AI Automation Engineering
Customer Experience
Marketing Ops
RevOps
SalesOps
Outbound GTM Pods
Healthcare
Logistics
Financial Services
Enterprise Software
Manufacturing
AI & Technology
Private Equity
Professional Services
InsurTech
PropTech
Supply Chain & LogisticsDataTruck
How Phi took DataTruck from founder-led sales to a $12M Series A.
LogisticsThe outcome
The challenge
A product with no engine.
DataTruck had a sharp TMS product built for SMB carriers. Fleets liked it. Retention was strong. Product-market fit wasn't the problem, growth was. Like most early-stage B2B companies, DataTruck was running on founder-led sales: closing deals through personal networks, warm intros and sheer persistence. It worked well enough to prove the product. It doesn't scale. They weren't missing leads. They were missing the machine.
01
No sales team
Every deal depended on a founder being in the room.
02
CAC at $1,103
No repeatable system for turning interest into revenue.
03
No pipeline visibility
No ICP framework meant growth relied entirely on founder-led hustle.
What Phi built
Building the engine (months 1–9).
Phi didn't drop in a full team. We placed one person, a founding AE, embedded inside DataTruck and running the entire outbound motion end-to-end. No advisory decks, no strategy-only retainers. Nine months in, DataTruck crossed $1M ARR, CAC had dropped from $1,103 to $561, and the Phi-led outbound engine alone had generated $207,552 in ARR. For every dollar DataTruck invested in Phi, they got $9 back.
01
ICP segmentation
TAM to SAM to SOM mapped to high-intent SMB carriers. A scoped, signal-based targeting model, not a broad spray.
02
Pain-driven messaging
No feature pitches. Every email, call script and follow-up built around operational problems carriers deal with daily: missed loads, manual dispatch, billing chaos.
03
Cold outreach infrastructure
8,000+ targeted calls via Aircall. 11,000+ personalized emails via Instantly. Multi-touch sequences tested, optimized and scaled.
04
Sales stack & CRM
HubSpot configured from scratch. A/B tested workflows. Pipeline dashboards with real-time visibility.
Execution
Scaling what works (months 10–21).
With the outbound engine running, the question shifted from "can we sell" to "how fast can we compound." Phi stayed embedded and the scope grew. DataTruck went from $1M to $2.5M ARR in 12 months; outbound alone generated $629,400 in new ARR. CAC dropped again from $561 to $530, and month-over-month revenue additions more than doubled from $1,950 to $4,370.
01
CRM overhaul
Rebuilt DataTruck's CRM architecture to handle higher volume without losing signal: better lead scoring, cleaner handoffs, faster follow-up.
02
PLG build & launch
Designed and shipped a product-led growth motion alongside outbound. Self-serve signups feeding the same pipeline infrastructure. Two channels, one unified system.
03
Team growth
Scaled from one founding AE to a team of three (2 SDRs, 1 AE). Every hire stepped into a system already producing: playbooks, sequences and pipeline visibility all proven first.
Results
The full picture.
When DataTruck went to raise, they didn't walk in with projections and promises. They walked in with a working revenue engine and the numbers to prove it. A $700K pre-Series A came first, then a $12M Series A. Investors weren't betting on a product. They were betting on a company that already knew how to sell it.
01
$2.5M ARR
Grown from ~$200K in 21 months
02
$530 CAC
Down from $1,103, a 97% reduction
03
$629,400
Outbound ARR (Phi-led) in the scaling phase
04
$12.7M raised
Pre-Series A plus a $12M Series A
“Phi didn't just advise. They sold. Their outbound system scaled faster and cheaper than anything we tried in-house.”
More proof
The same machine, other markets.
The same machine, pointed at your number.
How Phi helped DataTruck build an outbound GTM engine: $2.5M ARR in under 2 years, 97% CAC reduction, $9 back for every $1 spent, and a $12M Series A.