Offer and audience alignment
Set up a controlled experiment with a useful metric and a clear decision rule.
A/B testing implementation
Set up a controlled experiment with a useful metric and a clear decision rule.
Set up a controlled experiment with a useful metric and a clear decision rule.
A button click is not a sale. We align the page, form and measurement plan around qualified enquiries or transactions so subsequent decisions have a useful basis.
The measurement plan connects the agreed work to meaningful customer actions.
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“They are very professional and they take their time on their work to provide you the best possibilities for your project.”
“ICM performed a stellar job on this contract and they ALWAYS give more than what you bargain for.”




WHAT YOU RECEIVE
Businesses improving an existing website, acquisition journey or marketing workflow.
Run agreed representative cases and record the outcome and remaining limitations. Results identify the tested environment and coverage; they do not imply that every device, attack or future business condition was tested.
Configure the agreed environment and named functionality, with ownership and access recorded. A staging or controlled release is used where feasible, followed by the specified functional checks and a documented rollback route.
The brief defines the exact results framework required for a/b testing implementation. We show the named output at its review milestone and record any data, access or third-party dependencies before handover.
Tests need sufficient traffic and duration; early differences are not proof.
Any additional work is scoped and priced for your approval.
THE DELIVERY PATH
Follow the preparation, review and delivery stages for this service.
Review the audience, offer, traffic source and existing customer journey.
Agree the content, technical change or experiment and its success measure.
Verify the experience, events and relevant platform connections.
Report the implementation and the evidence available for the next decision.
Includes Test hypothesis, Variant implementation and Results framework. Tests need sufficient traffic and duration; early differences are not proof.
No. We define the work and measure outcomes, but search engines, audiences and competition are outside our control.
Media budgets and third-party subscriptions are separate from the implementation fee.
We prioritize clear usability and measurement first. Reliable statistical A/B-test conclusions require adequate traffic and a suitable test design.
YOUR NEXT LEAP STARTS HERE
Share the change you want to make. We will help turn it into a clear, practical project.