Fracture

Single Print Photo Customizer

Overview

Challenge & Opportunity

01. Overview

Fracture is a wall decor company that prints custom photos and art directly on glass.

Fracture aimed to grow by targeting a new user segment, but these users were not converting. I was brought on to help solve this. In this case study, I detail how I overcame product strategy disagreements, bandwidth constraints, and research blind spots to arrive at the final solution which increased new customer conversion rate by 4%.

Role

Solo Product Designer (In House)

Team

1 product manager • 5 Developers

UX Methods

Stakeholder Interviews • Data Analysis • User Testing • A/B Testing • Design Workshops • Competitive Analysis • Wireframing

Industry

E-Commerce

Product Type

Website

Year

Launched 2025

02. Challenge & Opportunity

The goal was to grow but new users weren’t converting. Based on the data our Single Print Photo Customizer was the biggest area of opportunity.

The Single Print Photo Customizer was a multi-step process that helped users create a custom glass print.

Recently, the flow went through a redesign. At the time we were re-platforming and rebranding. This created an opportunity to add new features to the first step of the funnel (The product display page - PDP for short). Despite my push for a gradual rollout, the business was prioritizing speed, so we decided to implement everything all at once. Unfortunately, this negatively impacted conversion.

Hypothesis: The changes led to two key problems.

Users thought price was too high.

Users thought price was too high.

There was an increase of cognitive load at the top of the funnel.

There was an increase of cognitive load at the top of the funnel.

03. Discovery

Initially, the project scope was vague. I organized meetings with cross-functional teams to set expectations, and define both the project and research scope.

These conversations gave me hypotheses from various teams. This helped shape my research goals, questions, and blind spots, which in turn informed my research plan.

Research Plan

Reviewed past qualitative and quantitative data

Reviewed past qualitative and quantitative data

Unmoderated usability test

Unmoderated usability test

A/B Test

A/B Test

My research revealed the following:

The biggest drop-off occurred on the product display page (PDP).
About ⅔ of customers didn’t scroll past pricing
Participants found the customizer was generally easy to use
A big selling point for our product is it’s quality.

The biggest drop-off occurred on the product display page (PDP).
About ⅔ of customers didn’t scroll past pricing
Participants found the customizer was generally easy to use
A big selling point for our product is it’s quality.

Based on my findings, we narrowed the hypotheses to two.

04. Defining Success

A divide emerged over the problem and area of opportunity. Marketing still believed that new customers preferred buying multiple prints, not just one.

Marketing felt that our current experience for buying multiple prints wasn’t intuitive. They wanted to focus on a product called gallery walls (above) because their belief was that new customers preferred buying multiple prints, not just one. This was the opposite of what I found in my research.

To resolve the misalignment, I facilitated a design thinking workshop where we defined success and gained a better understanding of each other's views on Gallery Walls.

Definition for Success (KPIs)

Increase in new customer conversion rate

Increase in new customer conversion rate

Flat or increase in revenue per visitor

Flat or increase in revenue per visitor

Argument for Gallery Walls

In marketing channels, ads with gallery walls outperformed ads with just single prints.

Argument Against Gallery Walls

There was a high onsite bounce rate and abandonment rate for gallery wall products.

We agreed that we should prioritize the Single Print Photo Customizer over Gallery Walls. But there was still a misalignment on the core problem and the solution.

Marketings Theory
Marketing believed that the number of steps in the flow was a problem. However, this was would be a huge lift and it was not backed by any data.
Products Theory
Product believed that we should focus on removing distractions at the top of the funnel.

Marketings Theory
Marketing believed that the number of steps in the flow was a problem. However, this was would be a huge lift and it was not backed by any data.
Products Theory
Product believed that we should focus on removing distractions at the top of the funnel.

05. Defining The Problem

To test each team’s hypothesis, I ran an unmoderated balance comparison of two competitors.

Due to limited bandwidth, I couldn’t prototype both team’s ideal flows. So I ran an unmoderated comparison test on competitor flows similar to the ones we aimed to emulate.

Frameology
Like Marketing’s concept, Frameology used a one step customizer where users uploaded a photo and chose product options on a single page.
Framebridge
Framebridge’s multi-step flow, with fewer upfront options, was closer to what Product aimed to implement.

Frameology
Like Marketing’s concept, Frameology used a one step customizer where users uploaded a photo and chose product options on a single page.
Framebridge
Framebridge’s multi-step flow, with fewer upfront options, was closer to what Product aimed to implement.

I learned users didn’t mind the number of steps. What they really cared about was price, quality, and being able to easily visualize the product in their space. These insights highlighted two key issues with our flow.

Problem #1: Users believed our price point was too high.
Data confirmed pricing was crucial to new users and likely effecting their experience. This reinforced my belief that the add-ons were negatively impacting conversion rate.
Problem #2: Users struggled to visualize their photo and the product in real life.
Most test participants felt more confident after seeing their uploaded image in the product. This is something our flow delays until the end, with many distractions beforehand.

Problem #1: Users believed our price point was too high.
Data confirmed pricing was crucial to new users and likely effecting their experience. This reinforced my belief that the add-ons were negatively impacting conversion rate.
Problem #2: Users struggled to visualize their photo and the product in real life.
Most test participants felt more confident after seeing their uploaded image in the product. This is something our flow delays until the end, with many distractions beforehand.

06. Design

Research showed both solutions were worth testing, but for reasons different from each team’s original thinking.

Removing add-ons
Removing add-ons from the top of the funnel would reduce distractions. This would help users get to the final step (where they see their uploaded image with their selected add ons) faster.
One Page Customizer
Changing from a multi-page approach to a one page approach would help users see their uploaded image with their selected add ons faster.

Removing add-ons
Removing add-ons from the top of the funnel would reduce distractions. This would help users get to the final step (where they see their uploaded image with their selected add ons) faster.
One Page Customizer
Changing from a multi-page approach to a one page approach would help users see their uploaded image with their selected add ons faster.

07. Testing & Results

Due to the complexity to design and build the one page customizer, we’d have to wait to test it. In the meantime, we created and executed a multi-round A/B testing plan.

Test 1 - Cognitive Load Test
Hypothesis: Removing top-of-funnel distractions (like add-ons) increases the likelihood that users will move forward and convert.
Result: Control won. Something to note is that more people got through the funnel but dropped at cart.
Insight: The issue was probably not cognitive load. It was price.
Test 2 - Effects of Frames
Hypothesis: Users aren’t converting due to price. Removing frames (the most expensive add-on) can reduce intimidation and increase likelihood to purchase.
Result: The “No frames” variant won. Average order value dropped, but the increase in conversion rate helped push the “no frames” variant to victory.
Insight: Our product was too expensive, and frames made it worse.
Test 3 - Multi-step vs. One Step
Hypothesis: Users wanted to see their photo in the product. By moving this feature from the end to the top of the funnel, it will give them more confidence quicker. Which in turn, will increase the likelihood that they will convert.
Result: One page customizer variant won. There was a 4% increase in new customer conversion rate.
Insight: Users wanted to see their photo in the print as quick as possible.

By removing frames from the entire flow and switching to a one page single print photo customizer, we were able to increase new customer conversion rate by 4%.

08. Looking Forward

If I were to continue trying to improve new customer conversion rate, I’d focus on the following opportunities:

Customer Photos
New users want to see how our product looks in real life. Secondary studies show users find brand images too stylized; real customer photos can offer a more authentic view.
3D Model
New users want to see how our product looks in real life. A 3D model they can interact with offers a better sense of the product’s appearance.
Augmented Reality (AR)
New users want to visualize our product in real settings. AR lets them visualize their customized product in their space.

Customer Photos
New users want to see how our product looks in real life. Secondary studies show users find brand images too stylized; real customer photos can offer a more authentic view.
3D Model
New users want to see how our product looks in real life. A 3D model they can interact with offers a better sense of the product’s appearance.
Augmented Reality (AR)
New users want to visualize our product in real settings. AR lets them visualize their customized product in their space.

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Fracture

Single Print Photo Customizer