At Psychlift, we don’t just test randomly—we test with intention, structure, and psychology.

Our Pillar-Based CRO Framework is the reason we consistently hit a 40–50% test success rate, compared to the 15–20% industry average. Let’s break down how it helps us find insights fast and turn them into revenue. 🧠

We organize the entire user experience into a 3-level hierarchy:
• Pillars (our top-level categories): Usability, Trust, Comprehension, Motivation, Offer
• Levers (components within each pillar)
• Sublevers (specific, actionable elements—e.g. “Visual Hierarchy” under Usability)

This lets us zoom out to spot patterns—and zoom in for precision when it’s time to run high-impact experiments.

Our testing approach is supercharged by our lever scoring system:

1. Audit & Score First
• During the CRO audit, we assess and score every lever based on the data we have.
• Levers backed by more data (e.g. heatmaps, user tests, analytics) get higher scores and rise to the top of our testing algorithm.
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2. Win = Boost
• Every test win boosts that lever’s score, which nudges related ideas to the top of the roadmap.
• This fuels rapid iteration. Found a high-performing lever? We’ll squeeze more juice with multiple follow-up tests.
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3. Smart Prioritization
• Our algorithm weighs multiple variables:
        - Screen visibility
        - Placement impact
        - Effort to implement
        - Relevance to your business model (based on past Psychlift experiments)

That means we don’t just test what’s interesting—we test what’s likely to work for your site.

Found a winning lever?
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‍Great! Now we double down.
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For example, if “Product Discovery” (under Choice Selection) worked on Home, we’ll explore it again on Navigation.
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This focused iteration creates compounding results.
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One good idea leads to 3-4 great ones.

We use data from similar business types to predict which levers will move the needle for you.
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We track win rates by lever, location on the page, and many more factors so every test is built on a smarter foundation.
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We don’t just run isolated A/B tests—we build momentum.

Our model helps you stop guessing and start scaling wins—fast. Let's identify your strongest levers and get to work.