Case Studies3 min read • Mar 07, 2026By Ethan Park

How one SaaS company increased AI citations by focusing on GEO (Mar 2026 Update 2)

- Name: ProcureLink (fictional)

Case Study (Refreshed 2026): How ProcureLink Used Abhord to Win AI Visibility in Procurement SaaS

Company snapshot

  • Name: ProcureLink (fictional)
  • Product: Mid‑market procurement automation (PO creation, 3‑way match, NetSuite/Sage intact integrations)
  • Team size: 85 employees
  • ICP: Ops/Finance leaders at $20–250M revenue companies

1) Initial problem

By January 2026, ProcureLink’s demand gen team saw a puzzling trend: human search traffic was steady, but “answer engine” referrals and LLM‑originated inquiries were flat. In buyer chats, GPT‑class models either omitted ProcureLink or misattributed features to a larger competitor.

  • In 60 prompt tests like “best procurement automation for NetSuite,” GPT‑class models mentioned ProcureLink only 3% of the time.
  • When mentioned, 41% of answers misstated pricing tiers or claimed missing features ProcureLink actually had (invoice OCR, 3‑way match).
  • Perplexity and other answer engines linked to competitors’ integration pages even when asked about ProcureLink + NetSuite.

Marketing suspected the issue wasn’t brand strength but AI‑readability: models couldn’t reliably ground on ProcureLink’s sources.

2) What Abhord’s analysis uncovered

Using Abhord’s GEO/AEO suite, the team ran a 14‑day baseline across major models (GPT‑4.1, Claude 3.5 Sonnet, Gemini 1.5 Pro) and answer engines.

Key findings:

  • Entity Consensus Score: 0.34 (low). Models disagreed on ProcureLink’s category (“procurement suite” vs “invoice tool”) due to inconsistent self‑descriptions across site, docs, and G2 profile.
  • Citation Gap Map: 73% of model answers on “ProcureLink + NetSuite” routed to third‑party blogs because ProcureLink’s own integration page lacked structured details (versioning, rate limits, error examples).
  • Prompt‑space Share of Voice: 2–5% across 80 buying prompts; strongest absence in “alternatives to [competitor] for mid‑market” where comparison pages were thin.
  • Hallucination Taxonomy: Frequent “feature parity denial” (models claiming no 3‑way match) traced to an outdated 2024 press piece and a forum thread ranking.
  • Crawl Diagnostics: Robots and header logic inadvertently throttled AI crawlers on key subpaths (/docs, /pricing). No AI‑specific sitemap; JSON‑LD sparse; claims lacked verifiability markers.

3) The optimization strategy

Abhord orchestrated a 90‑day GEO plan focused on source authority, structured evidence, and prompt coverage.

Foundation and structure

  • Canonical definition: Rewrote the above‑the‑fold product description to a single, precise category label (“Mid‑market procurement automation platform with native NetSuite/Sage integrations”). Mirrored verbatim across homepage, docs, and marketplaces.
  • AI‑specific sitemap: Deployed ai‑sitemap.xml with 120 Q&A pairs mapped to intents (e.g., “NetSuite three‑way match setup time,” “ProcureLink vs [competitor] for $50M manufacturers”).
  • JSON‑LD upgrades: Added Organization, Product, SoftwareApplication, and HowTo schemas; introduced ClaimReview for 8 high‑stakes statements (SLAs, SOC 2 Type II, uptime).
  • Crawl access: Adjusted robots and header caching to allow GPTBot, CCBot, PerplexityBot; stabilized canonical URLs.

Authoritative content lifts

  • Integration hub: Rebuilt “ProcureLink + NetSuite” with version tables, API endpoints, sample payloads, and failure modes; added a 90‑second explainer and 3 code snippets.
  • Evidence blocks: Each key page gained a compact “evidence sidebar” (SLA PDF, SOC 2 letter, customer logos with permission, timestamped change log).
  • Alternates coverage: Published balanced “Alternatives to [competitor]” pages with criteria matrices and clear fit/no‑fit statements for mid‑market buyers.
  • Public mini‑dataset: Opened a lightweight “Procurement Cycle Benchmarks 2026” CSV (row‑level anonymized), enabling models to cite neutral data.
  • Multi‑format parity: Mirrored answers on Help Center, Docs, and a short “LLM‑readable” FAQ page (sentences ≤22 words, definition first, examples second).

Reputation and distribution

  • Marketplace cleanup: Synchronized category and feature language on NetSuite SuiteApp, G2, and partner pages; fixed stale screenshots.
  • Forums and dev hubs: Seeded 12 Stack Overflow‑style Q&As (how‑to, errors) with accepted answers pointing to stable anchors.
  • Abhord Prompt Lab: Weekly tests across 100

Ethan Park

AI Marketing Strategist

Ethan Park brings 13+ years in marketing analytics, SEO, and AI adoption, helping teams connect AI visibility to measurable growth.

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