RankLens
AI SEARCH VISIBILITY
An AI search visibility SaaS that analyzes a public URL across SEO, AEO, and GEO signals, then turns the result into scores, reports, competitor comparisons, monitoring, and improvement actions.
The challenge was to avoid building a generic SEO checklist and instead create a repeatable SaaS workflow: enter a URL, classify and analyze the page, score it across search and AI-answer categories, preserve history, support paid full analysis, compare competitors, and turn diagnosis into monitoring.
I structured RankLens around URL-level analysis. A public page is fetched, parsed, classified, scored by rule-based engines, enhanced with AI-assisted recommendations, and stored as a reusable report connected to exports, comparison, monitoring, billing, and dashboard history.
RankLens reframes SEO analysis as AI-search readiness analysis: a practical workflow for diagnosing pages, prioritizing improvements, comparing competitors, exporting reports, and building a foundation for recurring monitoring revenue.
Analysis Engine
RankLens is strongest when the page shows the transformation: a public URL is parsed, classified, scored, explained, compared, exported, and monitored.
Public page input
HTML and metadata
Page type and intent
SEO, AEO, GEO
Evidence and actions
History and alerts
Scoring Model
The report separates traditional search readiness from answer-engine and generative-engine visibility, then keeps category evidence attached to the score.
Search crawlability, titles, descriptions, structure, and canonical signals.
Answerability, direct question coverage, concise summaries, and extractable passages.
Generative citation readiness, source clarity, authority cues, and entity context.
Topic coverage, useful structure, internal evidence, and readable sections.
Performance, mobile readability, semantic HTML, and technical reliability.
Report UX
Each diagnosis connects a grade, category bars, written judgment, evidence, and next actions so the user knows what to fix first.
Keep the page's structured explanations while improving citation support.
Add answer blocks, FAQ-style headings, and direct responses to expected queries.
Attach sources, author/reviewer signals, and update notes to claims.
Turn the analysis into client-ready reports or spreadsheet-ready history.
Competitor Compare
RankLens compares the target URL with competitor pages, finds category leaders, explains the gap, and converts the result into priority actions without charging twice for the same full analysis.
Monitoring Loop
Saved reports, reanalysis history, score-drop risk, content-change alerts, exports, usage quotas, and billing turn the product into a SaaS workflow instead of a single free tool.
Same-URL results are grouped so trend changes stay readable.
Monitoring can notify score drops, content changes, and access errors.
PDF and CSV reports move the analysis into client and team workflows.
Quota and entitlement checks connect full analysis to a paid SaaS model.
