Money Page Finder
Auto-detect the most revenue-critical pages on any website. Surfaces pricing, signup, checkout, demo, and contact pages from the sitemap — the ones that must never go down.
By Deepak Shukla — Founder & CEO, Pearl Lemon
What This Tool Checks
- All URLs in the sitemap (and common sitemap variants: /sitemap.xml, /wp-sitemap.xml, /sitemap_index.xml)
- Pages classified by URL pattern: checkout, pricing, signup, demo, contact, product, landing, homepage
- Per-page confidence score (0-100) based on URL structure and path depth
- Top 40 candidates ranked by score
- Fallback: scans homepage links if no sitemap exists
Why This Matters
Most uptime monitoring watches the homepage only. The homepage doesn't convert — the checkout, pricing, and signup pages do. When those go down (often silently — they're behind login walls, A/B test variants, deploy branches) revenue disappears with zero alerts. This tool inventories every revenue-critical page on your site so you can monitor what actually matters. Pair with LemWatch monitoring to alert when any money page returns a 500, slows down, or loses key text.
How to Fix Issues
- 1.Once you have the money-page list, add each to your uptime monitoring (we make this one-click in LemWatch Pro)
- 2.Set up content-assertion monitoring: alert if "Add to Cart" button text disappears, or if pricing page returns "404"
- 3.Run synthetic transactions through checkout weekly — uptime monitoring alone won't catch broken payment forms
- 4.Cache your money pages aggressively at the CDN edge (these pages benefit most from CDN even if they're dynamic)
- 5.Create dedicated runbooks for each money-page outage — these incidents need <5 minute response time
Most teams obsess over homepage uptime and ignore the pages that actually generate revenue. This tool flips that. It auto-detects the URLs on your site that convert visitors into money — so you know exactly what to monitor obsessively and what to test before every deploy.
The money-page concept
Every revenue-driven website has a small set of pages that disproportionately determine income. For SaaS: pricing, signup, checkout, dashboard login. For ecommerce: product pages, cart, checkout. For service businesses: contact, book-a-demo, request-quote. These pages share three properties:
- They're where conversion actually happens
- They're usually a small percentage of total pages (5-50, not 5,000)
- When they break, no one notices for hours because most monitoring watches the homepage
How auto-detection works
We classify URLs by path pattern. Years of pattern analysis across thousands of websites yields a reliable rule set:
- Highest confidence (90-95):
/checkout,/cart,/pricing,/plans,/payment— these are unambiguous - High confidence (75-85):
/signup,/get-started,/trial,/demo,/book-a-demo— these convert directly - Medium confidence (60-70):
/products,/shop,/lp/,/landing/,/offer/— these often convert - Lower confidence (40-65):
/contact,/sales, homepage — context-dependent
We then adjust scores for path depth (shallow paths = more important), query strings (often AB-test variants, slightly lower), and language prefixes. Final scores cluster into a top-40 ranked list.
Sitemap-first, homepage-fallback
We try four common sitemap locations in sequence: /sitemap.xml, /sitemap_index.xml, /sitemap-index.xml, /wp-sitemap.xml. If we find a sitemap index, we follow up to 10 child sitemaps and aggregate. If no sitemap is reachable, we fall back to extracting all internal links from the homepage HTML. Either way, we cap at 2,000 URLs to keep response time bounded.
What you do with this list
Three immediate actions:
- Add each to uptime monitoring. Most monitoring tools (including ours) charge per-monitor; this list tells you which 10-20 monitors are worth paying for, vs which 500 pages don't need synthetic checks.
- Add content-assertion checks. "Alert if pricing page no longer contains the word '$99'" or "alert if checkout page no longer contains 'Add to Cart'." Catches silent deploys that uptime-only monitoring misses.
- Add to release-checklist smoke tests. Every deploy should hit each money page and verify a 200 + key content. Should take 30 seconds in CI.
Why this beats manual inventory
Manual inventory misses two failure modes: (a) the marketing team adds a new landing page that engineering doesn't know about, (b) old pages get repurposed (a /demo page that used to be a sales page is now the actual demo signup). Sitemap-driven detection catches both because the sitemap reflects what's actually live, not what someone documented two years ago.
What this doesn't do
We use URL-pattern heuristics only — we don't analyse page content, run conversion tracking, or use your analytics. Sites with unusual URL conventions (/p/buy-now/ instead of /checkout/) may not classify correctly. False positives (low-priority pages flagged as money pages) are easy to dismiss; false negatives (money pages missed) are caught by reviewing the URL list manually.
Methodology
Given a domain, we probe four common sitemap URLs in sequence: /sitemap.xml, /sitemap_index.xml, /sitemap-index.xml, /wp-sitemap.xml — each with a 15-second timeout. The first reachable sitemap wins. If the sitemap is an index, we recursively fetch up to 10 child sitemaps (depth 1) and aggregate up to 5,000 URLs. URLs are extracted via <loc> parsing. If no sitemap responds, we fall back to fetching the homepage HTML and extracting all internal href= attributes pointing to the same origin. For each URL, we apply a path-pattern classifier with 8 rule sets (checkout, pricing, signup, demo, contact, product, landing, homepage), each with a base score 40-95. We then adjust: shallow paths (<= 2 segments) get +5, deep paths (>= 5 segments) get -15, query strings get -10. URLs scoring below 35 are discarded. The remaining candidates are sorted descending by score and the top 40 are returned. We don't fetch or analyse page content — this is URL-pattern classification only, optimised for the common case where money-page URLs follow conventional naming. Total response time targets under 20 seconds even for large sitemaps.
Frequently Asked Questions
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HTTP Status Code Reference
Understanding HTTP status codes helps you diagnose issues found by this tool: