UX Design
Research and structure, before anything gets styled.
Marketing & Growth
Overview
Conversion optimization is often reduced to button colors and pop-ups. Done properly it is a research discipline: understand where users abandon and why, form hypotheses about the cause, test the ones with the most upside, and implement what wins. The research is what separates programs that produce durable gains from those that produce a string of inconclusive tests.
We combine quantitative and qualitative inputs — funnel analytics, session recordings, heatmaps, form analytics, user testing, customer interviews and support ticket themes. Together they usually reveal that the real problem is not the page everyone argues about, but an unclear value proposition, a surprise cost, or a form asking for information nobody wants to give yet.
Testing needs statistical discipline. Most tests are called too early, and most reported wins do not survive. We calculate required sample sizes in advance, run to completion, and are candid when a test is inconclusive — which is a legitimate and common outcome.
Business benefits
Analytics, session review, user testing and customer interviews to find the real friction, rather than testing whatever someone suggested in a meeting.
Hypotheses ranked by potential impact, confidence and effort, so the testing calendar targets what could actually move the number.
Sample sizes calculated in advance, tests run to completion, and inconclusive results reported as inconclusive.
Checkout, forms, onboarding, pricing pages and post-conversion flows — wherever the largest drop-off actually sits.
Most US traffic is mobile and most conversion gaps are worst there, so mobile is where testing starts rather than where it is adapted to.
A growing repository of what worked and what did not, so knowledge accumulates rather than being relearned each year.
Problems solved
“Traffic is growing but revenue is flat.”
Funnel analysis to locate exactly where the drop-off is, then targeted testing on that step rather than diffuse site-wide changes.
“Cart abandonment is over 70%.”
Checkout research and testing on the specific causes — usually unexpected cost, forced account creation or payment friction.
“Our A/B tests never reach significance.”
Test bolder changes and prioritize higher-traffic pages. Small variations on low-traffic pages cannot reach significance in a reasonable timeframe.
“Mobile converts at a third of desktop.”
Mobile-specific research and testing — form length, load speed, tap targets, wallet payment options — which usually closes most of the gap.
Our process
Quantitative funnel analysis plus qualitative session review, user testing and customer interviews to locate real friction.
Specific, testable hypotheses with a stated expected effect, prioritized by potential value and implementation cost.
Variant design and build, sample size calculation, QA across devices, and a defined runtime before launch.
Tests run to completion with segment analysis to understand which audiences the result actually applies to.
Winners implemented permanently, learnings documented, and the next hypothesis prioritized from what the test revealed.
Technologies used
Chosen for maintainability and hiring depth rather than novelty. We will justify any choice on request, and we avoid technology that makes you dependent on us.
Industries served
Sector context changes what good looks like. These are the industries where we have delivered this service repeatedly.
Why Mova
The same commitments apply to every engagement, regardless of size or service.
We scope a fixed-price starting point so you can evaluate us on conversion rate optimization before committing to a program.
The team you meet is the team that delivers. You will know exactly who is accountable.
Code, accounts, files and documentation are yours from day one, with no lock-in of any kind.
We baseline before starting and report against it honestly — including the months that fall short.
Questions
The questions we are asked most about conversion rate optimization, answered directly.
Roughly 10,000 monthly visitors and 300+ conversions on the tested page for meaningful A/B testing. Below that we use research-led implementation — making changes based on evidence and measuring before-and-after rather than split testing.
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Next step
Thirty minutes with someone who has delivered this work. We will tell you what it would take, roughly what it would cost, and whether Mova is the right fit.
No pitch deck. A 30-minute conversation about what you are trying to achieve.