Scientific conversion optimization · at scale

A million ways to present your product.
We find the ones worth testing.

Pricing, wording, framing, layout, defaults — the conversion optimization space is too big to A/B test your way through. We collect original behavioral data on your actual customers, then use it to simulate hundreds of variants and tell you which ones are worth running — so you stop optimizing in the dark.

Request free diagnostic → See how it works
Peer-reviewed science Real customer calibration Validated methods
Thomas Graeber

Prof. Dr. Thomas Graeber

Co-Founder

Tenured Professor of Cognitive and Neuroeconomics at the University of Zurich and Director of the Center for the Cognitive Foundations of Economics. Previously Professor at Harvard, 2020–2025. I study cognitive uncertainty and the heuristics people fall back on when overwhelmed — the science behind our method.

Research →
Christopher Roth

Prof. Dr. Christopher Roth

Co-Founder

Tenured Professor of Economics at the University of Cologne. Previously at the University of Warwick and University of Oxford. I run large-scale experiments on belief formation and narrative-driven decisions. My research on how framing and presentation shape choices is the backbone of how we generate and rank variants.

Research →
The problem

Most A/B testing optimizes locally.

Every upgrade flow, pricing page, and checkout step lives in a space of millions of possible variants. A/B testing can evaluate only some of them per quarter. So growth teams end up tweaking what's already in front of them — testing button colors while the real lift is in restructuring tier names, reordering feature lists, or changing a single default.

The variants that would actually move conversion stay untested, because nobody thought of them.

We make the blind spot visible — and help you optimize globally.
Your possible design space
Untested — blind spots
What you've A/B tested
Where the lift actually lives
The rare lucky overlap
The method

Research-backed, transparent at every step.

Every recommendation traces back to peer-reviewed science and calibration data we collected ourselves — and you can audit how we got there at every stage. You don't need to tell us what to test. We find it, and we show our work.

01 / Problem definition

What are we optimizing?

You tell us the decision your customers are making, what they're seeing, and the objective: conversion, revenue, upsell, retention. That's it — we don't need a list of variants from you.

02 / Pre-optimization

A free diagnostic of your touchpoint.

Send us a customer touchpoint and we'll run our diagnostic on it — a real demo of the method calibrated on comparable products. No commitment, no card.

Request free diagnostic → Free
03 / Calibration

Real data on your real customers.

We run our own behavioral data collection on your target customers — surveys and incentivized experiments we design and field ourselves. You don't need to share user data; we generate proprietary calibration data specific to your product.

04 / Perception measurement

How visitors actually experience your touchpoint.

We deploy a scientifically validated battery of perceptions — overwhelm, clarity, trust, attention paths, confusion, unmet needs and many more — built from our own published research. These perceptions are what predict behavior.

05 / Variant generation + simulation

Hundreds of variants, ranked.

From the measured perceptions, we generate interventions individually targeted at the binding constraints on conversion — then rank them through cross-model simulation across ten+ leading models.

06 / Delivery

A ranked A/B test roadmap.

A prioritized list of interventions — predicted uplift, confidence bounds, behavioral rationale, ready to run. Your next A/B test is the right one.

Where it works

Any customer decision you want to convert on.

Wherever a customer makes a decision you care about, we can model it and find the variants worth testing.

Pricing pages

Price sensitivity, plan structure, tier framing, decoy design, left-digit effects. Conversion and revenue, as separate objectives.

Upgrade flows

Free-to-paid conversion, feature bundling, social proof placement, commitment framing, upgrade triggers and CTAs.

Checkout flows

Friction identification, trust signal placement, shipping and payment framing, upsell positioning, abandonment recovery.

Onboarding decisions

Activation milestones, feature discovery, first-action framing, permission requests, retention-critical early choices.

Feature announcements

Adoption framing, positioning relative to existing features, CTA design, migration incentives, rollout messaging.

Email & landing pages

Subject lines, headline framing, value proposition testing, social proof, CTA design — any decision surface.

Scientific rigor

Predictions you can trust.

Naive AI tools predict confidently from generic priors. We don't. Every recommendation passes a scientific reliability pipeline — and we tell you exactly how confident we are in each one.

Real customer calibration
Grounded in behavioral data from your actual target customers — collected by us, not borrowed from generic datasets.
Robustness testing
Every prediction passes a comprehensive battery of scientific robustness checks before we report it. If a finding is fragile, we tell you.
Transparent precision
Predicted uplift comes with confidence bounds. We tell you transparently how precise (or imprecise) each prediction is.
The science behind

Most visitors leave your page unsure what's best for them.

>80%
of consumers report not knowing which option is right for them after visiting a product or pricing page. The problem isn't your product. It's the difficulty of the decision.

Difficulty comes in three forms — and each triggers a different shortcut. When you don't know which type is binding, you're optimizing blind.

— Three types of difficulty
01 — Understanding

Do they grasp what each feature means?

The customer doesn't understand the attributes well enough to evaluate them. When comprehension breaks down, people fall back on the simplest available shortcut — typically price, brand familiarity, or whatever requires the least interpretation.

02 — Self-knowledge

Do they know what they like, want and need?

The customer understands the options but can't map them to their own situation. They don't know which features they'll actually use, how much capacity they need, or which tier fits. This uncertainty drives systematic under-purchasing and deferral.

03 — Integration

Can they hold it all in their head?

The customer understands each attribute and knows what they want — but there are too many dimensions to compare at once. The comparison exceeds working memory. People stop weighing all the attributes and start relying on a single feature, a default, or a gut feeling.

— What our research shows

These difficulties create systematic, predictable distortions in how people choose:

— Key Finding 01

Less sensitive to what matters

Overwhelmed customers become less responsive to price, features, and actual value — the things that should drive the decision. The harder the choice, the flatter the demand curve.

Read the paper
— Key Finding 02

More sensitive to what shouldn't

At the same time, they become hyper-sensitive to presentation: which option is highlighted, how the default is set, how the tiers are named. The framing starts driving the decision more than the product.

Read the paper
The distortions are predictable — which means they're fixable. That's what we do.
Get started

Stop guessing. Test the right variants.

Tell us about a customer touchpoint you want optimized. We'll follow up to collect a screenshot or mockup of the decision screen, then deliver a free diagnostic showing what your visitors actually experience — and which changes are worth testing first.

No commitment. Concrete suggestions in a few days.

✓

Request received.

We'll reach out shortly to collect a screenshot or mockup of your decision screen, then deliver your diagnostic within a few days.