One test, run properly, so you can trust the answer.

Scale and commitment. This is one test: a single change, designed, instrumented and read to a standard, then delivered with a verdict. Conversion Optimization is an ongoing program, a prioritized backlog of hypotheses, a run rate of tests month over month, and a compounding record of what moves your numbers. Many clients start here to see the method applied to one real decision, then move to the program once it has earned their trust.

The setup itself is easy enough to run without help. The hard part is discipline. A plugin will show you a confidence number that gets recomputed every time you check it, and stopping the moment it turns green inflates the false-positive rate without you noticing. What you are paying for is the discipline the tools do not enforce: a sample size fixed in advance, a stopping rule set before launch, tracking verified to measure the right thing, and a read done against the plan rather than against whichever chart looks best.

It depends on your traffic and how small a change needs to be detected, and we work that out before launch rather than guess at it. Higher traffic and a bigger expected effect mean a shorter test; low traffic or a subtle change means longer. As a rule, useful tests are designed to land within a two-to-eight-week window and run for at least one full week to capture day-of-week patterns, per Statsig. If your traffic genuinely cannot power a meaningful test, we flag that up front instead of running one that cannot conclude.

Then the report says so, clearly, and explains why: usually not enough traffic to detect the effect within the plan, or a true effect too small to separate from noise. An inconclusive test is still a real answer. It means the change is not worth shipping on the current evidence, which is far more useful than a falsely confident win you would later regret. The report also states whether running longer could realistically change the read, or whether the better move is to test something else.

It is human work. A specialist frames the hypothesis, chooses the metric, runs the power calculation, sets the stopping rule, and reads the result against the plan. Tools do the arithmetic, as they should, but the judgement, deciding what is worth testing, whether the tracking is trustworthy, and what the numbers actually mean for your business, is craft, not the output of a generator. A specialist directs the work and reviews it before delivery.

Raveneye Global operates as RavenGroup Global Tech Private Limited, and billing is in USD with no surprise conversion. What matters for a test is that the method is testable and the read can be checked: the sample size, the stopping rule, and the tracking are all documented. A named specialist owns your experiment, directs it, and signs off on the verdict before it is delivered.

No. The point of an experiment is to find out whether a change helps, and a properly run test has to be able to come back and say it does not. We design and run the test to the plan agreed at the start and read the result against it, not toward a particular answer, because a test with a predetermined outcome is not a test.

Because the work genuinely differs. A test on a high-traffic page with clean tracking is a different job from one on a low-traffic form where the measurement has to be built and verified first. A single published price would either overcharge the simple case or under-deliver on the hard one. We publish the method and the deliverables, scope the exact test against your page and its traffic, and confirm the figure in writing before anything is committed.

A live, correctly designed test, and when it completes, a clear verdict with the reasoning behind it: ship, drop, or not yet conclusive. You also get the written test plan, the tracking setup, and a short record of the experiment, so it can be trusted and referenced later rather than becoming another half-remembered result nobody is quite sure about. Any tracking built during the test stays with you to reuse.