MARKET RESEARCH

Real-Time Review-to-Backlog Router via Webhook

Receives individual reviews pushed from a scraper webhook, scores each for product relevance.

CategoryMarket Research
Enginesim
Difficultyintermediate
Triggerwebhook
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook receives one reviewHTTP webhook
  • ActionScore relevance + assign themeOpenAI
  • LogicDrop low-relevance reviews
  • LogicRoute to ClickUp list by theme
  • ActionCreate ClickUp taskClickUpClickUp
  • OutputReturn task ID to callerHTTP webhook

What it does

This workflow reacts the moment a new review lands rather than waiting for a daily batch. An incoming review is scored for whether it contains usable product feedback, and qualifying ones are turned into ClickUp tasks routed to the right list, so the backlog updates continuously.

When to use it

Use it when you already have a review-collection pipeline that can post webhooks and you want near-instant triage. It fits teams who treat reviews as a live feedback stream and want feature signals in their planning tool within minutes.

How it works

  1. 1An HTTP webhook receives a single review payload from your scraper or aggregator.
  2. 2OpenAI scores the review for product relevance and assigns a feature theme plus priority.
  3. 3A logic branch drops reviews below the relevance threshold (praise, spam, pure ratings).
  4. 4For qualifying reviews, a second branch picks the destination ClickUp list by theme.
  5. 5The workflow creates a ClickUp task with the quote, store, rating, and suggested priority.
  6. 6A confirmation is returned to the webhook caller with the created task ID.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect ClickUpDocs + tasks + chats in one workspace.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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