Reduce abandonment, increase conversions and improve UX.
Ensure you are using an analytics platform like Zuko Analytics that gathers data at the form field level.
Software platforms with this feature allow you to break out the data for each form field as well as analyzing form conversion as a whole.
Abandonment data on a field means that it was the last field the user interacted with before leaving the form. The fields with the highest volumes of abandonment will give you an idea of where the largest opportunities for improvement are. They might not be the fields with the biggest problems, though.
Abandonment rate is calculated by number of abandonments on a field / number of sessions that interacted with that field. It is often more reflective of issues than the absolute number of abandonments. Fields with lower volumes of interactions could have a high proportion of dropouts.
A field return is when a user fills in a form but then comes back later to correct it. A high proportion of field returns might indicate an issue with the field’s usability, which is affecting the user experience.
When users are spending a lot of time trying to complete a particular field it may be causing them frustration.
High field returns or time taken might indicate a problem field but not necessarily - some fields naturally require a lot of involvement. To decide whether there’s an issue, look at the difference in returns or time taken between abandoned and completed sessions. If abandoned sessions have a significantly higher figure, it is a clear indication that the field is causing users friction.
For example, Gross income shows a discrepancy in the data between abandoned and completed sessions:
If users have tried to submit but haven’t successfully completed the form, there is likely to be an issue somewhere in the form. The fields users interact with immediately after attempting to submit are likely to be the ones causing the friction.
Analyze which error messages are being shown most frequently and whether they correlate with abandonment.
A large proportion of errors associated with a field implies that it is causing problems to your users.
Collate your list of problem fields and use it to create hypotheses about what is causing abandonment.
- Now you have your list, look at your form with your users’ eyes and create theories of what is causing them to abandon at this point.
- Test your hypotheses by making changes and analyzing the effects on abandonment and conversion.