Churning Deals Warning – Early Alert System

Context & Objective

The current Churn Report focuses on deals that are already churned — either through a formal cancellation or after 12 consecutive months of inactivity. However, by the time a deal is flagged here, it's often too late to take action.

To help Account Managers intervene earlier, we're introducing a new “Churning Deals Warning” section. This section will identify at-risk accounts based on behavioural patterns, enabling proactive outreach and retention efforts.

Proposed Criteria for “At-Risk” Accounts

We aim to flag accounts showing early signs of disengagement or decline. The criteria below are initial ideas and open for iteration.

1. Sharp Drop in Monthly Bookings

Flag deals where monthly bookings have dropped by 70% or more compared to the average of the previous 3 to 6 months.
Only apply this check to deals that had a minimum threshold of activity in the past (e.g., at least 10 bookings/month on average) to avoid noise from small or sporadic users.

2. Sustained Inactivity

Flag deals that have had no activity (0 bookings) in the last 3 to 6 months.
This helps catch accounts before they hit the 12-month churn threshold.

3. Step Change in Listings

Flag deals that have seen a significant drop in the number of active listings (e.g., 50%+ drop compared to 3-month average).
A drop in listings often precedes a drop in bookings.

4. Other possible options

Track accounts that haven’t had any contact with their Account Manager in over 6 months.
Track accounts that have bad CSAT score on their bookings (less than 2-3).

Purpose of These Flags

The main goal is not to automate action, but to guide Account Managers' attention to potentially declining accounts. With earlier signals, they can:

Reach out before accounts fully disengage.
Investigate potential issues (e.g., pricing, onboarding, product fit).
Offer support, incentives, or solutions.

Implementation Ideas

Integrate this section into the existing Churn Report, under a new tab or visual.
Allow filters by:
- Account Manager
- Warning reason
- Region / Country
- Deal Size (segmentation)
- Business Scope
Show “reason for flag” per deal (e.g., “Bookings dropped 75% in last month”).

Next Steps

Finalize flagging criteria with input from AMs and data team.
Build the logic and integrate into dbt / Power BI.
Gather feedback from pilot usage.

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