MARKET RESEARCH

JS-Rendered Pricing Page Watcher (Headless Browser)

Watches pricing pages that hide their plans behind toggles, modals, or client-side rendering by driving a real browser.

CategoryMarket Research
Enginesim
Difficultyadvanced
Triggerschedule
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule starts run
  • ActionDrive headless browser, render pricing gridBrowserbase
  • ActionStore rendered snapshotCodaCoda
  • LogicDiff vs. prior capture; exit if unchanged
  • OutputAlert on meaningful render changeSlack

What it does

Some pricing pages can't be read by a simple fetch — the plans only appear after clicking a monthly/annual toggle, expanding a comparison table, or running heavy client-side JavaScript. This template drives a headless browser to load each page exactly as a buyer would, captures the fully rendered pricing region, and detects when that region changes between runs.

When to use it

Use it for competitors whose pricing lives in single-page apps, behind interaction (toggles, region selectors, login-gated calculators), or in dynamically loaded widgets that static scrapers return empty for. It's the right tool when Firecrawl alone comes back blank or stale.

How it works

  1. 1A daily schedule starts the run.
  2. 2Browserbase loads each tracked page, clicks the annual/monthly toggle, and waits for the pricing grid to render.
  3. 3The rendered pricing region's text and structure are captured as the day's snapshot.
  4. 4A logic step compares it to yesterday's stored capture and computes a structured delta.
  5. 5If a meaningful change is detected, the run continues; otherwise it exits quietly.
  6. 6A Slack alert links the before/after and names which interaction state changed.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect BrowserbaseHeadless browsers, sessions, replays.
  2. 2
    Connect CodaDocs, packs, automations.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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