MARKET RESEARCH

Quarter-Over-Quarter Guidance Change Detector

After each new earnings call for a tracked company, compares the fresh guidance against last quarter's, flags raises, cuts, and reaffirmations, and posts a diff with the exact…

CategoryMarket Research
Enginesim
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook fires on new earnings callHTTP webhook
  • ActionPerplexity extracts new guidance metrics and phrasingPerplexityPerplexity
  • LogicDiff against prior quarter and classify each metric
  • ActionWrite guidance diff to Coda history tableCodaCoda
  • OutputPost change summary to SlackSlack

What it does

When a tracked company posts a new earnings call, this workflow extracts the forward guidance and diffs it against the guidance captured last quarter. It labels each metric as raised, lowered, reaffirmed, or newly introduced, and surfaces the precise wording change so you can judge tone, not just numbers.

When to use it

Use it when guidance trajectory is the heart of your thesis and you want an objective record of how management's outlook is shifting over time — without re-reading two transcripts side by side every quarter.

How it works

  1. 1A webhook fires when your transcript feed flags a new call for a tracked ticker.
  2. 2Perplexity extracts the new quarter's guidance metrics and exact phrasing.
  3. 3A logic step loads the prior quarter's stored guidance and computes the metric-by-metric diff.
  4. 4Each metric is classified as raise, cut, reaffirm, or new.
  5. 5The structured diff is written back to a Coda guidance-history table.
  6. 6A formatted change summary is posted to Slack for the coverage team.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect PerplexitySearch-grounded answers with citations.
  3. 3
    Connect CodaDocs, packs, automations.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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