Reducing Friction in Checkout Flow

Overview

The checkout experience is a critical conversion point, but it showed clear signs of friction and user abandonment primarily from the first step alone with the highest drop-off. The existing flow combined multiple inputs increasing cognitive load and the likelihood of abandonment.

The Challenge

The checkout redesign needed to support a range of constraints, including existing backend limitations with order management system, multiple delivery scenarios, and planned product expansions, while also addressing known usability issues and bugs. I had to improve usability and reduce friction within a complex system without the redesign breaking critical functionality.

Opportunities & Goals

1. Confusing and convoluted delivery selection process. Opportunity for the system to pre-select best method for the customer based on behavioral data.
2. Reduce checkout abandonment by simplifying decision-making at each step.
3. Improve form completion rates through clearer structure and validation feedback.
4. Create a scalable checkout structure that supports future product and delivery scenarios.
   

PROBLEM TO SOLVE

Customers entering checkout experiences friction immediately, driven by dense form inputs, premature error feedback, and decision-fatigue resulting in ~64% user abandonment during the first step.

RESEARCH & DISCOVERY

Gathering Insights

Given that Homemakers operates in the furniture industry, longer consideration cycles and higher hesitation during checkout are expected due to the larger purchase value.

However, the level of early drop-off suggested that user behavior alone did not account for the loss, pointing to underlying usability issues within the experience.

KEY INSIGHT

Early Friction = Abandonment

Majority of the drop-offs occurred at the first step of the checkout, indicating usability issues and friction rather than intentional exit.

KEY INSIGHT

Complexity

Grouping multiple decisions into the first step increased cognitive load and made it harder for users to progress which was a direct contributor to early abandonment.

KEY INSIGHT

Error Handling Disrupted Confidence

Premature validation and errors introduced friction before users could successfully complete inputs.

HOW MIGHT WE

How might we reduce early checkout friction and improve completion rate by simplifying decision-making?

IDEATION & ITERATION

Using Insights to Drive Decisions

While reducing the number of steps is often seen as best practice, the existing checkout showed that combining too many decisions into a single step increased friction and led to early drop-off. Instead, I explored how breaking the experience into more focused steps could improve clarity and progression.

These explorations led to three key design decisions that shaped the final experience.

Early Friction Avoided

I simplified the entry point of checkout and prioritized clarity in the first step to reduce immediate drop-off. I accomplished this by updating the desktop layout of the form's input fields as a single column that's easy to understand.

I also aimed to include Apple Pay and Google Pay express checkout as part of the new experience. However, these flows ultimately fell short of expectations and weren't tested to the same depth as the core checkout. These are flows I will prioritize as a separate release rather than as an extension of the main redesign.

Creating an Additional Step

I split shipping and delivery into separate steps to reduce the cognitive load of the first step. This allows the user to focus on one decision at a time, and it also removed an error shown on the first step to enter shipping address information before seeing available delivery methods.

Reduced User Effort With Recommended Delivery Automation

Many positive improvements were made to the delivery selection process during the checkout redesign. Previously, users were required to select a delivery method for each item in their cart, creating unnecessary friction and increasing task completion time. Because delivery method was part of the first step initially, users had a long form plus a long delivery selection process.

After the redesign, items were grouped into a single shipment based on delivery date, and the most commonly selected delivery option amongst all customers was pre- selected using behavioral analytics and historical user data. This reduced repetitive decision-making and streamlined the checkout flow.

Working Towards a Scalable Catalog

The checkout was also redesigned with future catalog expansion in mind, ensuring it could support a growing mix of fulfillment types and vendors.

Building on the delivery grouping and automation work, the system was structured to accommodate grouping shipments by delivery date, vendor, and fulfillment type from owned inventory or D2C which may only have one delivery method available.

FINAL DESIGN

Check Out This Improved Flow

IMPACT

The Results

+16.7%

increase in end-to-end funnel conversion rate from 22.7% to 26.5% following the first few weeks compared to 30 days before the change

+15.6%

increase in users that are reaching the delivery step from 36% to 41.6% following the first few weeks compared to 30 days before the change

-4.9%

decrease in end-to-end funnel abandonment from 77.3% to 73.5% following the first few weeks compared to 30 days before the change

+8

operational hours per week customer service saves rather than recreating failed orders

What I Learned From This Project

A

A

A

A

What I'd Do Differently

I aimed to include Apple Pay and Google Pay express checkout as part of the new experience. However, these flows ultimately fell short of expectations and weren't tested to the same depth as the core checkout. Looking back, I would have prioritized these flows as a separate release rather than as an extension of the main redesign.

hello@noahheuton.com

(515) 446-8161

LinkedIn

© 2026 Noah Heuton