Conversion rate optimization

Here’s what our conversion optimization process typically looks like:

• We decide which metric(s) we want to increase based on the marketing strategy.
• See what these metric(s) currently are (to do so, we want to make sure we track all the data that we need to draw conclusions)
• Identify problems and make assumptions as per what we should change/add/remove to increase the metric(s)
• Formulate proper hypotheses for tests. Rank the hypotheses based on their potential and ease of implementation.
• Create the design for the highest-ranked hypothesis (wireframes-mockups-final design)
• Implement the design onto the website with a minimum possible amount of work. Lots of coding happens at this stage.
• Run A/B tests with control variation and experimental variation(s) until they reach statistical significance and a clear winner is decided.
• Analyze the data once the test is considered over by the testing tool. If the experimental variation won, we roll out the solution on 100% of the audience.
• Monitor the metric(s) closely after successfully completing the test to see if the actual changes match the ones we calculated earlier.