SOCIAL MEDIA

Brand-Mention Sentiment Triage with Approval Reply Queue

Pulls fresh brand mentions across social platforms every hour, scores each for sentiment and urgency, drafts a tailored reply.

CategorySocial Media
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerHourly schedule fires
  • ActionScrape new brand mentionsApify
  • ActionScore sentiment and urgencyOpenAI
  • LogicDrop spam and no-reply-needed mentions
  • ActionDraft a tone-matched replyOpenAI
  • OutputPost draft to Notion approval queueNotionNotion

What it does

This workflow watches for new public mentions of your brand, decides how each one feels and how fast it needs a response, and writes a first-draft reply for every one that warrants one. Nothing goes out automatically — drafts land in a Notion approval queue where a community manager edits, approves, or discards them.

When to use it

Use it when mention volume has outgrown manual monitoring but your brand voice is too important to hand fully to automation. It is the middle ground: machine speed on triage and drafting, human judgment on the actual send.

How it works

  1. 1On an hourly schedule, an Apify social scraper collects new mentions of your tracked handles and keywords.
  2. 2OpenAI classifies each mention by sentiment (positive, neutral, negative) and assigns an urgency score.
  3. 3A logic step filters out spam and mentions that need no reply.
  4. 4OpenAI drafts a reply matched to the mention's tone and your brand voice.
  5. 5Each draft plus its source mention and scores is written to a Notion approval queue, tagged by urgency, ready for human review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ApifyActors, scrapers, datasets.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect NotionPages, databases, comments.
  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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