Form Optimization Tips with Alun from Zuko

You already know that website optimization is important. But what about form optimization?

According to Alun Lucas, Managing Director at Zuko Analytics, getting your forms right is a key piece of the optimization puzzle.

Optimized forms mean smoother completion by users—and higher conversion rates.

On The Research LAB, Alun talked about: 

• The form optimization knowledge gap—and how to fill it
• The research methods and data points that can assist with form optimization
• The role of qualitative data in form optimization

What is the “knowledge gap”?

“Knowledge gap in terms of forms typically means you have an analytics on your forms, and you might know how many people reach your form, and you might know how many people successfully complete it. But aside from that, your form is a black box. You don't know what happens. Your setup doesn’t tell you what people are doing in your form. So you just don't know why people are dropping out… or if they're struggling with any particular field. Essentially the knowledge gap is not having the knowledge to optimize your form,” said Alun.

When you don’t have critical information about how users are interacting with your form, you can’t make informed decisions about how to improve it. And when you can’t properly optimize your form, you won’t be able to improve your conversion rate. 

What metrics can businesses use to help fill the knowledge gap?

“In terms of the basics, everyone tends to look at abandonment figures. So, what's the last field or element within your form that people interact with before leaving? And that's always a good place to start. You've obviously got to look at it in terms of total volume of abandonments. But also an abandonment rate, because forms, especially nowadays, they're very dynamic. You might not be serving every question to every user. So you want to know what proportion of people who interact with it drop out on it. That's always a great place to start, but it's not the be-all and end-all,” Alun said.

Other metrics that Alun recommends using are field returns: typically when users move backward within a form in order to make a correction. He assesses things like: 

• Do people have to keep bouncing back to a particular field? 
• How long are they spending in the field? 
• If you've got any setup error messages, what error messages have been generated? 

You can use these metrics to home in on the struggles that users are encountering. 

“The classic user segment that we use to start off with typically is users who successfully complete your form and users who don't. So they abandoned,” Alun said. “It is the key hypothesis that some of your greater insights come from the difference in behavior between those two groups.”

If users spend time to complete the form, click submit, and are unable to do so, you’ve immediately lost people who want to give you money.

What research or data points do you suggest businesses look at?

“There's tools out there that show you how users are moving through your form and bouncing… but you might want to overlay other things on top of that, to help you develop the hypothesis that you want to test. For example, you may know there's an issue with the email field. It's clear that there's a problem here. So what are the hypotheses? As well as obviously just opening up your form, trying to break it, and seeing what goes on. In terms of other data sources, there's things such as heat maps, eye tracking, user testing, those sort of things.” said Alun. 

Exploring additional data sources like heat maps and eye tracking can provide insights that analytics alone will not, helping you understand not only where the problems are, but also more specifically what they are. 

For instance, perhaps people are trying to click on something that isn't clickable within your form. An analytics platform won't necessarily catch that. Your form analytics will tell you where people have been, but not the specifics of why they are flowing through it in the way they are. 

What is the value of eye-tracking?

“We've done some eye-tracking studies that are on our website. We tend to see it's a great tool for helping streamline the UX. We see things like, where do you place your instructional copy? We've seen cases where instructional copy is on the right of the screen, the field’s on the left. People are dipping back, trying to see what does this apply to, does it match? Is that different on mobile? It’s frustrating. It may or may not cause an abandonment, but it's certainly unnecessary.” said Alun.

A classic example Alun pointed to is a DOB drop-down menu. Some drop-downs go all the way back to the year 1900, causing users to scroll all over the place. In contrast, a simple free-text box would allow users to quickly enter their birth year and move on. 

Eye-tracking will pick up on this issue, giving clues for how to improve the smoothness of your form. True, it’s difficult to quantify the effect of such a change. But it means people are spending less time on your form, and passing through it smoothly. 

“If the experience isn't causing an issue. Then you can just focus on okay, are there any questions or any error messages that are causing issues, rather than worrying about the broader flow,” Alun said.  

What is the role of qualitative data within form optimization? 

“It's great to refine your hypotheses and also sometimes reveal reasons why people do things and are dropping out. An example that we've seen user testing help reveal the answers, which in hindsight was fairly obvious, but people who are signing up for a credit check. They go through and give their email address or what have you. As soon as the email address comes in, an error message was triggering a lot. And it was because they'd already got an account, and just didn't realize it. It just refines the hypothesis. You can see someone actually doing it.” Alun said.

Qualitative observation allows you to delve into questions like: 

• How tight is my error message? 
• How helpful is my error message? 
• Are people just entering random data in order to move on? 

Qualitative data can help surface those hypotheses so that you can test error messages (and other elements) appropriately. 

“You don't have to necessarily pay for big, sexy user testing. Just let your mum do it or whatever. See what their initial feedback is. And you get those things like, ‘well, I don't even understand what this means. And the error message is even more confusing,’” Alun said.

Ultimately, qualitative stories about real users can also help you sell your approach to key stakeholders in order to get the business to take action. Once you've captured an insight, it's very useful to show the real-life experience of a user who is suffering through your form, and not giving your company money because of a bad experience.