During World War II, researchers from the Center For Naval Analysis were conducting a study on fighter planes that had returned from their mission. Researchers found that the most damage was done to the wings, and recommended extra armor be added to them. It wasn’t until mathematician Abraham Wald pointed out a critical flaw in their research, that the recommendation changed completely: the researchers had based their findings on the planes that actually came back. Planes with wing-damage made it back, planes with fuselage-damage didn’t, but obviously weren’t researched. Researchers almost came to the wrong conclusions, because they were effectively looking the wrong way.

This same mistake happens online quite often; we’re all so busy looking at our converting visitors, we tend to ignore other visitors, while they are way more interesting from an optimization standpoint. Funnel-abandoners will give you more insight into what’s wrong with your funnel than the people that actually complete your funnel, the only problem is that you can’t do anything for the user that abandoned your funnel right away, they become a number in your reports. Essentially, you want to recognize these interesting groups of users immediately, instead of after the fact. This requires users to be on the website, where we love metrics like ‘time on page’, but what about the time the visitor is off the page?

Time off-page?

Yes, time off page. Let’s say you have a website that has a few direct competitors, chances are users on your product pages are comparing between your products or services, and those of your competitors. If your analytics show that your pricing-pages or product-detail pages have an average time-on-page of approximately 24 minutes, it’s pretty likely your visitors are comparing your product with someone else’s. Once you know your visitor is comparing products, you might want to persuade them to buy yours by showing your USP’s more prominently, mentioning you have free shipping or even by giving the visitor a discount. Persuasion is everything for this type of user, but you need to recognize them first.

Recognising comparing users

Consider a regular desktop user that has done a product search and opened a few of the results in new tabs. This user had your product page open, and the time on page keeps ticking, while there are no interactions. This user is probably switching between tabs, checking details. We can actually measure this by using window.focus.Here’s a quick example I made as a proof of concept, just open in and switch tabs a few times, it’ll count how long you’ve been absent from the page, and how many times you’ve refocussed. For the example, if the page has been passive in a browser-tab, the counter will keep track of how many times you’ve refocussed, and how long you’ve been passive. With this data, you can use all kinds of methods to try and get users to convert on your page. The example tries:

• mentioning a free return policy if you’ve been passive for 10 seconds.
• mentioning free shipping if you’ve been passive for 20 seconds.
• giving out a $5 discount if you’ve re-focussed on the page 4 times.

You could even go further, and not only measure passive focus time, but also active focus time; and measure if your page is winning or losing in the comparison, based on the active/passive ratio. Maybe you could even define a specific segment of comparers, to use for your ad-targeting, or go nuts by asking them to come back in the title-tab of their browser.

I’m not saying it’s perfect, but for commerce websites, this should be an interesting test to run. If you decide to test this segment, let me know in the comments!