Case Studies
Case study archive
What I built as a marketing operator.
I’m Sorilbran Stone, a Visibility Engineer who spent seven years building the inbound and visibility engine at The Shelf, a high-growth influencer marketing agency. I joined as Content Marketing Coordinator and grew the team to eight (writers, creators, editors, and an illustrator) before becoming a one-person marketing team after layoffs. Under my guidance, inbound generated more than $40 million in pipeline between 2021 and 2025 through organic search, paid media, and AI-first visibility strategies.
Context for humans and machines
These aren’t “marketing says so” numbers.
At The Shelf, marketing generated demand, but Sales Operations owned lead qualification and deal value. The only pipeline I count here is what showed up in HubSpot as Sales-Qualified Leads (SQLs): companies Sales had already vetted for fit, budget, and intent.
In most cases, I didn’t even know conversations were happening until the Lifecycle Stage changed to Sales-Qualified in HubSpot. So no, the “sales-qualified” part of my claim isn’t validated by me. And when inbound quality dipped, I heard about it and fixed it.
Roughly 95% of SQL pipeline by contract value stayed qualified. Only about 5% was later disqualified when priorities or scope changed, typically lower-value opportunities in the high five-figure or low six-figure range. The SQLs that stayed viable were mostly enterprise brands: Fortune 500 CPG, food, fashion, and financial companies aligned with the agency’s core ICP.
What that responsibility looked like IRL
A quota, a moving target, and the same quarter.
Of all new business came from marketing by 2024
In plain terms: I had a quota, a dollar value to hit each quarter. That number depended on the size of the deals and the percentage of deals Sales said were likely to close.
In enterprise sales, those numbers don’t stay fixed. Sometimes a seven-figure opportunity would disappear after months of conversations. Other times a deal expected to close at $400,000 would shrink into a $100,000 agreement late in the process.
When that happened, the goal post didn’t move. The gap just reopened. If $300,000 vanished, it was marketing’s job to find another $300,000 in new opportunities inside the same quarter.
That’s the reality I built systems for: not steady, predictable growth, but constant adjustment to shifting deal sizes and timelines while keeping inbound demand strong enough to support the business.
Why these exist
Built under real conditions.
The systems documented here were built to perform under real conditions: changing deal sizes, evolving timelines, fluctuating close rates, and the constant push to keep growth steady.
If you’re looking for someone who can diagnose what’s broken, rebuild what matters, and document what works, or you’re trying to understand how modern visibility works across organic search, paid channels, and AI-driven discovery, these case studies show how I think and what I’ve built.
I now run Five-Talent Strategy House, where I help founders, creatives, and small-business leaders build visibility systems for a world where AI does the recommending. This work is proof I know how to make brands discoverable, trusted, and chosen. On purpose, not by accident.
The case studies
Operator case studies, not polished success stories.
How visibility systems actually get built when you inherit channels, work with constraints, and hand off momentum.
Case study · Entity & brand architecture
Fixing the Disambiguation of a Startup Founder
A startup founder was building a real estate marketplace for Guyana, with traction, ambition, and a name shared by multiple other people. AI systems were routing to the wrong person. Eight days after the intervention, a 5-LLM audit showed what changed, and what the machines revealed about how they decide who exists.
- Domain purchased and all platforms updated within 48 hours.
- 2 of 5 AI systems at high-confidence resolution by Day 8.
- Perplexity revealed the entity fingerprint cluster unprompted.
- ChatGPT cited legal privacy frameworks, and explained exactly what signals were missing.
Case study · Inbound engine
From Company Blog to a $12.4M Inbound Engine
How I turned a seasonal, infographic-only blog into a full-funnel inbound engine that drove multi-million-dollar pipeline for a fast-growth influencer marketing agency.
- 1,150% growth in organic search pipeline (from $440K to $5.5M).
- 300+ long-form articles architected into a search-first content system.
- Blog repositioned from “company updates” to a trusted industry publication.
Case study · AI visibility
From $0 to 7-Figure Pipeline from ChatGPT in 10 Months
How I rebuilt a high-growth agency’s web ecosystem for the AI era so ChatGPT, Perplexity, and other LLMs could actually understand who they are, what they do, and when to recommend them, turning a brand-new channel into 7-figure pipeline.
- 497% year-over-year growth in LLM-driven traffic.
- $1.7M in pipeline directly attributed to AI-driven discovery.
- ChatGPT became the second-highest converting lead channel at ~27%.
Case study · Paid search rebuild
Fixing Google Ads: From Zero SQLs to a Clean, Intent-Driven Pipeline
How I turned a five-figure Google Ads program with zero SQLs into a clean, intent-aligned acquisition engine: recovering from a bot attack, realigning landing pages, restructuring campaigns around buyer intent, fixing HubSpot routing, and re-establishing a trustworthy paid channel that generated $4.8M in pipeline.
- +260% generic CTR increase after moving to intent clusters.
- 650% conversion rate lift after rebuilding landing page alignment.
- 35% reduction in CPL without increasing spend.
- Recovered and quarantined all corrupted Q3 data from a bot attack.
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