AI-Driven Conversion Optimization
Find the constraint before you start testing.
Most CRO programs skip the diagnostic step. They test headlines and button colors while the real conversion barrier goes unaddressed: a trust gap, a funnel mismatch, a misread audience. We fix that.
Testing without diagnosis is expensive guessing.
When conversion rates disappoint, the reflex is to redesign a landing page, swap a CTA, or A/B test a headline. Those tests often show nothing. The common response is to run more tests. The real problem: no one asked what's holding conversion back for this audience, at this funnel stage, with this offer.
Test selection driven by gut feel or competitive benchmarking produces activity. It rarely produces evidence. The highest-leverage question in conversion optimization is what is constraining conversion, and how do we know, not what should we test next.
This is a diagnostic gap. Closing it is worth more than the next ten tests your team could run. It also changes what those tests should be.
Diagnosis before design.
- Funnel mapping and drop-off analysis We trace the full customer journey, identify where volume is lost, and score each drop-off by commercial impact. Not all funnel leaks are equal.
- Behavioral data review Heatmaps, scroll maps, session recordings, and exit surveys are read against the funnel stages, not viewed in isolation.
- Customer language analysis We compare how your customers describe the decision against how your copy, messaging, and offer are framed. Gaps here are often the real conversion barrier.
- Opportunity sizing Each identified opportunity gets a commercial impact estimate. We prioritize by expected lift, effort to test, and confidence in the hypothesis.
- Test design with decision criteria For each priority opportunity, we design a test: hypothesis, primary metric, guardrail metrics, sample size, and the rule that determines what happens when results come in.
Who this is for
- CMOs of $10M–$250M companies Who have invested in CRO but can't point to what changed and why. The testing program looks busy. The revenue impact is unclear.
- Heads of experimentation Who need a stronger analytical foundation, a diagnostic basis, before building out a testing program or presenting to leadership.
- CEOs and founders Who want to understand which part of the funnel is actually the constraint before committing capital to a broader optimization initiative.
FAQ
How is this different from a standard CRO audit?
A standard audit produces a list of suggestions. This produces a prioritized evidence base with commercial impact estimates and specific, designed tests. The difference is between a recommendation and a decision.
Do you run the tests?
We can support execution, but the higher-value work is in diagnosis and test design. Most clients run tests using their existing platforms and teams.
What tools do you need access to?
Typically: an analytics platform (GA4, Adobe, Amplitude), a behavioral data tool (Hotjar, FullStory, or similar), and any existing attribution or CRM data. We work with what you have.
How long does the diagnostic phase take?
Three to six weeks for a thorough diagnostic, depending on funnel complexity and the volume of behavioral data available.
We already have an internal analytics team. Does that matter?
It usually speeds things up. We often work alongside internal analytics teams. Our role is the external diagnostic perspective, not a replacement for existing capability.