MARKET RESEARCH

New transcript watch and surprise alert

Polls a competitor's investor relations page on a schedule, detects when a new earnings transcript is published, summarizes it, and emails an alert that flags any guidance…

CategoryMarket Research
Enginesim
Difficultyintermediate
Triggerschedule
Steps7
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerScheduled poll of competitor IR pages
  • ActionScrape IR transcript listingFirecrawl
  • LogicDetect new transcript vs last-seen, else stop
  • ActionScrape full transcript + read consensus from CodaFirecrawl
  • ActionSummarize call and extract guidanceOpenAI
  • LogicCompare to consensus, set BEAT/MISS/INLINE flag
  • OutputEmail surprise-tagged briefingGmailGmail

What it does

Watches competitor investor-relations pages so you don't have to. On each scheduled check it scrapes the IR page, detects whether a new transcript has appeared since last run, and only if one has, summarizes the call and compares stated guidance against the consensus expectations you logged in Coda. If guidance lands meaningfully above or below expectations, the email is marked as a surprise.

When to use it

Run it during earnings season for names you can't afford to learn about late. It turns "someone noticed the competitor reported" into an automatic, same-day briefing.

How it works

  1. 1A schedule polls the watch list a few times daily during the reporting window.
  2. 2Firecrawl scrapes each competitor's IR transcript listing.
  3. 3A logic step checks the latest item against the last-seen URL and stops if nothing is new.
  4. 4Firecrawl pulls the full new transcript text.
  5. 5OpenAI summarizes the call and extracts headline guidance.
  6. 6A logic step compares guidance to stored consensus and sets a surprise flag.
  7. 7Gmail sends the briefing, subject-tagged BEAT, MISS, or INLINE.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect FirecrawlCrawl, scrape, structured extract.
  2. 2
    Connect CodaDocs, packs, automations.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect GmailRead, draft, send, label.
  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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