MARKET RESEARCH

Quarter-over-Quarter Earnings Tone-Shift Tracker

On a schedule, compares a competitor's two most recent earnings transcripts, flags what management started or stopped emphasizing.

CategoryMarket Research
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerScheduled post-earnings run
  • ActionFind two latest transcript URLs (Perplexity)PerplexityPerplexity
  • ActionScrape both transcripts with FirecrawlFirecrawl
  • ActionCompare QoQ tone + extract deltas with quotes (OpenAI)OpenAI
  • LogicSuppress if deltas immaterial
  • OutputEmail delta brief via GmailGmailGmail

What it does

Detects what changed between a competitor's last two earnings calls. It pulls both transcripts, has an LLM compare them, and surfaces the deltas: topics management newly leaned into, themes they quietly dropped, and language that hardened or softened, each illustrated with quotes from both quarters so the shift is undeniable. The delta brief is emailed to stakeholders.

When to use it

Use it when the story is in the change, not the snapshot. Great for catching a rival pivoting away from a product line, going quiet on a struggling segment, or suddenly hammering a new narrative before it shows up in the numbers.

How it works

  1. 1A schedule fires after the new quarter's call posts.
  2. 2Perplexity locates the two most recent transcript URLs.
  3. 3Firecrawl scrapes both into clean text.
  4. 4OpenAI runs a quarter-over-quarter comparison, extracting started/stopped/intensified themes with paired quotes.
  5. 5A logic step suppresses the email when deltas are immaterial.
  6. 6Gmail sends the formatted delta brief to the distribution list.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PerplexitySearch-grounded answers with citations.
  2. 2
    Connect FirecrawlCrawl, scrape, structured extract.
  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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