Case 007 · Marketing Tech · AI Visibility

AI Visibility (GEO) Strategy for a Consumer Brand Facing Category Compression

A consumer brand came to us with a specific concern. Their category was consolidating inside AI answers. Every time a buyer asked ChatGPT, Gemini, or Perplexity for the top three products in their space, three names came back. Theirs was not one of them. We ran a full generative engine optimization diagnostic, mapped the citation sources shaping their AI narrative, and delivered a prioritized strategy to get them inside the answer.

+388%
YoY growth in Gemini referral traffic (category-wide signal)
3x
Conversion rate on AI-driven traffic vs traditional channels
91%
Higher paid CTR when cited in AI Overviews
01 · Context

The Brief

Search is no longer a list of links. For the first time in twenty years, buyers are not ranking options. AI is choosing for them.

The brand had solid traditional SEO, ranked well on Google, and had a good paid strategy. None of it was reflected inside AI answers. When their target buyer asked ChatGPT or Gemini for the top three options in their category, three competitor names came back. Theirs was invisible.

The brief was direct. Diagnose where the brand was invisible, why, and what would move the needle. Deliver a strategy, not a report.

02 · Decision

Why They Chose Solprime

Three reasons.

Reason 01

Category-level diagnostic, not vanity metrics.

Other agencies offered dashboards tracking brand mentions. We offered a full audit across ChatGPT, Gemini, Perplexity, and Google AI Overviews for 15 to 20 real buyer-intent prompts, with citation-source mapping to show why they were being excluded.

Reason 02

Prompt strategy, not keyword strategy.

SEO agencies were still selling keyword targeting. We reframed the problem around prompts, mentions, sentiment, citations, and entities. A different game with different mechanics.

Reason 03

Actionable, not academic.

The deliverable was a 30-60-90 day plan with named citation sources to influence, specific corrections to publish, and entity signals to seed. Not a slide deck of trends.

03 · Delivery

What We Built

A five-layer generative engine optimization engagement.

Layer 01 · Visibility Audit

Full category diagnostic across four AI surfaces

ChatGPT, Gemini, Perplexity, and Google AI Overviews. 15 to 20 buyer-intent prompts run programmatically. Every response captured, competitors identified, citation sources logged.

Layer 02 · Citation Source Map

Which third parties are writing the brand’s story

Brand-owned content was representing only a single-digit percentage of AI sources. The rest came from reviews, forums, and competitor comparisons. We mapped which sources AI models were pulling from, and prioritized which to influence first.

Layer 03 · Narrative Correction Plan

Fix the misinformation AI keeps repeating

Outdated pricing, wrong specs, and repeated myths surfaced across multiple prompts. We built a correction workstream with named sources, target corrections, and a sequence.

Layer 04 · Entity and Knowledge Graph Strategy

Position the brand as a canonical source

Structured data, schema markup, Wikipedia-adjacent signal building, and controlled first-party publishing. The goal is not to rank a page. The goal is to become an entity AI models cite.

Layer 05 · Prompt and Mentions Tracking Framework

Replace rank tracking with mention tracking

A framework for the brand to run monthly, tracking prompt-level visibility, mention frequency, sentiment, and citation share against the top three competitors.

04 · Technology

The Stack

AI orchestration

LLM APIs (ChatGPT, Claude, Gemini, Perplexity)

Data

Structured prompt logs, citation graph, mention database

Analysis

Python, embeddings, sentiment classification

Deliverable

Written strategy document, prioritized action plan, tracking framework

Infra

Internal tooling, reusable across future GEO engagements

05 · Execution

How the Engagement Looked

One week, fixed scope, fixed fee. Four phases, all delivered inside Week 1.

Week 1

Kickoff, category and prompt selection, buyer intent mapping

Week 1

GEO diagnostic across four AI surfaces, competitor visibility mapping

Week 1

Citation source mapping, entity gap analysis, narrative correction plan

Week 1

30-60-90 day action plan, tracking framework handover, readout call

06 · Results

The Outcomes

What the brand walked away with, delivered inside one week.

1 week

Diagnostic delivered inside one week, fixed scope, fixed fee.

4 surfaces

Category-level baseline established across ChatGPT, Gemini, Perplexity, and Google AI Overviews.

Top 10

Citation source map identifying the top ten third-party sources shaping the brand’s AI narrative.

30-60-90

Prioritized 30-60-90 day action plan with named sources, target corrections, and entity signals.

Monthly

Tracking framework transferred to the brand for ongoing monthly monitoring.

Phase 2

Foundation for Phase 2 execution, scoped separately.

Category context, published data, not client-specific:

+388%

YoY growth in Gemini referral traffic.

+52%

YoY growth in ChatGPT referral traffic.

3x

Conversion rate on AI-driven traffic vs traditional channels.

35%

Lift in organic clicks when cited in AI Overviews.

91%

Higher paid CTR when cited in AI Overviews.

07 · Implications

Why This Matters

Search is now winner-takes-all. There is no page two in an AI conversation. Brands that are not inside the answer are erased from the buyer’s consideration set before they ever visit a website.

Budgets for GEO are forming faster than tooling. The window to establish category entity dominance is now, not next year.

Every diagnostic we run reinforces the same pattern. The brands that show up in AI answers in 2026 will be the ones that started seeding entity signals in 2025.

More Work

Client name confidential. Details verifiable under NDA.

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