Using A/B Testing in HR - Part 1
Introduction to A/B Testing and some ideas on how to use it.
Introduction
As an Advertising graduate who began building websites with stone age tools, and later moved into HR in the Technology industry, I couldn't help but notice the similarities and overlap between some traditional Marketing functions and the Employment Branding and Talent Acquisition side of HR.
Marketing involves identifying and targeting a specific audience, creating messaging that resonates with that audience, and measuring campaign success. Its aim is to create a compelling brand image to attract and retain customers or clients.
Now replace "customers or clients" with "talent," and it becomes clear that clients are successfully converted prospects, just as employees are successfully converted candidates.
Advanced marketing practices, such as persona development, content marketing, and social media advertising, can be applied to employer branding efforts to help HR teams create and promote a compelling employer brand. Data analytics and artificial intelligence can also benefit HR practices by helping to identify and attract top talent. A/B Testing is one of the essential tools in the marketing toolbox.
What is A/B Testing
In its simplest definition, A/B Testing can be described as:
”…a methodology for comparing two versions of a webpage or app against each other to determine which one performs better. A/B testing is essentially an experiment where two or more variants of a page are shown to users at random, and statistical analysis is used to determine which variation performs better for a given conversion goal.
Running an A/B test that directly compares a variation against a current experience lets you ask focused questions about changes to your website or app and then collect data about the impact of that change.
Testing takes the guesswork out of website optimization and enables data-informed decisions that shift business conversations from "we think" to "we know." By measuring the impact that changes have on your metrics, you can ensure that every change produces positive results.”
Source: Optimizely website
A special and more complex case of A/B testing is multivariate testing, which uses the same basic mechanism but compares a higher number of variables and tries to understand also how these variables impact one another.
How to use A/B Testing
A/B Testing is a form of experimentation, and as such the importance is not on the result of each individual test, but rather on what you learned overall from the experiment. To ensure that you derive enough learning from the experiment, you should make sure that you:
Clearly define the problem you want to solve before starting any A/B tests.
Determine the goals and metrics you want to track before starting any tests.
Develop a hypothesis about what you expect the test results to be.
Test only one variable at a time to accurately measure its impact.
Use a large enough sample size to ensure statistical significance, randomizing the application of the tests, whenever possible to isolate the results.
Run tests for a sufficient amount of time to account for any variations or fluctuations.
Analyze and interpret the data carefully to draw accurate conclusions.
Use the results to inform future decisions and continually refine and optimize processes.
In Part 2 of this article, we’ll look at where to use A/B testing in HR, and discuss some challenges and risks.