A/B testing is an online experiment conducted to test potential improvements to a digital product. It allows you to see which version works best for your goals, based on data analysis. Ultimately, A/B testing helps you to make decisions based on statistical evidence, know more about your audience, what they like and prefer, and to test all your assumptions you have about the design.
you are wondering whether showing the filters expanded inside the PLP will invite them to use them more and thus react more relevant products for them. You can run an A/B test where you create two versions of the page. One will be as it is now with the filters closed, and the other will be a variation with the filters already displayed.
A/B testing can be very useful for optimisation and analysis.