You’re racing through the course now. You’ve already learnt how to set up an experiment, how to interpret your reports and you’ve learnt how to use some of your reports to find your form’s biggest issues.
In this masterclass we will talk through two of our most powerful reports, and you’ll learn:
- How to interpret the Corrections report
- What causes users to make corrections
- How to use the Popular Dropoff report effectively
- The key causes of user drop offs
This report tells you how many corrections users are making, and in which fields they make them. A customer journey that is held up by having to make corrections is one filled with friction. You should be aiming to reduce the number of corrections a user makes as much as possible.
The main data strip shows you on average how many corrections your forms starters make, and the table underneath gives a breakdown of which fields they have to correct.
Along the top of the table, you have the following columns:
Interactions – how many key presses and clicks have users made in this field?
Refocuses – how many times has a user left this field and had to come back to it to change or input more information?
Delete – how many backspaces and deletes have users had to press in this field?
Cursors – how many times has a user pressed a cursor key in this field?
Correction % – of all the interactions that take place in this field, how many are corrections?
Health – how does this field compare to the rest of my form and others in the same industry? Health scores use a percentage and traffic light system – the lower the percentage, the more problematic it is.
So, now you can see where users are making corrections (and what type of corrections), but how do you interpret that, and what might be causing your visitors to make those errors?
- Sloppy data input (by the user)
- Unclear labels (including compulsory fields)
- Unforgiving input requirements (of your form)
- Lack of good (inline) validation and error messages
When users enter a new field, the label and any supporting text gives them the only information they have in order to complete their data entry successfully. Is your field label clear and understandable to every single user? Is there any ambiguity about what you’re asking for?
Another problem we often see in this category is when fields are not clearly indicated as optional or mandatory. Users will for the most part do as little as possible in order to successfully complete the process. If mandatory fields are not marked clearly, users may to try and skip over ones that they perceive to not be necessary to move forward. They’ll be greeted with error messages and have to spend more time than they’d like completing your form.
Unforgiving input requirements
If your form requires that information be entered in a certain way, you have to ensure that you do everything possible to let the user know this, or force them to enter it in a way that they cannot get wrong.
For example, there may be a postcode or zipcode field where a user could not enter a postcode without spaces. The result? Lots of corrections, with a 12% corrections rate in that field (meaning that 12% of all interactions in this field were correcting previously entered inputs):
If your error rate is high for one field, it may therefore be because you do not accept information in a way that many users expect to enter it. Let’s think of some of the possible permutations of the following information:
|Telephone Number||0800 772 0982(0)800 7720982(0)8007720982
+44 (0) 800 722 0192
|Date of Birth||01/01/1970, 1/1/19701/1/7001/01/70
|Card Number||1234 5678 1234 56781234567812345678|
Does your form accept all of the above as valid?
With a little bit of input from your developers, you can accept inputs in a variety of formats so your users with see less validation errors and be able to complete your form more easily.
Give clear instructions on data entry
Let users know before they start typing that data must be entered in a certain way.
Yahoo’s password field in their sign up form is a good example of this:
Force users to enter information in a particular way (that is not intrusive). Gmail asks for your date of birth, but minimises potential errors by splitting the information into a drop down for month.
Yahoo’s form does the same for day, month and year of birth:
Lack of good (inline) validation and error messages
Inline validation is a great way to highlight where users have gone wrong with entry and ensure they get it right second time. Even if you do not have inline validation, your error messages should be helpful and instructive (See how Ikea get form validation wrong).
If you only highlight errors but do not pinpoint exactly where the user has gone wrong and provide guidance, they may end up trying to enter information more than twice.
NowTVs sign up form is a good example of providing useful feedback to make sure they get it right on the second attempt:
As a user, I know instantly where I have made my error, and what I can do to correct it.
Gmail’s labels are error handling are excellent. When you focus in a field, help text appears:
And if this doesn’t do the trick, a clear error message pops up as soon as you click or tab through the form, along with a friendly and clear explanation as to where you went wrong:
These simple additions to your web form can make a huge difference, both to your drop off rates, but also to a user’s experience of your brand. An angry error message is far less welcoming than a quick pop up explaining where you went wrong, and no (or at least as few as possible) errors in the first place is even better.
Most forms represent a potential client or customer’s first interaction with your business. A ‘computer says no’ experience is not going to get your new relationship off to a good start or, more likely, any start at all.
This report is our most popular. It shows you percentage of people that start to fill out your online form but abandon the process before the end. This is hugely undesirable, as a user who starts to enter information is displaying clear intent to purchase, register or get in touch with you.
The info at the top of this report gives you an idea of the scale of the problem. A high abandonment rate means you are losing a lot of potential users before they can complete the process. The table underneath gives you insight into where and why this might be happening.
On the above table you can see the following information:
- Field name – this is customisable and also lets you know the type of field (text, drop down, password)
- Drop offs – the number of people that interacted with this field, then left your web page
- Drop off % – the number of drop offs when expressed as a proportion of form starters
- % of total drop offs – of all the drop offs that happen in this form, how many is the field responsible for?
- Health score – this compares the stats for this field with the rest of your form, your industry and our benchmarks and gives you a very quick overview of how good or bad this field’s stats are.
Let’s look at an example of a form. This isn’t real data but illustrates the type of dropoffs that occur. Imagine 400 people viewed the form in a day and 160 engaged with it.
In total, 73 people completed the form, giving a conversion rate of 5.4%. The reasons for field abandonment could be:
The effort it takes to complete the form
Long forms immediately spell a long time commitment for users which will cause abandonment from time-poor or lazy users (we’re all inherently lazy). If this is the case for your form it may be indicated by the number of users who dropped off before even starting the form. Users can also suffer from ‘form fatigue’, dropping off after answering some questions but tired of answering any more. Look for steady dropoffs throughout the formin your data.
Password fields take additional effort for the user. First they have to think of a new password that adheres to your restrictions, then type it in a field that masks the characters and finally retype if you ask them to. By changing the password field we increased conversions on our own form by 55%.
Date of birth and gender seem like marketing questions. Users are becoming savvy to this and are more reluctant to share personal details. Get more advice on how to gather marketing information without creating a negative user experience in 5 Ways to Optimise Data Collection and User Experience.
Users don’t want to give their phone number unless they see the benefit to them. In the form above it says ‘Your phone number helps us keep your account secure’ which seems like a good reason. However, in the example above, it’s not clear if phone number will be used for marketing, which could cause some users to abandon the form.
Look at the wording of your terms and conditions message – could they be better?
CAPTCHA is a common cause of hesitation and drop offs. CAPTCHA are often incompatible with assistive technology, are hard for people with low vision to read and are generally a pain for all users. Do more work on your end and save your users the hassle of completing a CAPTCHA.
Drop offs at the end of the form can occur due to lack of instant validation in the form i.e. data isn’t validated as it’s input, only once the user tries to submit it. Rather than correct errors in the form lots of users will just leave.
Checkout forms have many more elements to them such as payment processes, delivery addresses and local store lookup. They also tend to be laid out over multiple pages or in multiple sections on a single page.
Shopping cart abandonment rate statistics show that unexpected costs and being forced to create an account cause the highest number of drop offs.
Trouble entering card details
A report by VWO revealed card security worries account for an average of 16% of all abandoned shopping carts. The process of entering card details can cause stress and anxiety for users. It’s common to see long ‘time in field’ reports for card payment forms, which could indicate users haven’t got their card out and ready to copy. Shoppers on the move are under additional time pressures and are likely to feel less secure in public places and over mobile networks.
The report below shows fields in the form with the most number of corrections, many of which are related to card payments e.g. cardholder’s name (19%), card number (13%) and the first line of the cardholder’s address (10%).
Voucher codes lead shoppers away
Voucher code fields act like an alert to shoppers that there might be a voucher code available somewhere, which isn’t always the case. While they search for a code there’s a great risk of drop off; shoppers can get distracted, cause the checkout to time out or find an alternative product at a lower cost.
VWO’s report on cart abandonment says 8% of shoppers abandon their baskets if they can’t find a voucher code.
Look out for hesitation and/or drop offs around this field if you have one in your checkout. Find out about alternative ways to introduce discounts in The Perils of Voucher Codes.
Visit the blog for teardowns of real ecommerce checkouts.
We hope you benefited from finding out how in interpret two of our most powerful reports. Next time we will introduce you to A/B testing and how you can get started with your first form test.
Why A/B test?
Conversion rate optimisation is unpredictable. A design that works for Amazon won’t work for every ecommerce site. That’s why you need to listen to your own data, know your audience well and test different options when optimising your site.
Ready to start optimising? Follow our guide to designing your first form test.
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