Spot at-risk customers before they churn with AI

Combines your CRM, usage, and support data to flag customers likely to churn and alert your team automatically.

How the work actually flows

It branches. Exactly one path is taken; runs once per each active customer.

Pattern: Exclusive Choice (4) · Multiple Instances with a priori Design-Time Knowledge (13)

flowchart TD trig(("team runs churn check")):::human s0["pull CRM deal data"]:::task s1["gather usage and support data"]:::task s2[["AI scores churn risk"]]:::mi s3["compare against risk thresholds"]:::task trig --> s0 s0 --> s1 s1 -->|"one per each active customer"| s2 s2 --> s3 gx{"× customer at risk"}:::gate s3 --> gx p00["email team with alert"]:::task gx -->|"at risk"| p00 p10["no alert sent"]:::task gx -->|"not at risk"| p10 p00 --> out p10 --> out out[/"at-risk customers flagged automatically"/]:::out pay{{"catches churn before cancellation"}}:::pay out --> pay classDef task fill:#e7f6fe,stroke:#34b8f0,color:#2c2a29 classDef svc fill:#f6f8fa,stroke:#7c8795,color:#2c2a29 classDef mi fill:#e7f6fe,stroke:#0079a8,color:#2c2a29,stroke-width:2px classDef human fill:#fff,stroke:#0079a8,color:#0079a8 classDef store fill:#f6f8fa,stroke:#0079a8,color:#2c2a29 classDef trig fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigtime fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigdata fill:#8ad4f5,stroke:#0079a8,color:#06314c,font-weight:bold classDef gate fill:#fff,stroke:#e8a23d,color:#6b4708,font-weight:bold classDef out fill:#1f9d6b,stroke:#167a53,color:#fff,font-weight:bold classDef pay fill:#06314c,stroke:#021f33,color:#fff
A stepRuns once per itemA personOne path onlyResultPayoff
Build size
Advanced

A larger build with multiple systems, AI reasoning, and custom rules.

Business functions
AI Agents & Autonomous SystemsCRM & Sales PipelineEmail AutomationSpreadsheet & Database OpsCustomer Support & Ticketing
Connects
HubSpotGoogle SheetsOpenAI

The problem it solves

By the time a customer cancels, the warning signs, like slipping usage or frustrated support tickets, were probably there for weeks. Nobody has time to manually cross-reference your CRM, spreadsheets, and support tickets for every account.

Who it fits

A customer success or account management team responsible for retention.

How it works

  1. You run the process against your active deals in HubSpot
  2. It pulls related support ticket sentiment and feature usage from Google Sheets
  3. AI scores each customer's sentiment and compares deal age, sentiment, and usage against risk thresholds
  4. If a customer looks at risk, it emails the responsible team member with the details and next-step recommendations
What you get

Customers flagged before they consider leaving

Your team gets an early alert with clear next steps whenever a customer's usage and sentiment signal they might be at risk of leaving.

What you get

An email alert flagging at-risk customers with the data and recommended next steps behind the score.

What you need

A HubSpot account, a Google Sheets tracking usage data, and an OpenAI API key.

We can build this. But should you?

The hard question is not how to build it. It is whether this is the right thing to build first.

That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.

Let's Talk Strategy

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