A/B Test Analysis for Your Business
AB testing consulting makes sure your experiment winners are real and not statistical luck. Omeiro audits conversion tests with Bayesian and frequentist methods, checks for sample ratio mismatch and confirms that significance claims hold up.
What A/B test analysis looks at
The main areas we work through. The exact scope depends on your package and is agreed before we start.
The question
- What you want to learn
- Who to include
- Time period
The data
- Sources and size
- Cleaning steps
- Limits
The analysis
- Right test for the question
- Plain-language results
- What it does not show
The write-up
- Short summary
- Charts
- Next steps
What we cover The exact scope depends on your package and your data, and is agreed before work starts.
What you get with A/B test analysis
Eliminating false-positive experimentation. Bayesian and Frequentist statistical frameworks auditing conversion experiments for sample ratio mismatch (SRM).
Basic Package
Statistical review of 1 A/B test incl. SRM check and significance. 2-day delivery, 2 revisions.
Standard Package
Audit of 5 tests, sample size calculator, Bayesian; frequentist results. 5-day delivery, 2 revisions.
Premium Package
Reusable stats engine in notebook/warehouse, test dashboard; 30 days support. 9-day delivery, 2 revisions.
Clear brief first
We confirm what you need before work starts, so the scope is clear on both sides.
Revisions listed
Each package shows its revision rounds. A round is one list of changes sent together.
Yours once paid
Copyright of the final work passes to you once the order is paid in full.
Your data stays in your own accounts and tools wherever possible, and access is removed when the work is done.
How our A/B test analysis works
Collect the data
We take raw exposure and conversion counts.
Check validity
SRM and tracking problems are looked for first.
Analyse
Results are computed with the chosen method.
Explain
You get a plain statement of what can and cannot be concluded.
AB testing consulting: getting the design right before launch
AB testing consulting is most valuable before a test goes live. We check that the hypothesis is specific, the primary metric is chosen in advance and the sample size matches the smallest change worth detecting. Share your testing tool, event tracking setup and past test results. Decisions such as whether to split by user or session, and how to treat returning visitors, change the validity of results more than people expect.
Common errors include stopping tests early when a result looks good, running many variants without correction and reading results from segments chosen after the fact. Our AB testing consulting documents rules for stopping and for multiple comparisons, so finance and product teams can trust the outcome. Premium adds a reusable stats engine, so your team can analyse later tests the same way instead of rebuilding a spreadsheet each time.
In short
- Delivery in 2 to 9 days, by package.
- Fixed price, shown before you order.
- Growth teams running dozens of experiments.
- Product managers doubting a surprising win.
- Copyright yours after full payment.
A/B Test Analysis: common questions
How much does A/B test analysis cost?
Prices are fixed and shown by package on our A/B Test Analysis pricing page, so you see the full price before you order. You can also ask for a custom quote.
How long does experimentation analytics take?
Delivery depends on the package: Basic 2-day delivery; Standard 5-day delivery; Premium 9-day delivery.
What is included in the Basic Package?
The Basic Package includes: Statistical review of 1 A/B test incl. SRM check and significance. Higher packages add more scope, revisions and support.
Can I get a custom bayesian AB testing setup package?
Yes. If none of the packages fits, use the custom package form on our pricing page to describe what you need, and our team sends you a fixed price.
What is sample ratio mismatch?
A sign that traffic split differs from plan, which can invalidate results.
Bayesian or frequentist?
Both are provided so you can compare.
Can you tell me how long to run a test?
The sample size calculator helps with that.
Do I need a testing tool?
Any tool works if we can export the data.
What is a minimum detectable effect?
It is the smallest improvement you want a test to be able to detect. A smaller target needs more traffic, so choosing it realistically is the first step in planning the test.
Who owns the final work?
Copyright of the final work passes to you once the order is paid in full. Paid fonts, stock files or licences, if used, are licensed in your name.
Ready to start your A/B test analysis?
Compare the packages and pick the one that fits. Not sure which? Write to us and we will help you choose.