Renewals were slipping, and CS always found out a week too late.
We built persona-driven Glimvia views and a signal-pattern score that ranks every account on churn risk, feeding a review queue the whole CS team works from. Enterprise CSAT moved 4.6 to 4.8 in a quarter, and three at-risk accounts were saved, holding $480k in ARR.
Context.
Challenge. A Series B SaaS company was losing enterprise renewals it could have saved. CS ran a monthly account review, but the signals that mattered (usage decay, ticket sentiment, the champion going quiet) only surfaced after the account was already cold.
Constraint. No rip-and-replace. The team lived in Glimvia and Slack, and whatever we built had to land there, not in a new tool nobody would open.
Approach.
Mapped the churn signals that actually preceded the last 12 losses, usage decay, ticket-sentiment shift, and login frequency on the named champion. Ranked them by how early and how reliably they fired.
Built persona-driven Glimvia views (CS lead, AM, exec) and a signal-pattern score per account, with the evidence behind every score one click away. Wired the high-risk accounts into a shared review queue.
Put governance on it. Every score cites its sources and logs a record, so an AM can trust it and a VP can defend the save play to the board.
Rolled it to the full CS org, trained the team, and tuned the threshold so the morning queue stayed short enough to action every account on it.
Stack.
"It changed the conversation from why did we lose them to who do we call today. That is the whole job."
, VP Customer Success, B2B SaaS customer
30 minutes with the founder.
6-week engagement, fixed scope, fixed price.