SOCIAL MEDIA
On-Demand Mention-Spike Postmortem Brief in Confluence
Triggered manually after a spike, an agent reconstructs the full event timeline from Apify, summarizes the narrative arc and key posts.
How it runs
The automated pipeline, trigger to output.
- TriggerManual run with brand term and date range
- ActionPull full mention set for windowApify
- LogicBuild timeline, find peak and amplifiers
- ActionPublish postmortem pageConfluence
- OutputLink team to the postmortemSlack
What it does
Produces the retrospective comms always means to write but rarely does. On demand, an agent pulls the entire mention history for a chosen window, reconstructs how the spike rose and fell, identifies the pivotal posts, and writes a clean postmortem in Confluence.
When to use it
Run this after a spike has cooled — once the dust settles on a viral moment or a flare-up — when leadership wants a written record of what happened, how it spread, and what the team learned. Best for documentation-driven orgs on Confluence.
How it works
- 1An operator triggers the run manually, naming the brand term and date range.
- 2Apify pulls the complete mention set for that window.
- 3An agent orders posts into a timeline, finds the peak, and identifies the originating and amplifying accounts.
- 4The agent writes the narrative arc, lists the top posts as evidence, and drafts lessons-learned.
- 5A Confluence page is published under the comms space.
- 6A Slack note links the team to the finished postmortem.
Set it up
What you configure once, before turning it on.
- 1Connect ApifyActors, scrapers, datasets.
- 2Connect ConfluenceSpaces, pages, blueprints.
- 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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