MARKET RESEARCH

Earnings Guidance Sentiment Trendline to Snowflake

Scores the management guidance sentiment of each new competitor transcript and writes a numeric time series to Snowflake so analysts can chart confidence trends across quarters.

CategoryMarket Research
Enginesim
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew-transcript webhookHTTP webhook
  • ActionScrape and isolate guidance sectionsFirecrawl
  • ActionScore guidance sentiment numericallyOpenAI
  • LogicValidate score range and evidence
  • OutputWrite time-series row to SnowflakeSnowflakeSnowflake

What it does

For each new earnings transcript it isolates the forward-guidance and outlook sections, scores management confidence on a consistent numeric scale, and appends a typed time-series record to Snowflake. Over time this builds a queryable trendline of how bullish or cautious each rival sounds.

When to use it

Use it when you want quantitative, chartable sentiment trends across competitors and quarters for dashboards or models, rather than prose summaries. Built for data and equity-research teams.

How it works

  1. 1A webhook fires when a new transcript is available for a watched competitor.
  2. 2Firecrawl scrapes the transcript and isolates guidance, outlook, and Q&A sections.
  3. 3OpenAI scores guidance sentiment and confidence on a fixed numeric scale with supporting evidence spans.
  4. 4A logic step validates the score is in range and tied to real guidance language before persisting.
  5. 5The scored record (competitor, quarter, score, drivers) is written to the Snowflake sentiment table.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect FirecrawlCrawl, scrape, structured extract.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect SnowflakeWarehouses, queries, shares.
  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.

Run this workflow in your colony.

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