MARKET RESEARCH
Quarterly Earnings Transcript Miner to Positioning Tracker
Scrapes a competitor's latest quarterly earnings-call transcript, extracts strategic signals with an LLM, and appends a structured row to a Coda positioning tracker each quarter.
How it runs
The automated pipeline, trigger to output.
- TriggerQuarterly schedule per watchlist competitor
- ActionFind latest transcript URLBrave Search
- ActionScrape transcript to markdownFirecrawl
- ActionExtract strategy signals to schemaOpenAI
- LogicSkip if no transcript for this quarter
- OutputAppend dated row to positioning trackerCoda
What it does
Once a quarter it pulls a named competitor's most recent earnings-call transcript, mines it for strategy signals (product bets, pricing moves, market expansion, headcount, guidance tone), and writes one clean row per competitor into a Coda positioning tracker so the table grows quarter over quarter.
When to use it
Use it when you maintain a competitive positioning doc and want it refreshed automatically after each earnings season instead of reading 40-page transcripts by hand. Best for product marketing and strategy teams tracking 5-20 public competitors.
How it works
- 1A quarterly schedule fires for each competitor in your watchlist.
- 2Brave Search finds the canonical transcript URL for the latest quarter.
- 3Firecrawl scrapes the transcript page into clean markdown.
- 4OpenAI extracts a fixed schema of signals: strategic priorities, pricing changes, new markets, guidance sentiment, and notable quotes.
- 5A logic step skips the row if no transcript was found for the period.
- 6The structured signals are appended as a dated row in the Coda positioning tracker.
Set it up
What you configure once, before turning it on.
- 1Connect Brave SearchWeb, news, image, video search.
- 2Connect FirecrawlCrawl, scrape, structured extract.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect CodaDocs, packs, automations.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More Market Research workflows
Hiring Surge Detector with Slack Alert
Detects when a target account's open-role count jumps above its recent baseline and posts a ranked Slack alert to the GTM channel so reps can act on a company that is clearly…
Tech-Stack Shift Inference from Job Descriptions
Reads new job descriptions for target accounts, uses an LLM to extract named technologies and infer stack changes.
Enrich Inbound Accounts with BigQuery Firmographics and Score Fit
When a new account row lands in Airtable, joins it against BigQuery public business datasets to attach firmographic attributes.
Blend BigQuery TAM with Live Competitor Signals into a Notion Brief
On demand, sizes a chosen segment from BigQuery public data, gathers current competitor signals via Brave Search, and synthesizes a one-page market brief into Notion.
Allocate Sales Territory TAM from BigQuery Geo Data to HubSpot
When triggered by a webhook, queries BigQuery public ZIP-level business data to compute TAM per sales territory.
Discover Adjacent Segments from BigQuery and Rank Expansion Bets
On a schedule, scans BigQuery public industry data for fast-growing NAICS sectors adjacent to your core segments, scores them as expansion bets.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.