URL to Markdown for Product Managers — Competitive Intel
Competitive intelligence is reading every competitor's feature pages, changelog, pricing page, and product announcement — repeatedly, monthly, forever. Convert each page to Markdown, drop into your competitive-intel wiki, and the manual Sisyphean reading turns into a diffable archive plus an AI-readable corpus you can query with "what did Competitor X ship in Q1 that we don't have?"
Why this is hard without the right tool
- Scrape competitor feature pages and changelog
- Build comparison docs from competitor messaging
- Archive product announcements across competitors
- Feed competitor docs to AI for analysis and gap-finding
Recommended workflow
- Maintain a list of competitor URLs to track — feature pages, changelogs, pricing, blog announcements
- Open /convert/url-to-markdown, paste each URL on your monthly cadence, and download the Markdown
- Commit each batch to a private Git repo —
git diffacross runs becomes a changelog of what every competitor shipped between snapshots - Merge the corpus with our Markdown merger and feed to Claude/ChatGPT: "extract every shipped feature in the last 90 days, group by competitor, and identify gaps relative to our product"
- For PDF assets a competitor publishes (analyst reports, white papers, sales decks leaked to the web), convert via /convert/pdf-to-markdown so the full intel corpus lives in one consistent format
Frequently asked questions
Best workflow for monthly competitive intel reviews?
A list of ~50 tracked URLs across 5-10 competitors, converted on a monthly cadence (manually paste each URL — under an hour for the whole list once you're used to the workflow). Commit each month's snapshot to a Git repo. Run <code>git diff</code> at month end to surface what changed; feed the diff plus the new content to Claude for a one-page summary memo. Total monthly intel cycle: half a day, instead of the half-week the manual read used to take.
How do I track changelogs across competitors with different formats?
Conversion normalises every changelog page to consistent Markdown — heading per release, list items per change. Once normalised, parsing is simple: extract every <code>## v</code> heading, group by competitor, sort by date. A small script gives you a unified changelog feed across competitors that none of them publish themselves.
Can I diff competitor pricing pages over time?
Yes — same workflow as feature pages. Convert pricing pages monthly, commit, <code>git diff</code> shows price changes, plan-tier renames, feature additions/removals on each tier. Particularly useful for catching competitor "silent" pricing experiments — they often A/B test by URL, and a snapshot diff reveals it where a casual browse would not.
How do I build a feature comparison matrix from converted pages?
Convert each competitor's feature page, merge into one corpus, prompt Claude: "build a feature matrix with rows = features, columns = competitors, values = supported / partial / not supported / pricing tier required, citing the source page for each cell". The structured Markdown input means the matrix is grounded in actual text, not the model's priors about the category.
Can I track competitors I don't want to log into?
Public-facing pages convert anonymously through the MDisBetter web tool — no signup at the competitor required. For pages behind a competitor's product login (in-app changelog, customer-only docs), neither MDisBetter nor any other tool legitimately bypasses that. Use only public pages and respect the access boundary.