sh-notion/notion_data_team_no_files/Churning Deals Warning – Early Alert System 1d00446ff9c98056b4f9fb5177e4e64d.md

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2025-07-11 16:15:17 +02:00
# 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.
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## 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 havent 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).
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### 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.
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### 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”).
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## 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.