Step 1: analyze
For the analysis you want to know ‘what’ happens and then ‘why’ this happens. To find out the ‘what’ you have to look mainly at the available data and figures. Data on how many people use your product or service, for example. Data about impact and performance. Mainly many dry figures and data. This also includes data about how a product or service works technically. This data says little when looked at on its own, but if you know how to place it in to context, the data becomes invaluable. That is why it is so important to find out the ‘why’. You can find out the ‘why’ by conducting qualitative research. You can do this in different ways. From questionnaires by email to conducting user research, such as usability testing with people from your target group.
Step 2: prioritize
Almost everything can be tested. Therefore it’s wise to start at the places where you can gain the most results. You should’ve have discovered which exact places that are during step 1. For digital products, it are often the places that are used the most or that are visited the most. For physical products it could be the places where you received the most feedback during your qualitative research. When prioritizing, it is important not to stare blindly at the quantitative data. You mainly use this data as a compass during your search. The most valuable insights are generally found in the qualitative data.
Step 3: testing
After completing steps 1 and 2, the foundation has been laid down for the real thing. The actual testing and optimization based on the results. Before you can start, you only have to make a clear test plan. This plan ensures that you have clarity about what you are testing and for what reason. This is the only way to arrive at conclusions from which any optimizations can arise.
The basis of each test plan is a clearly defined hypothesis. For example, if you have a high drop off in your checkout process, your hypothesis may be: “Our credibility is being questioned by our users because they encounter language errors in the checkout.” A good hypothesis:
- is testable and measurable
- has the purpose of solving usability or conversion problems
- provides market insights
Step 4: process insights and start over
A lot of tests will probably not give the results you expected in advance. Does this mean that the test was not successful? On the contrary! They’re just as valuable as tests that are successful because they provide valuable knowledge about your users and give you a new baseline for your next research. After each test, successful or not, continue to the next. An optimization process is never finished. If you don’t continue to improve, you’ll miss out on new opportunities and there’s a good chance that you’ll eventually fall behind your competition. Never stop optimizing.
Maibru, a brand strategy design studio.
We help brands with getting strategic, communicative, and visual clarity.