CRM

Detect negative inbound replies and flag HubSpot churn risk

Classifies the sentiment of each inbound Front reply, and when a customer message reads frustrated or cancellation-leaning.

CategoryCRM
Enginesim
Difficultyintermediate
Triggerwebhook
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerInbound Front reply receivedFront
  • ActionClassify sentiment and intent with OpenAIOpenAI
  • LogicNegative or cancellation-leaning?
  • ActionFind HubSpot contact by emailHubSpotHubSpot
  • ActionSet churn-risk flag and timeline noteHubSpotHubSpot
  • OutputPage account owner in SlackSlack

What it does

Reads incoming customer replies in Front, scores their sentiment with an LLM, and routes negative or cancellation-leaning messages into a HubSpot churn-risk flag plus an immediate owner alert. It catches dissatisfaction the moment it lands in the inbox.

When to use it

Use it when support replies and churn signals are buried in a high-volume Front inbox and you want at-risk accounts escalated automatically rather than discovered at renewal time.

How it works

  1. 1A Front webhook fires on each inbound reply.
  2. 2An OpenAI classification step labels the message sentiment and intent (neutral, frustrated, or cancellation-leaning) with a short reason.
  3. 3A branch passes only frustrated or cancellation-leaning messages forward.
  4. 4The flow looks up the HubSpot contact by the sender's email.
  5. 5HubSpot sets a churn-risk property and writes a timeline note with the classifier's reason.
  6. 6A Slack direct message to the account owner includes the quote, the risk reason, and a link to reply in Front.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect FrontShared inbox, conversations.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect HubSpotCRM, deals, marketing, support.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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