Case Study
SaaS
How Stackflow Doubled Expansion Revenue by Finding Upsell Signals in Its CRM
Stackflow with 600 B2B accounts and a self-serve expansion model was leaving significant revenue on the table. The signals that predicted which accounts were ready to expand had been in the CRM for two years. Nobody had looked at them.
2x
Expansion revenue
+31%
ACV increase
4x
CS expansion pipeline
We're a tech company helping B2B teams extract CRM data, find revenue leaks, and unlock growth. Our approach is simple, combine AI with strategy so you can focus on closing what matters most.
The situation
Stackflow's go-to-market was product-led: self-serve signup, a freemium tier, and an upgrade path from free to paid and from paid to enterprise. The sales team handled inbound upgrade requests and the CS team managed enterprise accounts. Expansion revenue existed but was almost entirely reactive: customers asked to upgrade, and the team processed the request.
The head of CS suspected there was proactive expansion revenue available in the account base. The data to identify it was theoretically in HubSpot, but the CS team had no systematic way to look at it across 600 accounts. Individual CSMs had intuitions about which accounts might be ready to expand. Those intuitions were right often enough to be credible but not systematic enough to build a repeatable process.
What we found
We pulled product usage data alongside CRM records for all 600 accounts and ran a cohort analysis comparing accounts that had expanded versus those that had stayed flat over the preceding 18 months.
Four signals consistently preceded expansion in the historical data. Seat utilization above 85% was the strongest predictor: accounts at or above this threshold expanded within 90 days at a 68% rate when proactively engaged. Monthly active user count growing more than 20% quarter-over-quarter was the second signal. The third was cross-functional usage: accounts where more than three departments had active users were significantly more likely to expand to enterprise tiers. The fourth was integration adoption: accounts that had connected three or more integrations had an expansion rate 3.4x higher than accounts with zero or one integrations.
When we mapped those four signals across the current 600-account base, 87 accounts matched at least two of the four criteria. Of those 87, only 12 had active expansion conversations in the CRM. The other 75 were being managed on a standard check-in cadence with no expansion motion.
What changed
The four signals were implemented as a real-time expansion scoring model in HubSpot. CSMs saw a prioritized expansion list every Monday, updated based on the previous week's product usage data. Accounts above the threshold received a specific expansion playbook rather than a standard check-in.
The expansion playbook was built from the patterns in the historical data: which value framing resonated in accounts with each signal type, what the expansion conversation should lead with, and what the escalation path looked like if the CSM wasn't getting traction. The playbook wasn't generic. It was built from what had actually worked in previous expansions.
In the first 8 months, expansion revenue doubled. Average contract value increased 31% as accounts moved from standard to enterprise tiers. CS-driven expansion pipeline, which had previously been informal and untracked, grew 4x and became a formal revenue line in quarterly planning.