Case StudyAI Search · First-Party · Fractional CMO
Data-Mania · First-Party
How I Turned AI Search Into $41.7K in Sales for My Own Business
In early 2024, Data-Mania was close to invisible when buyers asked AI assistants for a fractional CMO. Today ChatGPT, Gemini and Google’s AI Overviews recommend me by name, and four buyers who found me that way have paid about $41.7K.
$41.7Kfrom four buyers
who found me via AI
who found me via AI
#1on four high-intent
buyer questions
buyer questions
318,850Microsoft Copilot
citations in 3 months
citations in 3 months
6 daysto counted
Google gains
Google gains
Business Profile
BusinessData-Mania, a fractional CMO and AI-native growth practice
StageBootstrapped, founder-led
ModelServices plus digital products
TeamSolo founder
The Problem
Buyers had started asking ChatGPT, Claude and Perplexity for recommendations, and I rarely came up
Traditional SEO tactics weren’t moving AI answers
No reliable way to measure AI visibility
Root CausePositioning and content AI engines couldn’t categorize or cite
The Outcome
About $41.7K from four buyers who found me through AI search
#1 on four high-intent buyer questions across AI engines
318,850 Microsoft Copilot citations across 160 pages in three months
Timeframe: July 2024 to October 2026
The Challenge
Buyers Were Asking AI for a Fractional CMO, and I Wasn’t in the Answer
I had to solve AI search for my own business before I could sell it to anyone.
In early 2024 I noticed my prospects had changed how they discover solutions. They were asking ChatGPT, Claude and Perplexity who to hire, and the answers recommended other people.
Specifically:
I was close to invisible on the buyer questions my clients ask
Backlink and keyword tactics weren’t moving AI answers
No playbook existed for measuring AI visibility, let alone improving it
The Transformation
Before & After: From Invisible to Recommended by Name
Dimension
Before
After
AI Visibility
Rarely named in AI answers for fractional CMO and GTM questions
#1 rankings on four buyer questions in December 2025, and named by Google’s AI Overview among top fractional CMOs for tech startups
Revenue
Buyers asking AI who to hire were sent to other people
About $41.7K from four buyers who found me through AI search
Citations
Positioning and content AI engines couldn’t categorize or cite
318,850 Microsoft Copilot citations across 160 pages in three months, 58.9% on commercial or comparison questions
Measurement
No reliable way to measure AI visibility
A measurement standard: counted metrics first, sampled scores treated as direction
The Solution
I Treated AI Visibility as an Engineering Problem
Phase 1 · July to December 2024
Make Data-Mania Easy for AI Engines to Categorize
Specific positioning that names exactly who I serve, used the same way across every public profile.
Educational content that answers real buyer questions with frameworks and numbers, ahead of promotional copy.
Third-party validation through features, speaking, books and client results that engines can verify.
Weekly tracking of the buyer questions I wanted to win, across ChatGPT, Claude, Perplexity and Google AI Overviews.
Phase 2 · 2025
Double Down on What Engines Cite
I put more effort into the formats engines were quoting, especially tool comparisons and buying guides.
Phase 3 · 2026
Audit, Fix and Measure Like a Client Engagement
A Semrush AI Search Health audit cross-checked against my Bing citation data. It showed my top four pages earned 64.3% of my AI citations, so I strengthened pages I already owned before writing new ones.
A month of work driven by ThriveStack CitedBy’s recommendations, which moved two posts up in Google within six days.
A measurement standard: 40 runs of the same 25 prompts showed AI visibility scores swing about 10 points on their own. I report counted metrics first and treat sampled scores as direction.
The Results
AI Search Now Brings Me Paying Clients
$41.7K
from four buyers who found me through AI search
#1
on four high-intent buyer questions across AI engines
318,850
Microsoft Copilot citations across 160 pages in three months
6 days
to counted Google gains from CitedBy-driven fixes
About $41.7K from four buyers who found me through AI search. The first came through a ChatGPT recommendation in July 2025. That client, TeamCentral, is still with me 15 months later.
Who came in: TeamCentral via ChatGPT, Semrush and ThriveStack via my AI search work, and Bear.ai, a YC-backed generative engine optimization company whose own AI visibility dashboard surfaced a data-mania.com article.
#1 rankings in December 2025 on four buyer questions, including “Which fractional CMOs specialize in AI startups?” and “Who are the most reputable GTM engineers?”
Named by Google’s AI Overview among top fractional CMOs for tech startups.
318,850 Microsoft Copilot citations across 160 pages in the three months to July 2026. 58.9% landed on commercial or comparison questions, the ones buyers ask while choosing a vendor.
Counted Google gains in six days: one post went from 13 to 59 impressions, and another moved from average position 46.8 to 18.4.
The shortest sales cycle of any channel I’ve run. The ChatGPT-sourced client needed no nurture sequence.
A product: I packaged the method into AI Search Rank, a $37 course, and sold about $1K of it in 2025.
What AI Search Companies Say
“
Lillian put ThriveStack CitedBy through a full working month on her own site and turned its recommendations into Google AI gains within a week. 13 of the 15 issues she reported became product fixes.
Gururaj PandurangiFounder, ThriveStack
“
Lillian understood our bet on selling data over advice and told the story clearly to a founder audience. The feature was easy to work with and approved with a single edit.
Gintare RimolaityteChief Commercial Officer, Trendos
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