Quoted First
Case studies

From footnote to first citation.

Three engagements, three categories, the numbers attached. Every figure below comes from the same weekly monitoring our clients see.

Ledgerly · B2B SaaS Solstice Skin · DTC Lumen Health · Healthcare
B2B SaaS · Fintech · Growth plan

Ledgerly: from “a receipt-scanning app” to the first name ChatGPT gives for startup expense software.

Great SEO, zero AI presence — and when models did mention Ledgerly, they described a product from 2021.

The challenge

Ledgerly ranked top-five in Google for its core terms. But across 60 priority prompts — “best expense management software for startups”, “Ledgerly vs …”, “how to automate receipt matching” — ChatGPT and Perplexity named larger, older competitors every time. When Ledgerly did appear, 38% of answers described it as “a receipt-scanning app”, its positioning from three years earlier.

What the audit found

  • A 2023 robots.txt decision was still blocking GPTBot and PerplexityBot from the entire site.
  • Product pages were long and feature-led, with no direct answers models could lift.
  • Entity drift: Crunchbase, G2 and LinkedIn descriptions all disagreed with the website — and with each other.
  • No comparison or “alternatives” pages, though 30% of priority prompts were comparative.
  • The sources engines cited for these prompts — two fintech publications, r/startups and G2 — barely mentioned Ledgerly.

What we did

  • Technical: unblocked AI crawlers, shipped llms.txt, fixed canonical issues on pricing pages.
  • Content: rewrote 14 pages with answer-first structure and comparison tables; built six “Ledgerly vs” pages and a startup expense-management buyer's guide.
  • Data: published The State of Startup Spend 2026 from anonymised customer data — picked up by nine publications, including both fintech outlets the engines cited.
  • Entity: synchronised descriptions across all profiles; implemented Organization, Product and FAQ schema.
  • Authority: earned inclusion in six comparison articles; transparent, useful participation in r/startups threads.

Results after 11 weeks

Ledgerly became the first-cited source for “best expense management software for startups” in both ChatGPT and Perplexity, and appears in the answer for 41% of priority prompts (from 8%). Stale “receipt-scanning” descriptions dropped to zero in tracked answers. AI-referred demo requests rose 156% quarter over quarter.

Within eight weeks, ChatGPT went from never mentioning us to naming us first for our two most valuable prompts. Demo requests from AI referrals are now a line item in our board deck.
Maya Chen
VP Marketing, Ledgerly
DTC · Skincare · Growth plan

Solstice Skin: turning product pages into the sources Perplexity quotes for sensitive-skin questions.

Strong blog traffic, strong SEO — and AI assistants recommending the same three dermatologist brands every time.

The challenge

Solstice Skin's content brought in traffic, but when shoppers asked ChatGPT or Perplexity “what's the best sunscreen for sensitive, acne-prone skin?”, the answers named incumbents. Solstice appeared in 6% of tracked prompts. Product pages were pure marketing copy: nothing a model could quote as a fact.

What the audit found

  • Product pages contained no answerable information — no ingredient tables, no “who it's for / who it's not for”, no clinical summaries.
  • A Shopify app injected key product details client-side, invisible to most extractors.
  • Ingredient and efficacy claims weren't corroborated anywhere models trust: dermatology review sites, skincare communities, editorial “best of” lists.
  • No FAQ or Product schema.

What we did

  • Content: rewrote every product page with a direct “best for” summary, INCI ingredient table, clinical-study summary and honest “not for you if” section; built a 42-page Sensitive Skin Answer Hub from customer-service transcripts.
  • Technical: moved product facts server-side; implemented Product, FAQ and Review schema.
  • Authority: earned inclusion in four editorial “best sunscreen for acne-prone skin” lists; secured expert reviews on two dermatology review platforms; supported a fully compliant, non-incentivised review programme.
  • Entity: aligned brand and product descriptions across retailer listings, social profiles and directories.

Results after 16 weeks

Solstice is now cited in 71% of tracked sensitive-skin prompts on Perplexity, and is the first-cited source for “best mineral sunscreen for acne-prone skin” in ChatGPT and Perplexity, with an average citation position of 1.8. AI-referred sessions rose 340%; revenue from those sessions rose 212%.

We'd spent years on SEO and had nothing to show for it in Perplexity. Quoted First rebuilt our product pages so they actually get quoted. It's a different game and they know the rules.
Daniel Okafor
Head of Growth, Solstice Skin
Healthcare · 40-clinic provider network · Enterprise plan

Lumen Health: becoming the go-to reference for post-surgical rehab questions in a regulated category.

AI answers cited national reference sites and never local providers. Every word needed clinical review. The site had a decade of technical debt.

The challenge

Patients were asking assistants “how do I choose a physical therapy clinic after knee surgery?” and “how long is recovery after ACL repair?” — and getting answers built entirely from national reference sites. Lumen's 40 clinics were invisible, and in three tracked answers, models stated services Lumen didn't offer.

What the audit found

  • Content was written for hospitals, not patients: dense, un-scannable, with no named clinical authors.
  • Forty locations with inconsistent names, addresses and service lists across the site, Google profiles and directories.
  • No governance path for getting content through legal and medical review quickly.
  • Server-side rendering issues meant location pages often returned empty content to crawlers.

What we did

  • Prompt map: built from six months of call-centre logs — 320 patient questions clustered by condition and stage.
  • Content: 60 medically reviewed answer pages with named clinician authors and credentials; a clinical review workflow with a five-day SLA built into the process.
  • Data: an annual, anonymised Recovery Benchmarks report — now cited by two professional associations and regional press.
  • Entity: MedicalClinic, Physician and MedicalWebPage schema; NAP and service-list consistency across all 40 locations.
  • Technical: fixed rendering of location pages; AI crawler policy aligned with the compliance team.

Results after two quarters

Lumen holds 63% share of voice on priority local prompts and is first-cited for 22 of 80 priority prompts across engines. Appointment requests attributed to AI referrals rose 89%. Accuracy monitoring caught three incorrect service claims, each corrected at the source within two weeks.

The reporting alone changed how our leadership thinks about search. Seeing exactly what AI says about us — and watching it improve week over week — made the case for itself.
Priya Raman
Director of Digital, Lumen Health
The pattern

Different categories. Same four fixes.

01

Let the models in

Two of three clients were accidentally blocking or hiding content from AI crawlers. Fastest win, every time.

02

Say the answer first

Every rewrite led with a direct, quotable statement. Extractability moved the numbers more than volume.

03

Own your facts

Consistent entity data — everywhere — is what let models describe each brand correctly and confidently.

04

Get corroborated

Original data and genuine mentions in the sources engines already cited turned claims into citations.

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