MARKET RESEARCH
Weekly Pricing-Page Structural Diff Sweep
Every week, crawls a watchlist of competitor pricing pages, normalizes each into a structured snapshot, and posts a diff that flags structural changes (new tiers, renamed plans.
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly schedule fires
- ActionCrawl watchlist pricing pagesFirecrawl
- ActionParse pages into normalized tier/feature JSONOpenAI
- LogicDiff vs. prior snapshot, classify change type
- ActionUpsert snapshot to tracking tableCoda
- OutputPost grouped structural-change digestSlack
What it does
Maintains a living record of how every player in your category structures their pricing. Once a week it scrapes each watched pricing URL, extracts the underlying structure (tier names, prices, billing periods, feature bullets, CTAs), and compares it against last week's snapshot. The output is a human-readable change log that separates cosmetic edits from meaningful repackaging.
When to use it
Use it when you need a standing early-warning system for competitive pricing moves and don't want to manually check ten tabs every Monday. It catches the changes that matter — a competitor splitting one plan into two, quietly dropping a feature from the free tier, or adding usage caps — that a naive price scraper would miss.
How it works
- 1A weekly schedule fires the run.
- 2Firecrawl crawls each pricing URL on the watchlist and returns clean markdown.
- 3An OpenAI step parses each page into a normalized JSON schema of tiers and features.
- 4A logic step diffs the new snapshot against the prior one stored in Coda and classifies each change as structural, price-only, or cosmetic.
- 5The fresh snapshot is upserted into a Coda tracking table.
- 6A Slack digest summarizes every structural change, grouped by competitor.
Set it up
What you configure once, before turning it on.
- 1Connect FirecrawlCrawl, scrape, structured extract.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect CodaDocs, packs, automations.
- 4Connect SlackChannels, DMs, threads, mentions.
- 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.
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