Prepared for Del Priore Hospitality

You asked to see the work.
Here it is.

Four case studies chosen because they are the closest match to what you do: local businesses that live or die on search, and the AI visibility work that sits alongside it. Client names are withheld, which is the same courtesy your venues would get.

SS
Shubham SharmaSEO & Performance Marketing · 10 years · UK, US & international clients
Before the case studies

Something worth knowing about your 200 venues

0%
Of engaged couples now use AI in wedding planning. Nearly double last year.
0%
Of wedding-planning AI answers route to The Knot, WeddingWire and Zola.
0%
Of individual venues and vendors have zero AI citation share in their own metro.
Your entire pitch is getting venues off the listing sites. AI search has quietly rebuilt that dependency, and this time there is no paid tier to buy your way out of it. The venues that get cited in a year will be the ones whose sites are structured for it now.

5W Wedding Industry AI Visibility Index 2026, published May 2026. 65+ consumer-intent prompts run through ChatGPT, Claude, Perplexity and Google AI Overviews in Q1. Couple adoption figure from The Knot Worldwide 2026 Real Weddings Study.

01–04

Four that are worth your time

Picked for relevance rather than for the biggest numbers. Wedding venues first, then the AI search work, then two local businesses that compete the way a venue does.

01
Wedding venuesLocal SEOSector experience

Wedding Venues

Agency-side · multiple venue accounts
Why this one is first
The sector you are in
The honest version

I have run venue accounts before, agency-side. I am not putting numbers against them here because those were client accounts under a previous employer and I do not have the analytics to hand, and I would rather show you nothing than show you something I cannot evidence.

What I can give you is the part that actually matters: what I learned about how venue search behaves, which is different enough from ordinary local SEO that most agencies get it wrong.

Everything below this card is evidenced with the client's own analytics.
What is different about a venue
The radius is a county, not a town

Couples will drive an hour for the right venue. Optimising to the town is the single most common mistake and it caps enquiries hard.

Listing sites outrank you for your own name

Search a venue's own name and the directory often sits above it. That is a booking leaking out at the last step, and it is fixable.

Couples search by filter, not by name

Capacity, style, indoor or outdoor, price bracket. Most venue sites have one page for all of it, so they rank for none of it.

Galleries destroy the page speed

Venues are sold on photography, and photography is what makes them slow. On mobile that costs both ranking and enquiries.

The read-across. Every mechanic above is the same one at work in the two local cases further down, where I do have the numbers.
02
SaaSTechnical SEOAI Search / AEO

AI Transcription Platform

Software, global · SaaS, technical SEO, AI search
Visitors from AI platforms
7 → 617
Where it started

Fifty target keywords, none of them visible. Thirty-three organic visitors a month and seven arriving from AI platforms. Competitors held every high-intent term.

What we actually did
  1. Split one page into fifty. Competitors kept every supported language on a single generic page, which spread relevance too thin to rank for any of them. We built a separate landing page per language, each on its own URL.
  2. Rebuilt the technical base. Metadata, schema, crawl and indexing errors, page structure, content aligned to intent rather than to a keyword list.
  3. Wrote for people, not for models. AI systems surface content that reads as genuinely useful. Every page researched and written in a natural voice. Nothing generated.
  4. Built authority deliberately. Roughly 400 quality links a month, which is what let the new pages index and rank at the pace they did.
Results
Monthly organic visitors
33→619+1,776%
Visitors from AI platforms
7→617+8,714%
Search clicks, monthly
27→2,585+9,474%
Search impressions, monthly
240→9,310+3,779%
617most recent
Monthly visitors from AI platformsstarted at 7
Nearly half of this site's traffic now arrives from AI platforms rather than Google. That did not happen by accident and it did not happen through ordinary SEO.
03
Local SEOGoogle Business ProfileAI Search

Dental Practice, Central London

Single location, United Kingdom · the same search mechanics a venue lives on
Keywords in the local top 10
1 → 21
Where it started

Twenty-six target terms. One of them in the top ten. In Google Maps, which is where a location business actually gets found, the picture was worse: almost nothing ranked, and the practice was invisible for every "near me" variant.

What moved it
  1. Treated Maps as the primary channel. Category and service structuring on the Business Profile, review velocity, location signals built into the site itself.
  2. A page per service and per intent. Not one catch-all page. Separate pages for what people actually search, written for someone deciding rather than browsing.
  3. Fixed what blocked it. Structure, internal linking and schema, so individual pages could rank without leaning on the homepage.
  4. Wrote for the questions, not the keywords. Which is also what put the practice into AI answers for the first time.
Swap treatment for wedding package and this is the same build. Twenty-six terms is roughly what a venue competes on across its own county.
Results
Organic keywords in top 10
1→21of 26 tracked
Google Maps keywords in top 10
1→19of 26 tracked
Monthly organic visitors
510→2,337+358%
Visitors from AI platforms
1→34+3,300%
21 of 26Google organic
Keywords in the top 10from 1
19 of 26Google Maps
Keywords in the top 10from 1
Maps is the one that pays. For a location business the map pack decides the enquiry. It went from one ranking term to nineteen.
04
HospitalityLocal SEOAI Search

Hospitality Group

Multi-site hospitality operator · local SEO and AI search
Visitors from AI platforms
5 → 290
What happened

Organic traffic grew 73%, from 1,747 to 3,015 monthly visitors. Respectable, not remarkable. The interesting number is the other one.

Traffic from AI platforms went from 5 visitors a month to 290. Same site, same period, same work. AI visibility grew roughly eighty times faster than Google traffic did.

This is the pattern worth watching. AI visibility is not a slower version of SEO and it does not move in proportion to it. On a hospitality site, where people ask open questions rather than typing keywords, it moves on its own curve entirely.
Results
Monthly organic visitors
1,747→3,015+73%
Visitors from AI platforms
5→290+5,700%
+73%Google organic
Growth over the period
+5,700%AI platforms
Same site, same period, same work
Read the two bars together. Google grew by three quarters. AI grew by fifty-eight times. If you only measure organic sessions the second number is invisible to you, and it is the one that compounds.
Further work in the same shape

Other local businesses running the same playbook

The four above are the ones closest to what you do. These are the rest of the local and AI visibility accounts, in case it is useful to see the pattern hold across sectors.

+0
More people a month reaching these sites from search than when the work started.
0×
More visitors a month arriving from ChatGPT and other AI platforms. 52 up to 1,370.
11 of 11
Improved on both Google and AI visibility. Every one of them, not most of them.
AccountSectorOrganic, monthlyAI platforms, monthly
UK dental practiceHealthcare, UK510 → 2,3371 → 34
US dental groupHealthcare, US640 → 5,5766 → 52
Lending platformFinancial services, South Africa179 → 4,3967 → 68
Credit unionFinancial services, US1,485 → 4,3212 → 84
Hospitality groupHospitality1,747 → 3,0155 → 290
Personal injury firmLegal, US12,393 → 33,80816 → 100
Orthodontic practiceHealthcare, US178 → 1,1451 → 29
Dental clinicHealthcare, US1,789 → 10,4504 → 45
Family dental practiceHealthcare, US382 → 2,4212 → 29
Dental care groupHealthcare, US1,353 → 4,4071 → 22
Transcription platformSoftware, global33 → 6197 → 617

Client names withheld. Every figure taken directly from the client's own Google Analytics.

If it is useful

What I would do with one of your venues

Not a proposal. Pick a venue you are not fully happy with and I will run this properly and send you what I find, at no cost and with no expectation. You keep the work either way. It is a better way to judge someone than a page like this one.

Week one

Where it actually stands

Full technical and local audit, plus the part nobody is running yet: exactly what ChatGPT, Perplexity and Google AI Overviews say when someone asks for a venue in that county, and who they name instead.

Weeks two to six

Fix the foundation

Map pack and Business Profile, a page per package and per intent, schema and structure so individual pages rank alone. This is what moved the London practice from one ranking term to twenty-one.

Month three onward

Get cited, not just ranked

Content written to answer the questions couples actually ask, structured so AI systems can quote it. This is the eighty-four percent problem, and it is solvable while almost nobody is working on it.

Shubham Sharma
shub5721@gmail.com
SEO, Google Ads, Meta Ads and AI search visibility
White-label for agencies, direct for businesses
Prepared for Del Priore Hospitality
Client names withheld throughout
All figures from client analytics