Your test velocity is the ceiling on your growth rate.
Conversion gains compound. Every winning test raises the baseline the next test runs against. That means the number of tests you can actually get live per month matters more than the cleverness of any single one. Run the numbers on your own program.
A model, not a promise. Wins compound, but they also overlap, so each additional winner is discounted rather than multiplied cleanly. Your real result depends on traffic, funnel, and what you choose to test.
Where the days come from.
"Faster" is only a differentiator if you can say where the time goes. Here is the actual test lifecycle, and the specific places AI assistance removes waiting rather than removing rigor.
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01
Research & hypothesis
Analytics, session recordings, and competitive teardown synthesized into ranked hypotheses, each carrying the metric it should move and the reason to believe it will.
AI-assisted -
02
Variant build
The variant is implemented against your real stack rather than mocked. This is the step that usually costs a traditional agency a week of ticket queue.
AI-assisted -
03
Pre-launch QA
Cross-browser, cross-device, and tracking validation before a single visitor sees it. A test that fires wrong is worse than no test at all.
AI-assisted -
04
Launch & monitor
Live in your platform (VWO, Optimizely, Intellimize, or a custom layer) with guardrail metrics watched from the first hours.
Human-owned -
05
Read & report
Called on pre-registered criteria, not on the day the number looks good. You get the result, the confidence, and what it means for the next hypothesis.
Human-owned
We track cycle time, hypothesis to launch, on every engagement from day one and report it to you alongside your results. Until a program has enough logged cycles to publish a number, we describe the speed qualitatively rather than inventing a figure. If a CRO agency quotes you a precise average cycle time on a first call, ask them for the distribution.
Four ways in.
Most programs start with the audit. It is the cheapest way to find out whether we are any good before committing to a retainer.
CRO & Personalization Audit
A fixed-scope, one-to-two week paid engagement. Funnel analysis, session recording and analytics review, competitive teardown, and a prioritized test roadmap you own outright, whether or not you continue with us.
- Full-funnel analysis against your real analytics
- Competitive teardown in your category
- Prioritized roadmap, ranked by expected value
- Yours to keep, and to hand to any vendor
Experimentation Retainer
The ongoing program: hypothesis generation, build, QA, launch, analysis, and stakeholder reporting. Higher monthly test velocity at the same retainer as a traditional agency.
How the retainer runs →Fractional CRO / Head of Growth
Strategic ownership of your experimentation program, directing your internal team or another execution vendor. For companies with hands but no one setting the agenda.
What ownership includes →Personalization Build
Fixed-scope implementation of a personalization layer (segment logic, dynamic content, and targeting rules) in VWO, Optimizely, or a custom logic layer.
See the build scope →Pricing Engagement pricing is quoted per program after the qualification call, because scope depends on funnel complexity and the test velocity you want to commit to. Start with a teardown and you will have a number in writing before any proposal call.
This does not work for everyone.
Test velocity depends on your traffic, not on our effort. We screen for it up front because a program that cannot reach significance wastes your money and our reputation.
- Meaningful paid acquisition spend, so tests reach significance in a reasonable window
- Enough monthly conversions to call a test, checked independently of spend
- GA4 or equivalent already instrumented
- An existing funnel to optimize: trial signup, checkout, account opening, KYC, application
- Direct access to a decision-maker who can approve a test this week
- Pre-product-market-fit. Your problem is PMF, not conversion rate, and testing will not find it
- High spend but very low conversion volume. Long B2B cycles cannot clear enough events to test quickly
- No analytics in place. Engagement time would go into instrumentation, not testing
- Approval routed through an agency layer that slows every launch
- Looking for a redesign. That is a different purchase, and we will say so
DTC SaaS
Trial-to-paid, onboarding activation, upgrade and expansion flows, pricing page mechanics.
FinTech
Account opening, KYC completion, funding and activation events, card and loan applications, where small percentage gains carry large absolute revenue.
LATAM-facing
Bilingual experimentation with genuine regional fluency. Copy tests in Spanish that were written in Spanish, not translated into it.
Twelve years of other people's funnels.
The experimentation work behind this practice ran inside agency and in-house programs across fitness franchise, course platform, and creator-economy SaaS categories. We describe that work anonymously and show no client logos. Those programs belong to the companies that ran them, not to us.
Aggregated conversion lift delivered across client experimentation programs during the founder's tenure at a national performance marketing agency.
Hands-on experimentation across agency, in-house, and founder roles, running programs rather than advising on them.
National fitness franchises, a course-and-membership platform, funnel-software SaaS, and creator-economy tools.
No logo wall, no invented case study percentages, and no client testimonials we cannot source. The numbers above are the ones we can stand behind in a room with your CFO. On a qualification call we will walk through specific programs in detail, verbally, with the same discretion we will extend to yours.
Testing finds the winner. Personalization decides who sees it.
A single winning variant is an average across everyone who hit your funnel. Personalization is what you do once you know the average is hiding two different audiences with two different answers.
We build the segment logic, dynamic content, and targeting rules that let your best-performing experience find the visitor it actually works for, implemented in your existing testing platform, or as a custom logic layer when the platform gets in the way.
How personalization is builtSynthetic example, not client data
The blended number says "barely worth shipping." The segments say ship it to two audiences and build something else for the third. That decision is the product.
We run a small venture studio.
Awasero builds and holds its own products: menu.link, Synced, SplitMinder and others. It is why we implement against real stacks instead of handing over a slide. It is not what we sell you.
Let's find out what your funnel is hiding.
A teardown call, then a short qualification form so we can check the traffic math before either of us spends time on a proposal. If you are not a fit, we will tell you on the call and point you somewhere better.