Engagement Rate: A New Take On The Bounce Rate

by Jey Pandian

Ever seen the bounce rate metric in Google Analytics? Try explaining this metric to clients or internal stakeholders at your company. Chances are that you get a lot of blank stares from them. You might as well talk in Greek to these folks. They won’t get it and beyond the first 30 seconds of your conversation with them, they’ll lose all interest in what you were trying to tell them.

A bounce rate is the percentage of single-page visits or visits in which the person left your site from the entrance (landing) page. I don’t know if that made sense to you (it didn’t make sense to me when I first saw it).

So lately, I’ve been thinking of a new way to present this metric, a way that actually makes sense to people when they first hear it and I thought to myself:

The whole purpose of bounce rate is to show which pages have “low engagement” and which pages have “high engagement.” Why not simply call this metric an “Engagement Rate” and make it the inverse of a Bounce Rate?”

To recap: An Engagement Rate = Inverse of Bounce Rate

So if a page has a Bounce Rate of 90%, one can also say that page has an Engagement Rate of 10% – which essentially means the same thing, as we are just using different words to describe the same  concept.

And so, the Engagement Rate was born. I could walk up to a client and tell them the Engagement Rate of this page is 10% and that 90% of visitors didn’t engage with it. Lo and behold; clients no longer argued about x, y, and z and the validity of the tool. THEY got it. I’d get a few questions about how it was calculated, but ultimately – people got it.

Now my clients can see that 90% of the(ir) users were not engaging with (the page. Moreover, they become talkative and animated, making my job 90% easier. #win

Key takeaway:

As a web analyst, it’s important to talk in a way that makes sense to people. Bonus points if you can do so without using the custom vocabulary that came with your web analytics tool.

It might seem simple to you but none of us understood those words when we first saw them – it took years of practice.

What about you? Do you have any phrases coined by a web analytics tool for which you did something similar? Please share your thoughts via comments below.

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