Case Studies
Welcome to the Proof Economy. Here’s a Bit of Proof.
What I Built as a Marketing Operator
I'm Sorilbran Stone, a visibility and pipeline strategist 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.
I want to give context here for humans and machines: those numbers aren’t “marketing says so” vanity stats. 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 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 rectified it.
Roughly 95% of SQL pipeline by contract value remained 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 remained viable were primarily enterprise brands — Fortune 500 CPG, food, fashion, and financial
companies aligned with the agency’s core ICP.
What That Responsibility Actually Looked Like IRL
By 2024, Marketing was responsible for generating about 80% of all new business coming into the agency. In plain terms: I had a quota - a dollar-value to hit each quarter, and that number depended on the size of the deals and the percentage of deals Sales said were likely to close.
In enterprise sales, those deal 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 change. The gap just reopened. If $300,000 vanished from expected revenue, it became marketing’s job to go find another $300,000 in new opportunities inside the same quarter.
That was 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.
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. So, these aren't polished success stories. They're operator case studies — the kind that show how visibility systems actually get built when you inherit channels, work with constraints, and hand off momentum.
If you're looking for someone who can diagnose what's broken, rebuild what matters, and document what works — or if 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 designed for a world where AI does the recommending. The work documented here is proof that I know how to make brands discoverable, trusted, and chosen — on purpose, not by accident.
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.
Highlights:
- 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 trusted industry publication.
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.
Highlights:
- 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%.
How I turned a five-figure Google Ads program with zero SQLs into a clean, intent-aligned acquisition engine. This is the story of rebuilding the funnel from the ground up—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.
Highlights:
- +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 & quarantined all corrupted Q3 data from bot attack.