Case Study: How a Mid-Sized Agency Turned a "Zero-Click" Crisis into 300% ROI

Executive Summary

The Client: "TechFlow" (B2B SaaS, $50M ARR) – A composite case based on three agency clients, anonymized for this report.

The Problem: Organic traffic from informational queries dropped 60% YoY as Google's AI Overviews began answering questions directly on the SERP. The agency's traditional SEO retainer was delivering diminishing returns.

The Solution: A strategic pivot from "traffic volume" to "generative visibility." The agency implemented a GEO (Generative Engine Optimization) strategy focusing on Entity Authority and Answer Engine Optimization (AEO).

The Result: While informational traffic declined, commercial-intent traffic increased by 25%. More importantly, demo requests from accounts with 500+ employees grew by 40%, and average deal size increased by 50%, resulting in a 300% ROI compared to the previous SEO-only approach.

The Challenge: When Traditional SEO Stopped Working

For three years, TechFlow paid their agency $8,000/month for a standard SEO package: four optimized blog posts and ten backlinks monthly.

From 2021 to 2022, the strategy worked. Organic traffic grew 35% year-over-year, and the marketing team celebrated consistent MQL growth.

But 2023 brought a seismic shift. Google's AI Overviews began answering user queries directly on the search results page. By early 2024, TechFlow's top-of-funnel traffic had evaporated—a 60% drop in visits from informational keywords like "what is [category]" and "how to choose [solution]."

The CMO was ready to cut the retainer entirely. "We're paying for traffic that doesn't exist anymore," she told the agency. The problem wasn't poor execution—it was that they were optimizing for a search landscape that had fundamentally changed.

The Pivot: Building a GEO-First Strategy

The agency proposed a radical shift: stop chasing clicks, start chasing citations. They replaced the traditional SEO retainer with a six-month GEO strategy priced at $10,000/month.

Month 1: The Visibility Audit

Using a structured GEO audit framework, the agency tested how AI engines understood TechFlow's brand. They asked ChatGPT, Perplexity, and Google Gemini variations of bottom-funnel questions like "What is the best [category] tool for enterprises?"

The results were alarming:

  • ChatGPT couldn't describe TechFlow's core differentiators and instead listed three competitors

  • Perplexity cited competitors in 8 out of 10 test queries

  • Google Gemini hallucinated outdated pricing information

The diagnosis: TechFlow had strong Domain Authority (DA 65) but zero Entity Authority. Search engines knew the website existed, but AI engines didn't understand what the company actually did.

Months 2-4: Knowledge Architecture

Instead of writing generic "Ultimate Guides," the agency executed three parallel workstreams:

1. Strategic PR Placement

Published three in-depth case studies in TechCrunch, VentureBeat, and a leading industry journal—all sources frequently cited by GPT-4's training data. Each piece included specific product features, use cases, and customer outcomes.

2. Schema Markup Overhaul

Implemented comprehensive Organization and Product schema across the site. This included disambiguating the brand from similarly named companies and clearly defining product categories using schema.org vocabulary that LLMs recognize.

3. Answer-First Content Architecture

Rewrote the top 15 product and category pages to answer commercial-intent questions in the first 50 words. For example, instead of starting with "Welcome to TechFlow," the homepage opened with: "TechFlow is an enterprise workflow automation platform that helps IT teams reduce manual tasks by 70%. Used by 2,000+ companies including [logos]."

Months 5-6: Monitoring and Correction

The agency shifted reporting from "keyword rankings" to "Share of Model (SoM)"—tracking how often TechFlow appeared in AI-generated answers compared to competitors.

When ChatGPT hallucinated that TechFlow didn't support a key integration, the team published a correction via press release and updated structured data across Wikidata and the company's knowledge graph.

The Results: Quality Over Quantity

Six months after the pivot, the metrics told a different story.

Metric
Before GEO
After GEO
Change

Informational Traffic

45K visits/mo

18K visits/mo

-60%

Commercial-Intent Traffic

8K visits/mo

10K visits/mo

+25%

Demo Requests (500+ employees)

12/month

17/month

+42%

Average Deal Size

$48K

$72K

+50%

Monthly Pipeline Value

$576K

$1.22M

+112%

The ROI Breakdown

Previous SEO approach:

  • Cost: $8,000/month

  • Result: 12 demos/month × $48K ACV = $576K pipeline monthly

  • ROI: 7.2x

New GEO approach:

  • Cost: $10,000/month

  • Result: 17 demos/month × $72K ACV = $1.22M pipeline monthly

  • ROI: 12.2x

The 300% improvement in ROI wasn't about traffic volume—it was about traffic quality. Users asking Perplexity "What is the best enterprise solution for [use case]?" were already bottom-funnel buyers. By controlling how AI answered those questions, TechFlow influenced purchase decisions before prospects even visited the website.

Key Takeaway: Visibility Beats Volume

This case study demonstrates that agencies can deliver premium results—and justify higher retainers—by shifting from traffic metrics to influence metrics. When AI engines cite your brand as the answer to high-intent questions, you don't need to rank #1 on Google. You've already won the consideration phase.

The controlled variables matter: TechFlow's pricing remained unchanged, the sales team stayed the same size, and no major product launches occurred during this period. The increase in deal size came from attracting larger enterprise accounts who discovered TechFlow through AI-assisted research.

Implementation Questions

Q: What's the first step to replicate this strategy?

A: Run a visibility audit. Ask 20 high-intent questions related to your product across ChatGPT, Perplexity, and Google's AI Overview. Document whether your brand appears, what's said about you, and who's cited instead. That gap analysis becomes your roadmap.

Q: How quickly can we expect results in AI engines?

A: Changes in RAG (Retrieval-Augmented Generation) engines like Perplexity and Bing Chat updated within 2-4 weeks after we published new authoritative content. Core model training updates (like GPT-4 to GPT-5) take longer, but RAG systems handle 80% of current AI search use cases.

Q: Can every client expect 300% ROI improvement?

A: No. This strategy works best for "challenger brands" in B2B or high-ticket B2C categories. If a brand already dominates its category (think Salesforce or HubSpot), the upside is smaller. For mid-market brands currently invisible to AI engines, the potential impact is massive because you're starting from zero.

Q: What was the single most critical deliverable?

A: Creating an "Entity Home"—a single source of truth that clearly defines who you are, what you do, and why you're different, formatted specifically for LLMs to understand and cite. For TechFlow, this was a restructured homepage plus a dedicated /about/company page with comprehensive schema markup.

Q: How did you convince the client to accept lower traffic numbers?

A: We reframed success metrics before starting. In the proposal, we explicitly stated: "We're trading casual browsers for qualified buyers. You should expect informational traffic to decline while commercial-intent engagement increases." By setting expectations upfront and showing weekly SoM reports, the client understood the strategy was working even as vanity metrics dipped.

References & Further Reading

Real-world GEO case studies that validate this approach:

Single Grain:

Maximus Labs:

Xponent21:

AthenaHQ:


Want to assess your brand's AI visibility? Start by searching for your top commercial-intent keywords across ChatGPT, Perplexity, and Google AI Overviews. If competitors appear but you don't, you have an Entity Authority gap—and a massive opportunity.

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