Pay Monthly Optimization
Design efforts aimed at optimizing Pay Monthly’s initial release experience based on KPIs.
Lead UX Designer
Role
Figma, Miro
Tools
4 weeks
Timeline
Design Thinking
Methodology
Design Thinking
Project Summary
Product and UED initiatives aimed at optimizing and growing Pay Monthly acquisition experience based on the data obtained post-launch. The process involved analyzing metrics, forming hypotheses and creating design variants to test with users to help prove or disprove the hypotheses.
Product Recap
Pay Monthly a suite of deferred payment offers globally. It’s a closed-ended, interest bearing loan product that gives buyers the opportunity to finance larger purchases by spreading their payments between 6-24 months with an APR between 10-30%.
Problem Space
Based on the metrics and KPIs obtained post-launch, it became evident that certain parts of the Pay Monthly experience have a drop off rate higher than average. It was our responsibility to understand the possible reasons and address the issues by testing various design solutions.
Goals
The customer goal: design a more straightforward, simplified, robust experience to be as inclusive as possible – building confidence for first-timer or inexperienced buyers.The business goal: increase Pay Monthly TPV, number of loans and FTUs (first-time users).
Pre-Optimization: Acquisition Flow
Status quo Pay Monthly acquisition experience before any experiments & design changes.
Pre-Optimization: Servicing Flow
Status quo Pay Monthly servicing experience before any experiments & design changes.
Metrics
Data captured at 95% ramp.
Hypotheses & Solutions
Understanding all the “whys” by analyzing the data to translate customers’ possible challenges into opportunities for design.
Experiments
Testing optimization designs with users, gathering data & comparing metrics of control vs test variant groups.
Test #1: Splash Screen
HYPOTHESIS:
There is currently no product info page before the start of the Pay Monthly application that gives users insight into the product and its benefits. This can lead to users not feeling comfortable moving ahead with the application since they don’t have a complete understanding of the product terms. Adding a splash page before the application similar to Pay in 4, could help improve the user experience and the application conversion rate.
US FTU Projection vs. Results Analysis
Projected
(Based on 30 days: 9/01/22 – 9/30/22)
• $0.3M incremental TPV per month
• ~450 incremental loans per month
Actuals
(Based on 27 days: 12/16/22 – 01/11/23)
• $0.5M incremental TPV per month
• ~500 incremental loans per month
Test #2: RYI Split
HYPOTHESIS:
Customers might feel intimidated or not safe to be requested to provide a great amount of personal information right away on one page: phone number, DOB, SSN, annual income.
We want to test breaking down the ‘Review your info’ page into 2 parts in order to make the form feel less intimidating and to add more info on the pages about the product terms and details.
US FTU Projection vs. Results Analysis
Projected
(Based on 31 days: 6/15/22 – 7/15/22)
• $0.4M incremental Pay Monthly TPV per month
• 0.8K incremental Pay Monthly loans per month
Actuals
(Based on 9 days: 11/3/22 – 11/11/22 data)
• $3.9M incremental Pay Monthly TPV per month
• 12K incremental Pay Monthly loans per month
Test #3: Offers Page
HYPOTHESIS:
Customers might feel indecisive when being presented with installment options and, as a result, questioning whether it’s worth it. The reasons for doubts could be APRs higher than expected, lack of info regarding fees, credit check. We want to test updated language for the headings and subheadings on the offer selection page to provide more info on product benefits.
US FTU Projection vs. Results Analysis
Projected
(Based on 31 days: 6/15/22 – 7/15/22)
• $80K incremental TPV per month
• ~140 incremental loans per month
Actuals
(Based on 20 days: 10/21/22 – 11/09/22)
• $40K incremental TPV per month
• ~160 incremental loans per month
Test #4: Decline
HYPOTHESIS:
Customers who have been declined a Pay Monthly loan might feel frustrated, and therefore demotivated to return to checkout and pay full amount using a saved card. It feels like a dead end in the experience, thus customers just drop off on the decline page.
We want to test downselling Pay in 4 tp pre-approved customers, – another Pay Later product, which isn’t interest-bearing.
Fast Follows
Optimized designs that were implemented as a fast follow based on the feedback from the legal compliance team in order to provide customers with more clarity & transparency.
Set Up Autopay
DESIGN CHANGE:
Adding monthly payment amount + autopay start date the set Up Autopay page in the acquisition experience.
Document Repository
DESIGN CHANGE
Adding a new feature to the servicing – the document repository which contains all the disclosures & consents that customers have previously agreed to during acquisition. These documents are available for review & download tapping the ‘download documents’ link. Previously, this link labeled as ‘download document’ would open the loan agreement only.
Success & Impact 🚀
+$7.8M TPV/mo.
Split Review Info
+$1M TPV/mo.
Splash Page
+$0.8M TPV/mo.
Offer Selection
Learnings & Takeaways
Split Review Info Page
While we expected a maximum of 5% lift in personal info submission rate, this test far exceeded that with statistically significant lift in not only submission rate, but also risk approval rate, thus indicating that we underestimated the number of people (particularly those with higher FICO scores) that found the single page application cluttered and intimidating.
Offers Page
While T3 showed a lift similar to expectations, the impact did not continue through to the end of the funnel, whereas T1 showed an overall 1.7% lift in loans.