MARKET RESEARCH

Earnings-Call Theme-Shift Alert to Slack

When a new earnings transcript is published for a watched competitor, compares its themes to last quarter's and posts a Slack alert only if a theme materially appears…

CategoryMarket Research
Enginesim
Difficultyintermediate
Triggerwebhook
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook: new transcript published for a watched companyHTTP webhook
  • ActionScrape full transcript textFirecrawl
  • ActionExtract current-quarter themes and scoresOpenAI
  • ActionFetch prior-quarter theme profileGoogle BigQueryBigQuery
  • LogicDiff quarters; alert only on material change
  • OutputPost theme-shift summary to SlackSlack

What it does

Turns earnings calls into signal, not noise. Whenever a competitor publishes a fresh transcript, the flow compares the themes against that company's previous quarter and posts to Slack only when something actually changed — a new theme entered the narrative, an old one was dropped, or the emphasis on a theme swung past a threshold you set.

When to use it

Use it when leadership wants to hear about meaningful strategic pivots the moment they surface, but doesn't want a notification for every routine call where nothing changed. Great for analysts and strategy leads who track a handful of key rivals.

How it works

  1. 1A webhook fires when your transcript source flags a newly published call for a watched company.
  2. 2Firecrawl scrapes the full transcript text from the supplied URL.
  3. 3OpenAI extracts the current quarter's themes and their emphasis scores.
  4. 4The flow pulls the prior quarter's stored theme profile for the same company from BigQuery.
  5. 5A logic step diffs the two and decides whether any change clears the materiality threshold.
  6. 6If it does, a Slack message summarizes exactly what shifted; otherwise the run ends quietly and the new profile is saved for next time.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect FirecrawlCrawl, scrape, structured extract.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect BigQueryDatasets, queries, schemas.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Connect HTTP webhookTrigger any URL on agent actions.
  6. 6
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  7. 7
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  8. 8
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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