24.6 C
Texas

What Can I Learn From User Password Frustration?

- Advertisement -

You may have done all you can to optimize your site and make it clean, sleek, and bug-free, but depending on your content, there’s plenty more to do; if you’re selling a product, there are always more customers to catch, and there’s always churn to reduce. This goes double for affiliate marketing sites, who seek to answer their users’ questions while also clicking appropriate links to buy marketed products. Even if you are a content site that isn’t monetized, it’s important to keep your readers engaged.

Once you have data about how your site is being used, you can break down and compartmentalize that data into behavior signals. When users try to log in to your site and are prevented by a wrong password, it can set up a product for failure even though it has no fault in it whatsoever.

What are behavior signals and why are they important?

Behavior signals are a combination of data and analysis that provides insight into how a site is used and why users perform certain actions. These signals attempt to categorize how users feel about a site and why they feel that way. These behavior signals aggregate all actions and reactions – positive, negative, and neutral. UX, after all, hopes to manage all those feelings.

- Advertisement -

If your users use the site exactly how you want them to, those are positive behavior signals. It is extremely valuable to see users click on a link exactly when they are meant to or navigate directly to the call-to-action button.

You can also learn about what users don’t like and the corresponding negative behavior signals, especially when it comes to passwords. For example, ExpressVPN’s research shows the negative externalities of password frustration. In most cases, the new changes of one-time links or SMS codes are slightly better but still lead users to be annoyed by their experience. It could help website owners get more exact data on how their users use the site.

Take Maps, for example, are important for supplementing the raw data of how many times a link or button has been clicked. You can learn if users are attempting to click on something that isn’t clickable, in which case the text or layout can be edited to improve clarity. You can also monitor the exact word (or words) that a user is clicking in a link, which can give insight into what encouraged them to click the link. Or, if they were repeatedly clicking in the same area, you can get insight as to why they are frustratedly clicking the same spots. Maybe a link is broken, or they’re trying to find something that isn’t on the page. 

You shouldn’t just focus on what your users like and don’t like, though; it is equally important to learn what they don’t care about at all. If your users are completely ignoring large swaths of your site, there may be some room to change them into something they do care about or completely excise them. (Though if those large swaths are important for SEO and organic traffic, that’s another story.)

Utilizing these signals

Once you have access to these behavior signals, you can change the layout appropriately, directing users to where you’d like them to go while also eliminating their pain points. If you can fix “rage clicks,” buggy display issues, or scrolling past key links without clicking, you can improve the site’s value while also improving UX and maximizing user satisfaction.

Behavior signals can also be preemptive. They provide knowledge about how users interact with a site and how they might interact with future iterations of the site and pages that don’t yet exist. Having that knowledge in a back pocket when crafting new pages, features, and updates to a site is crucial and can help you maximize your users’ happiness while avoiding pitfalls. 

Your users aren’t a monolith, of course, which is why heatmapping platforms (Osserva included) offer subscriptions at multiple price points depending on how much data you’d like to collect; for larger sites, more sessions per month may be wise to get a better picture of how the average users may behave.

LEAVE A REPLY

Please enter your comment!
Please enter your name here

Latest article