Watch the full conversation on YouTube
On the Revenue Creator Podcast, Sowmya Srinivasan, VP of Customer Success at Cohesity, walked me through the retention signals teams miss. She started as a support engineer at Informatica, ran post-sales RevOps at HubSpot, and now owns the number herself.
Her view is that churn rarely hides in complex problems. It shows up in support tickets, consumption data and green accounts nobody questions. The full conversation is below.
What you’ll learn
Which support tickets warn you a customer is leaving
How to find "watermelon" accounts that look green and aren't
How to build a KPI tree from GRR down to the first week after close
How Informatica pushed subscription retention toward 90% with five workstreams
Why customer success is turning into a technical role
Episode Highlights
01:22 - Retention problems hide in plain sight
02:06 - The support ticket that predicts churn
03:28 - From support engineer to RevOps to running CS
05:37 - Customers want proof, not promises
06:54 - The rise of the technical CS team
09:38 - Measured on leading indicators, paid on lagging ones
13:01 - How the account team works at Cohesity
15:08 - The weekly at-risk review
17:25 - Watermelon customers
20:12 - When everyone builds their own dashboard
23:07 - The KPI tree, from GRR down
26:19 - "Why not 90": fixing subscription retention
28:00 - Grading deals at the point of sale
30:59 - What she stopped doing as a new VP
35:54 - Her first three moves at a smaller company
Key Takeaways
1. Read support tickets as churn signals
Support usually gets treated as break-fix. Sowmya reads the patterns. At a previous company, customers kept opening tickets asking for help exporting their data to Excel, and support engineers helpfully did it. If a renewal is three to six months out and a customer asks to export their data, they're leaving. At Cohesity, a customer planning to move off the platform starts that work 12 to 18 months before renewal, so CS has to spot it early.
2. Measure leading indicators, pay on lagging ones
Her team gets paid on gross and net revenue retention. Along the way, they're measured on leading indicators: how much of their book has adopted the product by six months and by a year, consumption and telemetry, and how early they flag a renewal risk to the account team. Her rule is that if CS does its job, the renewal is a non-event.
3. Cut open the watermelons
Her weekly review starts with three risk buckets. A customer using less than 30% of what they bought is red. So is a service risk, like repeated P1 tickets or an escalation with a threat to leave, and any renewal due within six months. Each bucket has a playbook and a named owner. Once a month, the team looks at accounts that look healthy: no escalations, good CSAT, people logging in. Sowmya calls them watermelons. Green outside, but nobody is using the features that make customers stay.
4. Agree on one definition of risk
With Claude and an MCP connection, everyone at Cohesity could pull their own report, so every team defined risk differently. Someone would bring an account to the at-risk review, pull a quick report, and argue from it. As she put it, that's where AI goes from a boon to a bane. She standardized the dashboards and cut the executive view to three to five KPIs. Every review has to end in a decision, whether that's an executive ask, a product commitment or commercial relief.
5. Build the KPI tree from the close forward
Gross and net retention sit at the top, split by segment and by where the customer is in their journey: zero to six months, six to 12, and 12 plus. Below that are simple checks. Was a technical account manager assigned after close? Is there a success plan built on what the customer was promised at the sale? Has a QBR happened by month six or nine? Are they hitting consumption milestones? If not, is there a get-well plan with an owner?
"We look for the most complex problems to solve, and it is actually the simplest things that make a difference to the customer."
6. Churn can start at the point of sale
At Informatica, maintenance contracts renewed at about 95%, but subscriptions renewed in the high 80s. Her team launched a project called "Why not 90" with five workstreams. The first graded every deal at close, from A to F. An F meant the customer was sold something the product couldn't deliver, so CS started in recovery mode on day one. The others covered policies, sales incentives, customer engagement and operating rhythms. Once the model proved right, sales leaders got retention accountability, with holdbacks and clawbacks on commission.
If you're enjoying these, reply and tell me which signal warns you first that a customer is about to churn.
Catch you next week,
Jared
P.S. Sowmya is very active on LinkedIn and happy to connect. Also, always growing our RevGenius community; you can join here to follow along.
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