AtoB had 77 customers and a product that worked. What they didn’t have was a system to turn that early traction into a market position. Customer acquisition was expensive, the sales motion couldn’t move without the founders in the room, and the post-sale experience depended on heroics rather than process.
Phi came in as an embedded operating layer. Not a consulting firm with a deck. The systems didn’t exist yet, so Phi built and ran them.
What AtoB Was Dealing With Before Phi
AtoB operates in logistics payments: a vertical with long sales cycles, high churn risk, and buyers who have been burned before. The unit economics of their early customer acquisition model were not going to survive a Series B raise.
The problem wasn’t the product. It was infrastructure. Scaling without fixing that first would have compounded the cost at every layer.
- No repeatable GTM system. Every deal required founder involvement to move through the pipeline.
- No CRM architecture. Leadership had no real visibility into pipeline health or stage progression.
- No CS motion built for volume. Onboarding was inconsistent and reactive, not systematic.
More reps into a broken sales system, more customers churning through a broken onboarding experience. That was the trajectory without intervention.
What Phi Built: Two Pods, One Operating Layer
Phi deployed two pods inside AtoB’s org: a GTM sales pod and a customer experience pod. Neither handed off a playbook. Both ran the systems.
GTM Sales Pod
The sales pod built a repeatable outbound motion in the trucking vertical. That meant defining the ICP with real precision, then building the data and sequencing infrastructure on top of it.
Phi embedded sales professionals who understood logistics payments well enough to run conversations without hand-holding. The pod plugged into AtoB’s existing stack and added what was missing: enrichment, sequencing, CRM workflows, and attribution. For more on how that type of pod works, see how Phi builds and runs sales pods.
Customer Experience Pod
The CX pod tackled the post-sale problem. Onboarding was rebuilt from the ground up: standardized, documented, and tied to retention metrics instead of gut feel.
The pod put health scoring and escalation workflows in place so the CS team could get ahead of churn instead of reacting to it. The result wasn’t just better CSAT scores. It was a retention engine that could absorb a large volume of fleet accounts without breaking. More detail on that system lives in the AtoB CX case study.
RevOps Layer
The RevOps layer connected both pods. Pipeline visibility, attribution, and reporting all ran through a CRM architecture that gave AtoB’s leadership a single view of the revenue operation.
That’s what makes a RevOps system worth building: it stops sales and CS from operating in separate silos with separate data.
The Results: What the System Produced
AtoB went from 77 customers to 7% of the U.S. trucking market. The Series B closed at an $800M valuation. CSAT improved 40% across thousands of fleet accounts.
Those numbers compound on each other. Lower churn means each new customer is worth more. A functional post-sale system means the sales team can close more aggressively without worrying about what happens after the contract is signed.
| Metric | Before Phi | After Phi |
|---|---|---|
| Customers | 77 | 7% U.S. trucking market share |
| CSAT | Baseline | +40% improvement |
| Series B valuation | Pre-raise | $800M |
| Sales motion | Founder-dependent | System-led, repeatable |
A CRM that actually reflects reality means leadership can make resourcing decisions based on data instead of instinct. That’s a different company than the one that started.
Why This Worked When Other Approaches Had Not
AtoB didn’t need more advice about what to do. They needed someone to do it with them. That’s the distinction between a consulting engagement and an embedded operating layer.
Phi’s pods weren’t reporting to a project manager at arm’s length. They were inside the org, accountable to the same metrics AtoB’s leadership was accountable to.
- When onboarding wasn’t working, the CX pod rebuilt it. No approval chain, no slide deck.
- When the ICP definition was too broad, the sales pod tightened it and restarted the sequencing infrastructure on top of the sharper criteria.
- When pipeline visibility was missing, the RevOps layer built the CRM architecture to surface it.
That’s also why the results held. Systems built by people who operate them daily get iterated. Playbooks handed off by consultants get abandoned when reality diverges from the deck.
If you’re at the stage where the sales motion is founder-dependent and the post-sale experience is held together by individual heroics, the AtoB story is a useful reference point. You can see how Phi took Datatruck from $0 to $2.5M ARR for an earlier-stage version of the same problem, or how TruckX scaled from $2M to $16M ARR in 18 months for what mid-stage expansion looks like.
- The companies that scaled weren’t the ones with the best pitch decks.
- They were the ones that built the system first.
