Halving what a customer costs you rarely means cheaper ads — usually it means fixing the page they land on, and proving the fix.
You are paying for traffic that arrives, looks around, and leaves. Two out of every hundred visitors buy; the other ninety-eight cost you exactly the same. Most teams respond by buying more traffic, which just scales the leak. Conversion rate optimization — CRO — is the other lever: raise the share of visitors who act, and every channel you already run gets cheaper overnight. A landing page that converts at 5% instead of 2.5% cuts your cost per customer in half without a single extra ad dollar. This course runs the full loop: research first (heatmaps, session recordings, five-user interviews, funnel analytics), then hypotheses you can falsify, then tests that survive scrutiny — sample size, significance, and why peeking at results early makes you ship losers. You will work through the pages where money actually leaks: landing pages, signup forms, pricing tables, and checkout. Mobile gets its own module, because thumb zones and tap targets break desktop assumptions. You finish with an audit of a real product and a scored, quarter-long test roadmap.
Built by Lakshya Kumar
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I am learning conversion rate optimization — the CRO loop, UX psychology principles, landing page design, A/B test mechanics, form and funnel optimization, pricing page psychology, checkout optimization, qualitative research methods, and mobile CRO. Help me build a systematic process for improving conversion rates.
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Anchoring, loss aversion, and mental effort decide the click before your copy does — learn to design with them instead of against them.
Every section has a job — hook, proof, objection, ask. Get the order wrong and visitors bounce long before they reach your pitch.
Most winning tests were called too early on too little traffic — size, run, and read one you can bet real budget on instead.
Cut the fields, split the steps, fix the error states — small friction removals compound into large gains in completed signups.
Too many tiers and vague plan names stall the decision — learn the layout choices that move people onto the plan you want them on.
People with a card in hand still walk at the final step; fix the trust gaps and surprise costs that push them out.
Analytics shows you where people drop out; recordings, heatmaps, and five short interviews tell you why — the part you can act on.
Thumb reach, tap targets, and keyboard types break every desktop assumption — and mobile is where most of your traffic already is.
Run a full audit on a real product and leave with a scored test backlog you can defend to whoever controls the budget.
Complete all modules, then submit the required number of capstone projects. Each must earn a passing rating from an admin reviewer.
Conduct a full CRO audit of a real product page stack: heuristic evaluation using the LIFT model (all 6 dimensions), analytics diagnostic (funnel drop-off analysis, device segmentation, scroll depth), heatmap and session recording synthesis (minimum 10 recordings), 5-user qualitative interview with coded findings, and ICE-scored hypothesis backlog (8 hypotheses minimum). Produce a one-quarter testing roadmap and a one-page executive summary framing the audit findings as revenue impact.
Take a real checkout funnel (yours or example). Map dropoff at each step via funnel analytics. Implement 3 changes (form simplification, trust signals, error-handling). Run as A/B test or pre/post measurement. Produce the report with conversion-rate uplift.
Run an A/B test on a pricing page: 3 hypotheses (anchor pricing, tier reduction, social proof). Calculate sample size, run for the required duration, and report the winner with statistical significance. If you can't run live, produce the experiment-design doc.
Define 3 user segments worth personalizing for. Implement at least 2 personalized experiences (e.g., different homepage hero for paid vs organic traffic). Measure conversion rate by segment. Document the ROI of personalization.
Watch 50 session recordings (Hotjar, FullStory, or LogRocket) of a real funnel. Identify 5 friction patterns; design experiments to fix each. Run or specify the experiments. Produce a report mapping qualitative observation to quantitative test.
The standard tool for A/B test sample size calculation used in Module 4.