PIE is one of many different frameworks for prioritization. It is a quite simple-structure and cross-functional prioritization type, but it is usually connected with A/B testing using.
First, it is important to consider the meaning of A/B testing. It is the experimental check that is held for websites or applications in order to see the real influence of any new feature or change on the entire conversion. Such testing is a common practice for startup companies or those websites that have a millionth traffic.
PIE prioritization helps specialists determine, which features should be tested in the first place and which of them have to wait for a while.
Like many similar prioritization types, PIE consists of the following components:
P is Potential - it indicates how it is possible to measure the changes values on the page
I is Importance - it indicates the value of the traffic on the page with made changes
E is Ease - it indicates the test’s complexity degree
PIE formula
Every component in PIE system has to be estimated with ten-to-one scale, where 10 means the highest and the best indicator, and the 1 is the lowest and, therefore, the most unfavorable. During the prioritizing activity, all the figures are added together, and after that there is an arithmetic average of them what is the PIE total result. The more result is the higher prioritization level.
To demonstrate how PIE works on practice, it is better to compose such a table, as follows:
There is a typical PIE scoring of the planned features for A/B testing. As it can be seen, the lowest PIE result is for the testing of the caption’s new style - it is obvious that this feature can be tested in the last turn. At the same time, the highest figure is for new banner on a main page testing, what is also predictable for such a key element for a website.
To sum up about PIE
The constant practice of PIE prioritization will give such advantages as:
to allocate the resources for A/B and other forms of testing better: it becomes clear what features are deserved to be tested and analyzed
to understand the user’s preferences better and follow the trends in a proper way
to lead the appropriate optimization and track the timely conversion of the website or app.
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