A customer's product usage is declining sharply, signaling churn risk.
A sustained drop in usage—fewer logins, lower seat activity, abandoned key workflows—is a leading churn signal that shows up well before a cancellation.
Track usage against each account's healthy baseline and detect meaningful declines early.
An AI agent can monitor health scores, detect at-risk accounts, diagnose the likely cause, and trigger a CS save play before renewal.
Agentic workflows that listen for or act on this signal. Use them as a starting point for what to automate when it fires.
Aggregates account data, analyzes churn risk with AI, alerts teams about high-risk accounts, and provides recommended intervention actions.
Automatically detects significant product usage drops, sends personalized check-in emails to at-risk customers, and schedules follow-up actions.
You want inspiration for the signals your team should track and how to act on them across the buyer and customer journey.
You want inspiration for the signals your Ai agents can detect, score, and respond to automatically.
You want inspiration for the signals that matter at the stage of the customer journey you're focused on.
Go-to-market signals are observable events or behaviors—about an organization or a contact—that indicate intent, opportunity, or risk. Captured and scored well, they tell your team (and your Ai agents) who to engage, when, and with what message.
Each signal has a subject (the organization or the contact it describes) and a journey stage (where it fires—buyer, onboarding, product, retention, or advocacy), so you can route the strongest ones into the right workflow or automation.