How to determine if someone is going to convert in less than a second and help them along the way
When someone walks into a brick and mortar store, if they know what they’re looking for, they go straight for it.
When someone arrives at an ecomm store, the commitment to stay is much less and it’s harder to see and find what they want. So, an ecomm store must remove all potential roadblocks between the visitor and the product page.
So, how do you know what visitors want within the first second and how do you get them there?
There are two on-site behaviors that answer both these questions:
Time to first interaction and time between interactions.
Let’s start with time to first interaction–the time between page load and the the first click or scroll. The faster the visitors interact, the more likely they are to convert.
Note: this is why a slower page load time is so destructive to conversion rates.
The trick is combining time to first interaction with either (or both) a digital campaign or an on-site link.
If you combine time to first interaction with a UTM from a digital campaign, you will know what the visitor has just seen and what has motivated them.
Combine either of these with an on-site link and you’ll know the direction and intensity of the visitor.
And this takes us to time between interactions. The interactions between the first and those on the product page demonstrate if the path to conversion increases or decreases the motivation to convert.
This leaves us with two key questions:
How do you track and measure time to first interaction and time between interactions?
How can you increase users’ motivation to convert on your site?
Here comes the sales pitch.
The answer to the first is TUP. You need to track, catalogue, and connect on-site behaviors
The answer to the second is multivariate testing. There are plenty of companies that help with multivariate testing, TUP, of course, is one of them. When considering which to go with, think about what data is collected (quantity, diversity, and reliability are the goals in data collection) and the effort needed to deploy each variation.