Catch a seat upsell moment while it's still fresh

Create an AI-derived attribute 'seat_capacity_used' on the Account object. Compute: (active_seats / plan_seat_limit) as a fraction. Flag when >= 0.8 (approaching limit) or > 1.0 (over limit, billed as overage). Also surface: (a) net seat growth in last 30 days, (b) count of new sign-ups from the account's domain in last 14 days not yet provisioned, (c) any usage cap proximity (API calls, contacts, etc.).

Build a segment 'Seat-expansion candidates' capturing existing paying accounts where (a) seat_capacity_used >= 0.8, OR (b) 3+ new users from the domain signed up in the last 14 days not yet provisioned, OR (c) any usage cap is >= 0.9 utilized. Excludes accounts already in active expansion deal conversations (handled by AE).

Create a workflow firing when seat_capacity_used crosses 0.8, or when a new user_signed_up event comes from an existing customer domain. Step sequence: (1) refresh account context; (2) check whether AE already engaged this account in last 30 days (if so, skip — they're on it); (3) create an AE expansion task with the trigger context (seat-capacity threshold vs. domain-signup spike vs. usage-cap), current ARR, plan tier, expected upsell size; (4) post Slack DM to the AE owner. If the account has no assigned AE, route to RevOps queue.

Compose an expansion pipeline dashboard: count of expansion signals per week (by trigger type: seat-cap / domain-signup / usage-cap), AE response time, expansion-task-to-deal-created conversion, expansion deal cycle time (typically 2-3x faster than new-logo deals), and expansion-deal win rate. ARR uplift from expansion signals YTD vs. target.