Enterprise GTM · Case Study

From PLG
to Enterprise Revenue In 90 Days.

How Dovetail and ScaleAgentic partnered to create $6.5M in enterprise pipeline and save 1,000+ hours – by replacing scattered GTM tools with a single coordinated intelligence system.

Results at a glance

$6.5M

Total Pipeline Created

Land + expand across all motions

$2.5M

New Land Revenue

European market expansion

1,000+

Hours Saved

Eliminating manual research cycles

90 Days

First 90 Days

Results in a single quarter

$6.5M Revenue Touched ◆ $2.5M European Expansion ◆ 1,000+ Hours Saved ◆ PLG → Enterprise ◆ First 90 Days ◆ Dovetail × ScaleAgentic ◆ $6.5M Revenue Touched ◆ $2.5M European Expansion ◆ 1,000+ Hours Saved ◆ PLG → Enterprise ◆ First 90 Days ◆ Dovetail × ScaleAgentic ◆

The Challenge

A mandate to transform, not optimize.

Dovetail had a board-level directive: move beyond PLG and build a true enterprise revenue engine. Paid ads and SEO were running. They just weren't compounding.

Enterprise buyers had moved to AI and peer communities. Traditional channels were underperforming. The team lacked a single intelligence layer connecting signal to revenue.

Market signals scattered, not actionable
Account prep was manual and episodic
Events were brand-led, not revenue-backed
Vertical expansion lacked real-time intelligence

"There was a mandate to transform Dovetail beyond PLG into an enterprise sales motion. Paid ads and SEO weren't converting, and we needed to understand how enterprise leaders were actually discovering products."

— Jeremie Gluckman

The System

Not a tool. A GTM intelligence engine.

ScaleAgentic deployed a multi-agent system that converted Reddit conversations into structured revenue intelligence, continuously and automatically.

Industry + intent signals from live community data
Precision ICP lists for vertical expansion
VIP event targeting for land-and-expand accounts
Revenue-first event strategy from the ground up
GEO & content roadmap grounded in real buyer language

Each output fed the next. The system compounded with every cycle.

"It wasn't a point solution; it was a connected system. Conversations became industry signals, intent signals, and lead signals that fed directly into our vertical expansion and land-and-expand motions."

— Jeremie Gluckman

The Mechanism

How signals became revenue.

The breakthrough wasn't a single channel. It was how information flowed. Reddit became the initial signal layer – structured into actionable intelligence that cascaded across every motion.

Industry, intent & adjacent signals extracted from community data
Signals → precision ICP generation for vertical expansion
ICPs → VIP executive dinner targeting & ABM swarm motions
Motions → enterprise land-and-expand revenue
Each cycle taught the next – the engine learned continuously

This is the difference between optimizing tasks and coordinating outcomes.

"ScaleAgentic helped us move from traditional point solution thinking to actual systems thinking. Our vision isn't to build isolated tools – it's to create a system where each component feeds intelligence into the others."

— Jeremie Gluckman

The Results

$6.5M touched. In the first 90 days.

$6.5M total enterprise pipeline touched across all connected motions
$2.5M in new land revenue pushed into European markets
1,000+ hours saved by eliminating manual research cycles
PLG → enterprise transformation accelerated
Fully documented, repeatable GTM system, fully outsourceable

This wasn't an incremental performance lift. It was structural revenue acceleration.

"ScaleAgentic's GTM system drove $2.5M in new land revenue in Europe and touched $6.5M in land and expand revenue. It accelerated our transformation from PLG to enterprise."

— Jeremie Gluckman

From PLG to Enterprise Revenue In 90 Days.

A mandate to transform, not optimize.

Not a tool. A GTM intelligence engine.

How signals became revenue.

$6.5M touched. In the first 90 days.

Your pipeline is eithercompounding or decaying.

From PLG
to Enterprise Revenue In 90 Days.

Your pipeline is either
compounding or decaying.