instead, the research combines UK-specific platform data with clearly labelled international and US consumer benchmarks where equivalent current UK evidence is unavailable.

1. Research Scope

The 50 statistics are organised around five areas:

1. UK Google Search, Google Maps and mobile usage.
2. Local-business choice, proximity and listing information.
3. Reviews, ratings, review freshness and reputation.
4. AI recommendations, social media and multi-platform discovery.
5. Local AI sources, websites, directories and geographic visibility.

These categories reflect the main stages through which a local consumer can move from discovery to selection.

2. Source Hierarchy

Sources were prioritised according to transparency, relevance and methodological detail.

The preferred hierarchy was:

1. UK regulatory and audience-measurement data — including Ofcom and Ipsos iris.
2. First-party platform documentation — including Google Business Profile and Google Search guidance.
3. Large-scale local-search research — including BrightLocal consumer and AI-search studies.
4. Independent market-share data — including Statcounter.
5. CGO Media calculations derived transparently from published source values.

3. UK Data Is Prioritised Wherever Available

Where reliable current UK evidence exists, it is used in preference to international benchmarks.

Examples include:

• Google Search reach.
• Google Maps reach.
• Smartphone usage.
• UK platform reach.
• UK search-engine market share.

These figures provide the UK-specific foundation for the report.

4. US Consumer Benchmarks Are Explicitly Labelled

Detailed 2026 research covering local-search behaviour, local-business choice and review expectations is more readily available for US consumers than UK consumers.

Where this research is used, each statistic is labelled:

US Local Search Benchmark

or:

US Consumer Review Benchmark

These figures should not be converted into UK population statistics.

5. Multi-Market AI Search Data Is Treated Separately

The local AI source studies include businesses and searches from more than one country.

Findings concerning:

• AI recommendations.
• AI citation sources.
• Google Business Profile citations.
• Business websites.
• Directories.

are therefore treated as multi-market or local AI benchmarks rather than UK-only statistics.

6. Platform Reach Does Not Equal Local-Search Usage

A platform reaching a large proportion of UK adults does not mean that all those users search for local businesses there.

For example, YouTube, Facebook and Instagram reach large UK audiences, but overall platform reach is not equivalent to local-business discovery usage.

The report therefore distinguishes between:

• Platform reach.
• Local-search use.
• Local-business recommendation use.

7. Google Maps Reach Does Not Mean Every User Is Conducting a Business Search

Google Maps is used for many purposes including:

• Navigation.
• Journey planning.
• Place discovery.
• Business discovery.
• Directions.

The UK reach statistics demonstrate the scale of the platform rather than the percentage of users conducting commercial local searches.

8. Search-Engine Market Share Is Not Identical to Local Search Share

Statcounter market-share figures measure search-engine usage generally.

They do not isolate local-commercial searches.

The figures are used to establish Google’s wider UK search dominance, not to claim that the same exact percentage applies to local search alone.

9. Consumer Surveys Measure Reported Behaviour

Consumer research relies partly on participants describing their own recent behaviour.

Reported behaviour can differ from directly observed clickstream behaviour.

Survey results should therefore be interpreted as evidence of consumer attitudes and recalled behaviour rather than perfect behavioural tracking.

10. Sector Differences Can Be Significant

Local-search behaviour varies by industry.

For example, proximity may be especially important for:

• Restaurants.
• Healthcare.
• Emergency services.
• Retail.

Review volume may matter differently for:

• Professional services.
• Legal services.
• Home services.
• Hospitality.

Aggregate statistics should not automatically be treated as identical across every sector.

11. Local Search Behaviour Can Vary by Age

AI recommendation usage varies significantly between age groups.

The same may be true for:

• Social discovery.
• Review use.
• Mobile behaviour.
• Platform preference.

Businesses should therefore compare general benchmarks with their own customer demographics.

12. Local Rankings Are Geographically Variable

Google Maps and local organic results can change as the searcher’s location changes.

A ranking measured at one postcode, coordinate or office location cannot automatically represent an entire city.

Geographic grid measurement is therefore more reliable for businesses serving wider areas.

13. Local AI Recommendations Are Also Geographically Variable

Current AI-search research shows that moving the search location across the same city can materially change the businesses recommended.

This means local AI visibility should also be tested geographically rather than from a single location.

14. AI Recommendations Are Probabilistic

Repeated identical or near-identical AI prompts can generate different local business lists.

One recommendation should not be interpreted as the equivalent of a permanent ranking position.

Reliable measurement requires repeated tests.

15. Different AI Platforms Recommend Different Businesses

ChatGPT, Google AI Mode and Google AI Overviews show limited overlap in current local recommendation studies.

Results from one platform should therefore not be presented as universal “AI rankings”.

16. AI Citation Does Not Always Equal Recommendation

A business website or directory may be cited as an information source without the associated business being recommended to the user.

The report therefore distinguishes between:

• Source citation.
• Business mention.
• Business recommendation.

17. Google Business Profile Citation Data Does Not Prove Causation

The presence of Google Business Profile information within local AI source datasets demonstrates its importance as a source environment.

It does not prove that simply completing additional profile fields will independently cause an AI system to recommend the business.

Correlation and causation remain separate.

18. Directory Citations Should Not Be Interpreted as a Quantity Target

The presence of hundreds of directories in AI-source research does not mean businesses should submit themselves to hundreds of directories.

The stronger interpretation is that reputable directories can contribute to local entity verification and external evidence.

Quality, relevance and accuracy remain more important than raw quantity.

19. Review Statistics Describe Consumer Expectations, Not Google Ranking Factors

Review surveys measure how consumers evaluate local businesses.

They should not be interpreted as direct evidence that Google uses the same thresholds algorithmically.

For example, a consumer requiring a 4.5-star rating does not mean Google requires 4.5 stars for local ranking.

20. Review Quantity and Review Rating Should Be Separated

A high average rating and a large review volume are different signals.

Consumers may consider both when evaluating credibility.

Reporting should therefore avoid collapsing them into one “review score”.

21. Review Freshness Is a Consumer Signal, Not a Proven Independent Ranking Factor

Consumers strongly value recent reviews.

That does not independently prove that review age is a standalone local-ranking factor used by Google.

The report therefore treats review freshness primarily as a trust and conversion signal.

22. Business Profile Completeness Data Requires Context

Google has published figures linking complete Business Profiles with stronger consumer consideration and visits.

These are first-party platform benchmarks and should not be treated as independent UK consumer experiments.

23. Local SEO Rankings Do Not Equal Commercial Performance

A business can improve search visibility without generating more customers.

Commercial analysis should include:

• Calls.
• Direction requests.
• Bookings.
• Forms.
• Transactions.
• Revenue.

24. Offline Outcomes Are Often Under-Measured

A customer may discover a business through local search and then:

• Walk into a physical location.
• Telephone from another device.
• Return later.
• Search for the brand directly.

These behaviours can make local-search attribution incomplete.

25. Local Search Data Changes Quickly

Google interfaces, AI systems, review behaviour and consumer adoption can change rapidly.

Statistics should therefore be reviewed according to:

• Publication date.
• Measurement period.
• Platform version.
• Country.
• Sample population.

Research Updates

CGO Media treats this page as a living research resource.

Individual statistics may be updated or replaced when:

• Stronger UK-specific evidence becomes available.
• Consumer behaviour changes materially.
• Google changes local-search functionality.
• AI recommendation behaviour changes.
• Larger datasets improve the evidence base.
• Older benchmarks become unrepresentative.

For the wider CGO Media approach to evidence selection, calculations, limitations and updates, see the CGO Media Research Methodology.

Frequently Asked Questions — Local SEO Statistics UK 2026

The following questions address the main issues surrounding local SEO, Google Maps, Google Business Profile, reviews, local rankings, directories and AI-powered local discovery in 2026.

What is local SEO?

Local SEO is the process of improving a business’s visibility for searches connected with a geographic location.

It can include:

• Google Search.
• Google Maps.
• Google Business Profile.
• Local landing pages.
• Reviews.
• Directories.
• Local links.
• AI-generated local recommendations.

Is Google still the most important local-search platform in the UK?

Yes.

Google remains the dominant search engine in the UK, while both Google Search and Google Maps reach large majorities of UK online adults.

Other channels are becoming more important, but Google remains the central local-search environment.

How important is Google Maps for UK businesses?

Google Maps is increasingly important.

Ofcom data shows that Google Maps reached 78% of UK online adults in May 2025 and had grown significantly from 2023.

For local businesses, Maps can influence discovery, directions, telephone calls, reviews and website visits.

Is Google Business Profile still important in 2026?

Yes.

Google Business Profile remains central to conventional local Search and Maps visibility and also appears prominently within current local AI source research.

Businesses should keep profile information accurate and complete, including:

• Categories.
• Address.
• Telephone number.
• Opening hours.
• Services.
• Website.
• Photos.

Does ranking number one in local search guarantee the customer?

No.

Current consumer research shows that relatively few consumers simply choose the first local result without considering other factors.

They frequently compare:

• Distance.
• Ratings.
• Review quantity.
• Opening hours.
• Business information.
• Pricing.

How many local businesses do consumers usually compare?

Current US consumer research found that 72% considered three businesses or fewer before making a decision.

This is not a UK population statistic, but it illustrates how small the local consideration set can be.

How quickly do consumers choose a local business?

In BrightLocal’s 2026 US benchmark, 75% chose a business within 30 minutes and 28% made the decision within five minutes.

This reinforces the importance of clear information and strong first impressions.

Are reviews important for local SEO?

Yes, but there are two different issues.

Reviews can influence consumer trust and conversion, while Google also identifies review quantity and score as factors that can contribute to local prominence.

Consumer research also shows that people inspect ratings, review volume and review freshness before choosing businesses.

What star rating do consumers expect?

Expectations are rising.

In BrightLocal’s 2026 US consumer survey:

• 68% would only use businesses rated four stars or higher.
• 31% required at least 4.5 stars.

These are consumer-choice benchmarks rather than Google ranking thresholds.

How recent should local-business reviews be?

Current consumer research suggests review recency matters strongly.

BrightLocal found 74% of consumers looked for reviews written within the previous three months.

This means businesses benefit from a steady flow of genuine recent reviews rather than relying only on historical review totals.

How many reviews does a local business need?

There is no universal number that applies to every industry or location.

Businesses should compare themselves with the competitors appearing in the same local results.

Consumer research indicates that review quantity influences credibility alongside star rating and freshness.

Should businesses reply to every review?

Where operationally realistic, responding consistently is a strong practice.

BrightLocal’s 2026 consumer research found that 89% expected businesses to respond to reviews and 80% were more likely to use a business that responded to every review.

Responses should remain personalised rather than repetitive templates.

Does proximity still matter in local SEO?

Yes.

Google continues to identify distance as one of the major factors influencing conventional local results.

Current AI local-search research also shows a strong concentration of recommendations near the searcher’s location.

Can a business rank across an entire city?

Possibly, but local visibility often changes significantly from one neighbourhood to another.

Distance, competition and relevance can all affect the result.

Businesses serving a large city should therefore use geographic grid tracking rather than measuring from only one point.

Do local landing pages still work?

Yes, when they provide genuine location-specific value.

Useful local pages can include:

• Services available in the area.
• Location details.
• Directions.
• Local FAQs.
• Local case studies.
• Local team information.
• Relevant photographs.

Thin pages that simply replace one town name with another provide far less value.

Are directories still important for local SEO?

Relevant directories still have value.

Current AI citation research shows that directories continue to appear as local-business evidence sources.

Businesses should prioritise reputable platforms that are:

• Relevant to the industry.
• Used by customers.
• Visible in search.
• Accurate.

Submitting to hundreds of low-quality directories is not the objective.

Is NAP consistency still important?

Yes.

The business name, address and telephone number should remain consistent across important platforms.

This reduces confusion for both customers and machine systems attempting to understand the business entity.

Do business websites still matter for local SEO in the AI era?

Yes.

Large-scale local AI research found business websites represented the overwhelming majority of unique domains used as source material.

The website remains the strongest first-party location for publishing accurate information about:

• Services.
• Locations.
• Pricing.
• Experience.
• Contact details.
• Customer questions.

Can ChatGPT recommend local businesses?

Yes.

ChatGPT can recommend local businesses in response to relevant prompts, and consumer use of AI for local-business recommendations has increased materially.

However, recommendations can vary between repeated prompts.

Is ranking in Google Maps enough to rank in ChatGPT?

No.

Current large-scale testing shows that Maps visibility and AI recommendation visibility overlap only partially.

A business can perform strongly in Maps without appearing consistently in ChatGPT.

Is there one local AI ranking?

No.

ChatGPT, Google AI Mode and Google AI Overviews can recommend different businesses for similar prompts.

AI visibility should therefore be tracked separately by platform.

How should local AI visibility be measured?

Use repeated testing rather than one result.

Track:

• Mentions.
• Recommendations.
• Citations.
• Repeat appearances.
• Geographic variation.
• Competitor visibility.

Does social media matter for local search?

It increasingly contributes to local discovery and verification.

Consumers may use social platforms to check:

• Recent activity.
• Photographs.
• Customer comments.
• Products.
• Services.

Social media should be treated as a supporting discovery and trust environment rather than a direct replacement for Search and Maps.

Does YouTube matter for local businesses?

It can.

YouTube has extremely high UK reach and can support local discovery through:

• Demonstrations.
• Location videos.
• Expert explanations.
• Customer education.
• Service walkthroughs.

Its relevance varies by sector.

Is local SEO becoming GEO?

The two areas are increasingly overlapping.

Strong local SEO assets such as:

• Accurate business information.
• Google Business Profile.
• Useful local pages.
• Reviews.
• Directories.
• External authority.

can also support AI-powered discovery.

GEO adds the question of whether generative systems can retrieve, understand and recommend the business.

What should UK businesses prioritise first?

A practical priority order is:

Conclusion — Final Research Findings from the 50 Local SEO Statistics UK 2026

The 50 statistics in this report show that local SEO is becoming more complex, but its underlying purpose remains the same: helping the right customer find and choose the right local business.

What has changed is the number of places where that discovery and decision can now happen.

Google Search and Google Maps remain central to UK local discovery, but reviews, websites, directories, social platforms, video and AI-generated recommendations are increasingly influencing which businesses enter the customer shortlist.

Google Remains the Foundation of UK Local Search

The strongest UK-specific evidence in this report confirms that Google remains deeply embedded in consumer discovery.

Google Search continues to reach a large majority of UK online adults, while Google Maps has expanded significantly and now sits among the country’s most widely used smartphone applications.

The rise of AI therefore does not currently justify moving away from Google.

Instead, businesses need to build on strong Google visibility while becoming discoverable across additional channels.

Google Maps Has Become a Major Commercial Discovery Environment

Maps now influences much more than navigation.

Customers use it to:

• Discover businesses.
• Compare locations.
• Read reviews.
• Check opening hours.
• Call.
• Request directions.
• Visit websites.

This makes Maps visibility a core local business metric rather than a secondary SEO consideration.

The Customer Decision Window Is Small

Local-business decisions frequently happen quickly.

Consumers often examine only a small number of businesses before choosing.

That means the real competition is frequently not to outperform every business in the market, but to secure a place in the first credible shortlist.

Being Visible Is Only the First Stage

Ranking highly in Search or Maps creates an opportunity.

It does not guarantee selection.

Consumers continue to evaluate:

• Proximity.
• Star ratings.
• Review volume.
• Review freshness.
• Business information.
• Pricing.
• Photos.
• Opening hours.

Local visibility and local conversion therefore need to be optimised together.

Proximity Remains a Powerful Local Signal

Distance continues to influence conventional local search and consumer choice.

Current AI-local-search research also shows that a large proportion of recommended businesses remain geographically close to the searcher.

Generative search has therefore not removed geography from local discovery.

Google Business Profile Remains Foundational

Google Business Profile continues to connect several stages of the customer journey:

• Search visibility.
• Maps discovery.
• Reviews.
• Directions.
• Telephone contact.
• Website visits.
• AI source selection.

Profile maintenance should therefore be treated as ongoing local-search infrastructure rather than a one-time setup task.

Reviews Have Become a Multi-Dimensional Trust System

Consumers do not judge local reputation through one number.

The evidence shows that they consider:

• Average rating.
• Review quantity.
• How recently reviews were written.
• Whether customer experiences appear consistent.
• Whether the business responds.

A local review profile is therefore a continuously changing body of commercial evidence.

Review Expectations Are Increasing

Consumer thresholds for ratings, review volume and recency are becoming more demanding.

Businesses that once appeared competitive may gradually lose consideration if their review programme becomes inactive.

The strongest strategy is a steady flow of authentic customer feedback rather than occasional review campaigns.

AI Is Entering the Local Discovery Journey

Generative AI has moved rapidly into local-business recommendations.

ChatGPT, Google AI Mode and other AI systems can now influence which businesses enter the customer shortlist.

However, current behaviour also shows that consumers frequently verify AI recommendations through Google, reviews, websites and social channels before acting.

AI Is Currently More of a Discovery Layer Than a Complete Replacement Journey

The current evidence suggests that AI is particularly effective at helping consumers identify possible businesses.

The wider journey can then continue through:

Local AI Visibility Is Not a Fixed Ranking

One of the most important findings is the volatility of local AI recommendations.

Repeated prompts can produce different businesses.

Results can also change when the simulated searcher’s location moves across the same city.

This means local AI visibility should be measured through repeated tests rather than single screenshots.

There Is No Single Universal AI Local Ranking

ChatGPT, Google AI Mode and Google AI Overviews frequently produce different local-business sets.

Even different Google AI surfaces can disagree significantly.

Businesses therefore need platform-specific measurement rather than one headline “AI ranking”.

The Business Website Remains Central

Large-scale local AI citation research shows that individual business websites remain major information sources.

This means websites continue to play several roles:

• Organic search asset.
• Local relevance source.
• Conversion destination.
• First-party entity source.
• AI citation source.

The business website is not disappearing in the AI era. Its role is expanding.

Directories Have Not Become Obsolete

Current AI research identifies hundreds of directories among local AI sources.

The purpose of local citations is therefore evolving.

They can support:

• Consumer discovery.
• Entity verification.
• Reputation.
• Search visibility.
• AI source corroboration.

Quality and relevance remain more important than raw listing volume.

Social and Video Are Becoming Supporting Local Discovery Layers

Major social and video platforms have enormous UK reach.

Consumers can use them to verify whether a local business appears:

• Active.
• Credible.
• Professional.
• Relevant.
• Trusted by real customers.

These platforms increasingly complement Search and Maps rather than replacing them.

Local SEO and GEO Are Converging

The strongest foundations for conventional local SEO are also useful in generative discovery:

• Accurate business information.
• Google Business Profile.
• Strong business websites.
• Location pages.
• Reviews.
• Directories.
• External authority.

GEO adds the requirement that AI systems can retrieve, understand and recommend the business from that evidence.

The Local Entity Is Becoming the Strategic Centre

The common thread connecting Search, Maps, directories, reviews and AI is the underlying business entity.

Each system needs consistent answers to basic questions:

• What is this business?
• Where is it?
• What does it provide?
• Who does it serve?
• Is it credible?

The clearer and more consistent those answers are across the web, the stronger the local evidence environment becomes.

Commercial Measurement Needs to Move Beyond Rankings

Local SEO performance should ultimately be connected to business outcomes.

That means measuring:

• Calls.
• Directions.
• Bookings.
• Website conversions.
• Leads.
• Transactions.
• Revenue.

Rankings are useful diagnostic metrics, but they are not the final commercial objective.

Final CGO Media Research Position

Traditional local SEO asked:

Can this business rank locally?

The 2026 local discovery environment adds:

Can this business be consistently discovered, verified and trusted wherever the customer or AI system looks?

Research Usage, Citation & Press

The Local SEO Statistics UK 2026 research is intended to support journalists, researchers, businesses, agencies and organisations examining how local discovery is changing across Google Search, Google Maps, reviews, mobile behaviour, business websites, directories and AI recommendation systems.

Statistics, findings and CGO Media analysis from this report may be referenced provided the original geography, evidence classification, platform context and material limitations are preserved.

How to Cite This Research

A suggested citation format is:

Where an individual statistic is quoted, readers should also consult and reference the original source identified beneath that statistic where appropriate.

Journalists & Media

Journalists may quote individual statistics, findings and CGO Media analysis from this report in editorial coverage.

Where possible, please:

• Credit CGO Media.
• Link to the original research page.
• Preserve whether the statistic is UK-specific, US or multi-market.
• Retain the relevant platform or research environment.
• Distinguish consumer behaviour from ranking-factor evidence.
• Distinguish measured data from CGO Media interpretation.
• Retain material methodological limitations.

For press enquiries, methodology questions, expert commentary or supporting material, visit:

CGO Media Press & Media

Researchers & Academics

Researchers may reference this evidence synthesis provided that the original evidence type and geographic scope remain identifiable.

The report combines:

• UK audience-measurement data.
• UK search-engine market-share data.
• US consumer local-search surveys.
• US consumer review research.
• Multi-market local AI-search studies.
• First-party Google guidance.

The 50 statistics should therefore be interpreted as an evidence synthesis rather than a single homogeneous dataset.

Businesses & Organisations

Businesses may use the findings for:

• Local SEO strategy.
• Google Maps planning.
• Google Business Profile optimisation.
• Review and reputation strategy.
• Local content planning.
• Directory audits.
• Local AI visibility benchmarking.
• Board and management presentations.

External benchmarks should be combined with first-party business data wherever possible.

Useful internal metrics include:

• Google Business Profile actions.
• Calls.
• Direction requests.
• Website conversions.
• Bookings.
• Lead volume.
• Revenue.

Using UK-Specific Statistics

UK-specific evidence should retain its measurement date and source.

The second statement incorrectly turns overall platform reach into specific local-business-search behaviour.

Using US Consumer Benchmarks

US findings should remain labelled as US benchmarks.

Avoid rewriting this as:

“75% of UK consumers choose a local business within 30 minutes.”

The report does not provide evidence for that UK-specific claim.

Using Review Statistics

Review survey findings describe consumer attitudes and reported behaviour.

They should not be converted into Google ranking-factor claims.

It would not be accurate to state:

“Google requires a four-star rating for strong local rankings.”

Using Google Business Profile Statistics

Google’s Business Profile figures should be identified as first-party platform benchmarks.

They provide useful context about profile completeness and consumer consideration but should not be treated as independent UK consumer research.

Using Local AI Recommendation Statistics

Local AI recommendations can vary between repeated searches and geographic locations.

A statement such as:

is more accurate than:

“ChatGPT changes 77% of local results every time.”

The first version preserves what was actually measured.

Using Local AI Source Statistics

A source citation is not automatically the same as a business recommendation.

For example, a business website can be used to verify opening hours or service information without the associated business being presented as the recommended provider.

Citation and recommendation should therefore remain separate concepts.

Using Directory Statistics

The identification of hundreds of directories within local AI citation datasets should not be converted into a recommendation to create hundreds of business listings.

The evidence supports the importance of relevant, trusted and accurate directories — not indiscriminate directory submission.

Using Proximity Statistics

Distance data should retain its measured platform and methodology.

AI recommendations can have different geographic distributions across ChatGPT, Google AI Mode and AI Overviews.

No single radius should therefore be presented as a universal AI local-search distance threshold.

Using Google Maps Statistics

Google Maps reach, map rankings and customer actions measure different things.

The fact that Google Maps reaches a large proportion of UK adults does not demonstrate that every one of those users is conducting a commercial local search.

Charts, Infographics & Visualisations

Charts, diagrams and infographics created from this report may be referenced with attribution to:

CGO Media Research Team — Local SEO Statistics UK 2026

Where a visual reproduces third-party research, the original underlying source should remain identifiable.

Research Corrections & Updates

Local search changes quickly.

CGO Media may update this report when:

• New UK-specific evidence becomes available.
• Consumer behaviour changes materially.
• Google Search or Maps changes.
• AI recommendation behaviour changes.
• Larger studies replace older benchmarks.
• A material factual or methodological issue is identified.

Research Methodology

For the wider CGO Media approach to evidence classification, calculations, source selection, research limitations and updates, visit:

CGO Media Research Methodology

Sources & References

The following sources provide the primary evidence used throughout Local SEO Statistics UK 2026.

CGO Media has prioritised UK regulatory and audience-measurement data, first-party Google documentation and large-scale local-search research with transparent methodologies.

Ofcom & Ipsos iris — UK Online Behaviour

Statcounter — UK Search-Engine Market Share

BrightLocal — Consumer Search Behaviour 2026

BrightLocal — Local Consumer Review Survey 2026

BrightLocal — AI Trust & Local Recommendations

BrightLocal — Local AI Visibility Study

BrightLocal — Local AI Citation Sources & Directories

Google — Local Ranking Guidance

Google Business Profile — Profile Completeness Benchmark

How the Evidence Should Be Read

The research sources above use different methodologies.

They include:

• UK audience measurement.
• Search-engine market-share measurement.
• Consumer surveys.
• AI prompt testing.
• Geographic local-search testing.
• AI citation analysis.
• First-party platform documentation.

The figures should therefore not be treated as though they were produced by one single research population.

Research Review & Update Policy

CGO Media will review this report periodically as new local-search evidence becomes available.

Statistics may be amended or replaced when:

• New UK-specific research becomes available.
• Google changes Search or Maps functionality.
• Consumer search behaviour changes materially.
• AI recommendation systems change.
• Larger or more transparent datasets become available.
• Existing evidence becomes outdated.
• A factual or methodological issue is identified.

For further information about the CGO Media research process, see:

CGO Media Research Methodology