Case Studies/B2B Payments Business Turnaround
Aju Joseph John is a product and commercial leader. 20 years across B2B SaaS, fintech, payments, and data platforms.
B2B Payments Business Turnaround
CanadaHelps: Canada's largest online giving and payments platform. $260M+ processing volume. $27M+ P&L.
$230M → $266M
Processing Revenue
25% → 77%
Stickiness
5 → 33
NPS
10K → 16K
MAU
Context
CanadaHelps is Canada's largest online giving and payments platform. $260M+ annual processing volume. $27M+ P&L. Approximately 14,000 clients across three main fundraising products, plus a legacy CRM.
I joined as General Manager of the B2B group, reporting to the CEO. The mandate was to grow the fundraising business. What I found was a business where four teams were each running their own disconnected strategies with no tie back to shared objectives.
Problem
Every function was operating against its own plan, disconnected from business objectives like revenue, retention, stickiness, and CAC payback.
Sales had two mandates (acquire new customers and onboard to paying) with separate commissions on each. Neither was optimized for overall revenue targets, pipeline health, or CAC payback.
Marketing was blasting campaigns without strategy. Communications were not driving top of funnel acquisition or retention.
Client Success was drowning: 14,000 clients, 1,000+ support tickets and escalations, no scalable tooling or tiered approach.
Product was a feature factory. Three products, but the roadmap had no tie back to business outcomes. The legacy CRM (DMS) was losing $115 for every $100 earned.
Decision
In the first 30 days, I listened. Spoke to customers, met with product, finance, and operations teams. Read every support ticket from the past six months. Met every person one on one. Understood the competitive dynamics and financials.
In days 30 through 60, I diagnosed. The core issue was not that any individual function was failing. The issue was that no one had created a single operating model that aligned all four teams to the same objectives across the customer lifecycle.
In days 60 through 90, I acted. The strategy had two pillars: restructure the teams into cross functional pods organized around the customer lifecycle, and deploy AI as an operating lever for efficiency and conversion.
Execution
Pillar 1: Pod Restructuring
Four disconnected teams became three cross functional pods, each aligned to a stage of the customer lifecycle.
The Acquisition Pod, led by Sales, added a marketing person for top of funnel lead generation. Sales focused solely on converting registrations to paying clients within 30 days. A CS team member was assigned to handhold new clients through onboarding.
The Retention and Engagement Pod, led by Marketing, shifted from campaign blasting to customer lifecycle engagement: retention tactics, product tips, engagement practices throughout the lifecycle. Client Success started managing 14,000 clients at scale using new tooling to identify at risk clients, churn signals, and RFM segments. Investments included Pendo for marketing analytics, Amplitude for product analytics, and a CS platform for scaled client management.
The Product Pod sunset the legacy CRM, eliminating all six DMS salespeople and four of five CS members (one kept for maintenance). The product roadmap was rebuilt, tied to business objectives instead of feature requests. This freed headcount, budget, and bandwidth for what became CanadaHelps Ensemble.
Pillar 2: AI as an Operating Lever
AI was not an experiment or an innovation initiative. It was the second pillar of the operating strategy, deployed where it would move business metrics directly.
The AI Sales Agent was a human in the loop system that researched prospects, generated evidence backed qualification scores, and recommended next best actions. The agent did the repeatable research; the rep made the judgment call. Discovery to Demo stage conversion went from 5% to 45%.
The AI Product Management System automated the PM drafting workflow. A single command generated a complete draft: problem statement, requirements, user stories with acceptance criteria, and a full PRD. The PM still made every judgment call. The Chief Architect still reviewed for technical feasibility. The difference was the PM spent 80% of their time on decisions instead of 80% on drafting. Development cycles went from many weeks to under two weeks.
Course Corrections
The DMS sunset freed headcount, budget, and bandwidth. That space became CanadaHelps Ensemble, a lightweight CRM for nonprofits who could not afford Salesforce or Blackbaud. A small team built the MVP in under a month. Every validation signal came back negative: $0 willingness to pay in a webinar survey, six beta invitees who were all no shows. I read it as a false negative on stated preference and assigned 25% of the sales team to sell it. Ten deals closed in the first month. Real demand, confirmed by revenue.
Ensemble grew to 200+ customers and $432K ARR. But two significant missteps happened along the way. First, I extended the free trial from two weeks to four weeks, believing more time would push PLG conversion from 25% to 35%. Sales pushed back; they argued buying is impulsive. I overruled them. PLG conversion dropped from 25% to 10%. Revenue fell 40% below target. Customers were achieving their goals during the trial, which removed all urgency to buy. The deceptive part: headline pipeline metrics still looked healthy. The conversion engine was broken underneath numbers that said everything was fine.
I reversed the trial in one quarter. Flipped it back to two weeks, cleaned 20%+ of stale pipeline to closed lost, replenished with better qualified leads, and used targeted discounts to recover deals already on the extended trial. The quarter hit 140% of target. Win rate recovered from 7.75% to 20%. But the discounts eroded ARPU roughly 7%, crashing LTV:CAC from 4:1 to 1.3:1. The fix required four coordinated moves: add a Reporting feature to justify a price floor of $75 per month, raise renewal prices 10%, run engagement and retention plays, and invest in PLG volume to bring down CAC. LTV:CAC restored toward 3:1. The pattern: each point fix created the next problem until I stopped treating connected metrics as independent variables and redesigned the system.
Outcome
Over approximately two years at CanadaHelps ($260M+ processing volume, $27M+ P&L), the coherent operating strategy produced measurable results across every dimension.
Processing revenue: $230M to $266M (8%+ CAGR)
Retention: 67% to 83%
Stickiness: 25% to 77%
NPS: 5 to 33
MAU: 10K to 16K
AI sales conversion: 5% to 45%
Dev cycle reduction: 65%
eNPS: 44, with 5 promotions in 3 years
Learning
When teams operate in silos with disconnected strategies, the leader's first job is not to optimize any single function. It is to create one coherent operating model that aligns everyone to the same objectives across the customer lifecycle. Structure enables strategy. Strategy without structure is just a slide deck.
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