SOCIAL MEDIA
Mention-Spike Tracker Log in Airtable
Logs every detected mention spike as a row in Airtable with top posts, peak volume, and sentiment.
How it runs
The automated pipeline, trigger to output.
- TriggerHourly schedule
- ActionPull mentions and evaluate windowApify
- LogicConfirm spike, rank posts, score sentiment
- ActionCreate spike record (Needs triage)Airtable
- OutputPing on-call commsSlack
What it does
Gives every spike a permanent, structured record. Instead of ephemeral alerts, each surge becomes an Airtable row capturing when it happened, how big it got, what drove it, and a link to the evidence — so the team can triage now and review patterns later.
When to use it
Use this when you need an auditable history of brand events: to spot recurring flashpoints, report spike frequency to leadership, or hand new spikes to an analyst with a consistent intake format. Pairs well with an alerting workflow.
How it works
- 1A schedule fires hourly.
- 2Apify pulls the latest mentions and the spike check evaluates the window.
- 3If a spike is confirmed, top posts are ranked and peak volume plus a quick sentiment score are computed.
- 4A new Airtable record is created with the timestamp, peak count, sentiment, top-post links, and a status of "Needs triage."
- 5A short Slack ping notifies the on-call comms person that a new spike was logged and is ready to assess.
Set it up
What you configure once, before turning it on.
- 1Connect ApifyActors, scrapers, datasets.
- 2Connect AirtableBases, tables, views, automations.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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