Form Optimization Case Study

Ecommerce Checkout

Company: Major UK Online Retailer (Anonymous)

Sector: Ecommerce / Retail

Country: UK

Results: £2.725 million in projected additional revenue following checkout optimisations informed by Zuko

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"The biggest test win of my career came from form analytics."
Abi Hough, UX & Experimentation Specialist

The Challenge

A major UK retailer was losing 41% of customers at the very first stage of its checkout, where shoppers were required to enter their personal details and create an account.

Despite attracting significant traffic, too many potential customers were failing to complete their purchases. The problem was particularly acute on mobile, where abandonment reached 42.9%.

Traditional web analytics showed where customers were dropping out, but couldn't explain why.

The retailer needed to understand exactly which elements of its checkout were frustrating customers, identify opportunities to remove unnecessary friction and turn more existing visitors into paying customers.

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The Solution

Using Zuko Analytics alongside usability research, the optimisation team uncovered specific problems within the checkout that conventional analytics had missed.

Zuko's field-level data highlighted where customers were abandoning, correcting their entries and struggling with individual questions. Three particularly valuable opportunities emerged:

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1. An unnecessary field causing abandonment

Zuko revealed that a dropdown asking how many months customers had lived at their current address accounted for 17.6% of recorded field drop-off events.

Further investigation showed that customers frequently missed the question and encountered validation errors. The most commonly submitted answer was zero.

Rather than simply redesigning the field, the team challenged whether it was needed at all. Following consultation with stakeholders, the visible dropdown was removed and a default value submitted behind the scenes.

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2. An email field creating a dead end

Zuko identified that email address and confirmation fields accounted for 26.4% of recorded field corrections.

Further research revealed that existing customers were encountering account-related problems late in registration, often after completing much of the form, without sufficiently clear guidance on how to proceed.

The solution was to move email entry to the beginning of the journey and introduce earlier inline validation, allowing returning customers to be identified before wasting time completing unnecessary fields.

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3. An address lookup customers couldn't find

Usability research revealed that customers were regularly overlooking the postcode lookup button and manually entering their full addresses instead.

The checkout was redesigned to show only the house number and postcode initially, revealing additional address fields when required.

This simplified the experience and reduced the amount of information customers were confronted with.

These changes formed part of a wider checkout optimisation programme that also improved field grouping, validation guidance, password interactions and the overall clarity of the journey.

Crucially, Zuko provided the quantitative evidence to identify and prioritise the friction points, while user research helped explain the behaviour and A/B testing validated the improvements.

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The Results

The optimisation programme delivered substantial commercial improvements across two successive iterations.

The first experiment generated a 2.9% uplift in overall conversion, as reported by Google Analytics, equivalent to approximately £2.32 million in projected additional annual revenue.

Rather than stopping there, the team continued analysing the checkout and testing further improvements. A subsequent iteration generated an additional £405,000 in projected annual revenue.

Together, the two iterations represented:

  • £2.725 million in combined projected additional annual revenue.
  • +2.9% overall conversion uplift in the first experiment.
  • +5.0% mobile conversion uplift in the first experiment.
  • Further conversion gains through continued optimisation.

Revenue figures are annualised projections based on historical experiment results, rather than revenue already realised.

You can read more on this checkout case study in this more detailed blog article.

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