Unlocking 25% More Conversions with In-App Gift Card Redemptions
Re-designing the browsing and checkout experience for Gift Cards to drive a meaningful lift in conversions
Re-designing the browsing and checkout experience for Gift Cards to drive a meaningful lift in conversions
AIR MILES is one of Canada's largest loyalty rewards programs, helping millions of collectors earn and redeem Miles on everyday purchases. Users couldn't complete a Gift Card redemption in the AIR MILES app. After navigating to the Gift Card listing screen, they were redirected to the website to view the product details page and checkout. This created friction in the experience and was a barrier to redemptions. As the sole UX designer on the project, I worked closely with product and engineering to re-design the experience e UX design effort to bring the full browsing and checkout experience into the app, removing friction and driving conversions.
The AIR MILES app offered limited eVoucher browsing and no way to complete a redemption. Beyond the eVoucher listing screen, collectors were redirected to the AIR MILES website to view eVoucher details and complete a purchase. My product partner and I took a multi-faceted discovery approach to deeply understand the Rewards space, and uncovered three core pain points:
Too many steps and redirects caused drop-off before completing a redemption.
Collectors couldn’t easily find rewards that matched their interests or Miles balance.
Collectors weren’t sure what their Miles were worth or what they could get.
Despite being redirected to the website to complete their redemption, collectors coming from the app made up nearly half of all conversions. These were already engaged collectors — they had downloaded the app, were actively browsing rewards, and were motivated enough to push through the friction of being redirected to web. Removing that friction represented a clear opportunity to increase conversion rates among the most engaged segment of the user base.
The original product listing page offered limited support for browsing and surfaced very little information about the eVouchers themselves. Key details such as the minimum Miles required to redeem, whether an eVoucher was on promotion, or what denominations were available were hidden behind an extra click. Collectors had no quick way to know which rewards were actually within reach based on their Miles balance.
To improve the browsing experience, I redesigned the eVoucher cards to surface high-value information upfront, including "new" and "promotion" badges and a clear "starting at" Miles amount. Market research showed that ~50% of redemptions are spontaneous, so I introduced a quick filter that instantly surfaced rewards collectors could redeem with their current Miles balance.
My hypothesis was that making this information visible directly on the listing page would reduce friction, decrease drop-off, and ultimately drive more redemptions.
Based on web analytics, the click-through rate for product detail page views was significantly higher when a user filtered on the product listing page. This led to the assumption that adding filters to the PLP in-app would increase click-through rates and ultimately conversions.
I referenced Baymard Institute's UX guidelines for e-commerce filtering to validate which filters to include, how to group them, and how to present default and disabled states for scannability.
I defined filters for Miles range, brand, category, and denomination. Filters are interdependent: selecting an option in one dynamically updates the others to avoid dead ends. Disabled options remain visible with a count of "0", and enabled options are prioritized and sorted alphabetically.
I used AI (Co-pilot) to help flush out edge cases — including empty states, dynamic filter dependencies, and what happens when valid options scroll out of view. This accelerated the design process and helped me catch scenarios I might have otherwise missed.
Edge case: User interacts with the "within my balance" filter and searches for an eVoucher
The handoff documentation captured default states, interaction logic across search, sort and filter (including edge cases), dynamic behaviour and interdependencies, and visual examples. This served as a single source of truth for design and engineering, reducing ambiguity and ensuring consistent implementation.
I ran structured feedback sessions where participants navigated a prototype and provided structured feedback. Key findings confirmed that participants appreciated the "Within my balance" filter, and seeing the percentage saved on product cards influenced which cards they clicked on first.
The new redemption flow is currently in phased development, rolling out incrementally to reduce risk and accelerate time to production.
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