This is pretty awesome: Lingerie company Adore Me A/B-tests photos of their models wearing their products to ensure maximum audience engagement that translates into maximum revenue.
For those not in the know, A/B testing is an experiment with two variants, noted as A and B. (Typically, A is the control and B is the variable.) Users are split into randomized groups, so that one will see version A and the other will see version B. (Who sees what version can sometimes change day-to-day due to the randomization.) Those who run the A/B testing are then able to see how users react to each option, and which one would be more impact for consumers over time.
(Companies can use A/B testing for basically any variable they have. For example, I used an A/B test in my last job to determine how email newsletter headlines affected click-thru rates. Control version A was the normal staid headline, while version B was more creative.)
In this “Fast Company” article that details Adore Me’s A/B testing process, writer Rebecca Greenfield details what variables the company tends to change:
“The distinctions between the pictures might include different models wearing the same set in the exact same position, or the same model in the same set in a different position, for example.”
If anything, this news reveals that analytics tools and approaches have crossed over into non-tech fields, and may soon take over more traditional processes of gathering consumer data.
It’ll also be interesting to see how sexuality stats cross over into Big Data. I feel we’re on the cusp of it right now.