Case study / AI SaaS

130 paid users in 90 days, from no commercial infrastructure at all

ScrubGPT by The CoBuilders, an AI data-cleaning SaaS. Full GTM System Build, pre-launch.

AI SaaSGTM from scratchLaunch sprint

~350

Users signed up

130

Converted to paid

37%

Free to paid conversion

The situation

The CoBuilders had built ScrubGPT, an AI data-cleaning product, and nothing else. No CRM, no ICP, no sequences, no messaging, no commercial motion of any kind. The engagement started before the app was even released. This was go-to-market from a genuinely blank page.

The problem

Launching with no audience, no pipeline and no infrastructure means the first 90 days decide everything. The goal was defined sharply from the start: signed-up users, then paid conversions. Not vanity metrics, but usage and revenue.

What was built

ICP definition. Who has data messy enough, and painful enough, to pay for automated cleaning.
HubSpot CRM. Pipeline architecture, workflows and reporting configured from zero.
Apollo workflows. Prospecting SOPs for continuous lead sourcing.
Cold email sequences. Written, tested and iterated against reply data.
LinkedIn strategy. A parallel outreach layer for the segments that do not answer email.
Community research. Mapping where the target users already gathered and how they described the problem.
Messaging framework. A documented system, so every future campaign starts from proven language instead of a blank page.

Results / 90-day launch sprint

What it produced

~350

Users signed up

During the 90-day sprint

130

Converted to the paid plan

37%

Free to paid conversion

100%

Of sprint goals met

Met and exceeded

Why it worked

Full autonomy and fast decisions. The founder treated the engagement like a founding-team role rather than a vendor contract, so feedback loops were measured in hours rather than weeks. When outbound learning can reshape messaging the same day, 90 days is enough to build what normally takes a year.