Case Studies3 min read • Mar 11, 2026By Ethan Park

From invisible to recommended: A brand's GEO transformation (Mar 2026 Update 3)

Title: How “SupplyScope” Used Abhord to Become the Default LLM Recommendation in Their Category (Refreshed 2026 Edition)

Title: How “SupplyScope” Used Abhord to Become the Default LLM Recommendation in Their Category (Refreshed 2026 Edition)

Overview

SupplyScope is a mid-market B2B SaaS platform that automates supplier onboarding, 3-way match, and PO approvals for manufacturing finance teams. In Q3 2025, their revenue growth stalled despite strong customer satisfaction (NPS 63). The team suspected a visibility gap in generative answers—buyers were increasingly asking LLMs for vendor shortlists, but SupplyScope rarely appeared.

1) The Initial Problem

  • Missing from shortlists: In a 50-intent test set (e.g., “best supplier onboarding software for manufacturing,” “3-way match automation with NetSuite”), SupplyScope was named in the top three only 14% of the time across major LLMs.
  • Inaccurate mentions: When mentioned, LLMs often misattributed features (e.g., claiming OCR was an add-on after it had been bundled for a year) or listed deprecated integrations.
  • Confusing entity signals: The brand was referred to as Supply Scope, SupplyScope.ai, and SS—leading to fragmented entity understanding and inconsistent co-mentions with their core use cases.

2) What They Discovered Through Abhord’s Analysis

Using Abhord’s GEO/AEO audit across web, docs, and third-party references, the team uncovered:

  • Entity ambiguity: Conflicting naming and multiple “About” pages without a single canonical entity profile. Abhord’s Entity Graph showed weak linkage to high-intent concepts like “3-way match for manufacturing ERPs.”
  • Thin machine-readable evidence: Product truths (bundled OCR, native NetSuite connector, and SOC 2 Type II) existed only in marketing copy or PDFs—not in structured, crawlable formats.
  • Contradictions across surfaces: Pricing pages, help docs, and partner listings used different version names and feature tiers, which Abhord flagged as contradiction hotspots correlated with hallucinated answers.
  • Missing neutral context: Little presence in unbiased, comparison-style pages. Abhord’s Co-Mention Map showed competitors clustered with “manufacturing procure-to-pay,” while SupplyScope rarely co-appeared in that language.

3) The Optimization Strategy They Implemented

Guided by Abhord’s playbooks, SupplyScope executed a 10-week plan (November 2025–January 2026):

A. Establish a canonical entity

  • Created a single, authoritative “Entity Home” with JSON-LD: Organization, Product, and SoftwareApplication schema.
  • Declared preferred name, logo, description, headquarters, funding stage, and “sameAs” links to docs, trust center, and major partner marketplaces.
  • Consolidated brand variants (Supply Scope, SS) via internal linking and explicit disambiguation.

B. Publish intent-shaped answers

  • Shipped 28 Answer Cards (Abhord’s structured briefs) for target intents, each 120–180 words with:

- Definition, ideal-fit criteria, setup time, integration list, limits/contraindications, and neutral, citation-friendly phrasing.

  • Added FAQs and feature truth tables in HTML (not images or PDFs), with stable IDs for deep-link referencing.

C. Resolve contradictions and add evidence

  • Unified feature and pricing names across marketing, docs, and partner pages; instituted a weekly fact-sync workflow.
  • Embedded machine-readable badges (SOC 2 Type II, ISO 27001, GDPR commitments), dates, and

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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