Case Studies

Four rebuilds. Four different root causes.

Each engagement starts with what the data actually showed, not what the team assumed. Jump to a case:

Case study 1 · Market entry

A new segment accepted 18% of meetings. The pitch was the problem.

The sales team executed exactly what it was asked to. The assumption underneath the playbook was wrong, so the fix was a new reason to care, not more effort on the old one.

18% to 38%

Meeting acceptance after the rebuilt talk track

10 of 20

Pilot accounts closed

~40%

Normal acceptance rate in core segments

Problem

A new customer segment came in at 18% meeting acceptance against a normal rate closer to 40%. A sales motion that worked elsewhere had been applied to a new part of the market.

Stakes

The obvious response was to push harder on the same pitch. That would have spent the segment's accounts on a message that was not landing.

Diagnosis

The team was not the issue. The assumption about why customers would buy was. I went back to the customers who had actually said yes and found three things:

  • Trust and compliance mattered more than expected.
  • Retention and repeat business mattered more than expected.
  • The benefit we assumed would open the door mattered far less.

Actions

  • Stopped optimizing the original pitch.
  • Rebuilt the talk track around what customers valued.
  • Tested the new motion on 20 accounts before any wider rollout.

Results

  • Meeting acceptance moved from 18% to 38%.
  • 10 of the 20 test accounts closed.
  • The approach was rolled out more broadly only after the test proved out.

Takeaway

Before asking a sales team to push harder, check whether customers have been given the right reason to care.

Meeting acceptance rate

Normal rate~40%
New segment, original pitch18%
New segment, rebuilt talk track38%

Scale: 0 to 100% of meetings offered.

Case study 2 · Compensation design

Payment monetization missed plan because ARR hit target.

The CFO asked why payment monetization was below plan. The two numbers were connected: reps were paid on ARR alone, so payments were never the priority.

41% to 76%

Payment setup within 30 days of close, over two quarters

Day 30

Activation milestone owned by the AE

0

New quota lines added

Problem

Sales was compensated on ARR. Payment volume lived in a different dashboard, owned by a different leader, reviewed in a different meeting. Payment setup was deferred at signing and never revisited, because no structured motion existed to revisit it.

Stakes

No single owner carried both the close number and the activation number. That made a handoff gap look like an execution problem, and ARR on target hid the shortfall in payments.

Diagnosis

The team operated on two beliefs. First, that ARR growth would pull payment attach along with it. Nobody had formally tested whether it ever had. Second, that the sequence was to close the contract and monetize the payment flow later.

The obvious fix was adding payment volume to the comp plan, and I nearly did. AEs were already at capacity on a complex multi-product sale. A second monetization variable on top of an unsimplified primary one would have created noise, not focus.

Actions

  • Created a payment activation milestone at day 30 post-close, owned by the AE.
  • Tied it to the trailing commission release on the initial deal.
  • Added no new quota line. The change was a release condition on money already earned.

Results

  • Payment setup in the first 30 days rose from 41% to 76% over two quarters.
  • Payment volume per new logo increased.

Takeaway

Compensation sequencing is product design. Whatever is attached second gets deferred until the pressure of the first objective lifts.

Payment setup within 30 days of close

Before the milestone41%
Two quarters after76%

How the incentive works

  1. Day 0

    Contract closesARR commission paid as before.

  2. Day 30

    Payment activation milestoneOwned by the AE who closed the deal.

  3. After

    Trailing commission releasedReleased once payments are live.

Scale: 0 to 100% of new accounts.

Case study 3 · Fresha · Account management rebuild

From churn prevention to a repeatable expansion engine.

Account management existed only to prevent churn. I rebuilt it into a segmented, proactive function that sells expanded capabilities to existing partners.

100.3%

Revenue growth from existing partners

117%

NRR against a 100% target

5 to 35

Reps, plus 2 team leads

Problem

Account management had no expansion motion, no segmentation, and no way to see churn risk before it happened. The team was 5 reps with no leadership layer and no formal hiring or training infrastructure.

Stakes

Existing partners were an underused revenue base. Without a repeatable expansion engine, growth depended entirely on new logos, leaving existing partner revenue and retention exposed.

Diagnosis

People. Five generalist reps, no team leads, and no structured hiring profile or training program to scale the function.

Process. No health scoring or portfolio segmentation, so intervention was reactive. No consultative cross-sell or upsell motion, and no multi-product training to support one. Marketplace merchant profiles were unoptimized, which limited visibility and revenue potential.

Actions

  • Built health scoring and portfolio segmentation across 12 merchant categories to flag risk before churn signals hit.
  • Scaled the team from 5 to 35 reps plus 2 team leads, rebuilding hiring, training, and performance management from the ground up.
  • Launched a multi-product training program to drive expansion selling.
  • Shifted the team motion from churn prevention to consultative cross-sell and upsell.
  • Directed a systematic optimization of merchant marketplace profiles across the managed book.

Results

  • 100.3% revenue growth from existing partners, reaching 98% of revenue target.
  • 36% of active partners paying for expanded capabilities, with monetized partners up 132% year over year.
  • NRR at 117% against a 100% target.
  • High revenue product adoption up 50% year over year across the AM team.
  • Improved marketplace profiles for 75% of all managed merchants.

What changed

Net revenue retention

Target100%
Achieved117%

Account management reps

Before5
After, plus 2 team leads35

NRR scale: 0 to 120%. Rep scale: 0 to 40.

Case study 4 · MyStudio · Org restructure

Fixing the commercial structure ahead of a Series A.

Growth had stalled, churn was rising, and two teams were working the same accounts for the same motion. I separated the roles, rebuilt the ICP, and fed customer signal back into product.

82% to 98%

Net revenue retention

24+ to 18

Months to payback on new cohorts

+7 pts

Rule of 40

Problem

Growth stalled and churn was rising. ICP drift filled the pipeline with bad-fit leads. Payback had stretched past 24 months, CAC sat at $1,000, NRR was declining, and the Rule of 40 was slipping.

Stakes

A Series A raise was on the horizon. Without improvement on these metrics, valuation and terms would suffer.

Diagnosis

People. The structure did not fit the problem. CS owned onboarding, churn prevention, support, and upsell all at once. Sales owned new business and existing account upsell. Two teams contacted the same accounts for the same motion, which confused partners and diluted accountability. Support was understaffed and overwhelmed, and CSAT was falling.

Process. I audited how CX handled tickets, how CS and product communicated, and how accounts moved from sales to CS.

Actions

  • Realigned sales to focus solely on new business, with lead scoring rebuilt around the true ICP.
  • Rebranded CS as AM, scoped to churn prevention and upsell only, removing overlap with sales and support.
  • Built a dedicated onboarding function and standardized the new user ramp.
  • Expanded CX in the Philippines to protect budget while scaling coverage.
  • Deployed AI tooling in the help desk to triage and quantify issues.
  • Built a feedback loop from AM and CX into product for data-driven roadmap decisions.

Results

  • New business conversion up 8%, and average new ACV up $2,000.
  • Churn down 3%, and NRR up from 82% to 98%.
  • CSAT up from 2 to 4.
  • Payback cut from 24+ months to 18 for new cohorts, and CAC down from $1,000 to $800. Drivers were higher ACV, lower acquisition cost, reduced churn, and add-on sales from the AM motion.
  • $100K net in add-on sales of the new AI product, driven by the AM team.
  • Rule of 40 improved 7 points.

Before and after

Net revenue retention

Before82%
After98%

Payback, new cohorts

Before24+ mo
After18 mo

Customer acquisition cost

Before$1,000
After$800

CSAT

Before2
After4

Each metric is scaled to its own larger value.