Use case
From the field, AI native workflow redesign of churn and renewal prediction process within Customer Success Sales function.
Get the playbookA senior Convolving delivery team partnered with the customer success function for one sprint. Operators from our expert network – with forty combined years inside enterprise SaaS post-sale teams – reviewed the redesign at each checkpoint. Forward-deployed engineers built inside the team's CRM, product analytics, and email stack. One flat fee, artifact out, no retainer creep.
Today renewal risk surfaces in the ninety-day window when the CSM opens the renewal queue. Most early signals sit unread in product analytics and email threads.
Churn drivers fragment across CRM activity, product usage, support tickets, and the buyer's email tone. The CSM cannot read all four for every account, so health scores rely on a manual call once a quarter. Renewal risk arrives late, leaving the conversation to revolve around discounts rather than value.
Click any node to see the activities and tools behind it. Open the canvas in fullscreen for the horizontal view.
By the time the CSM sees the account in the queue, the buyer has been quiet for a quarter. The conversation defaults to discount.
CRM, product analytics, support, and email each see one slice. No CSM stitches all four for every account, every week.
Tier-1 accounts get a weekly read; the long tail gets a quarterly guess. Quiet churners hide in the tail until the renewal date.
Same five steps. Click any node to see what the redesign does in that step.
The redesign above ships as a step-by-step playbook. Health-score model spec, identity-resolution map, playbook library, CSM brief prompts, and the rollout cadence we use on engagements.