Rebates : Instant Point Back
Product Designer (UI/UX) & Product Manager | App & Web
Objective & Result
Specific, Measurable, Achievable, Relevant and Time-bound.
To improve the post-purchase experience at Rakuten Rebates Japan, I led an initiative to reduce confusion around point tracking by introducing timely confirmation messages and educational content. Using newly built backend purchase detection signals, I collaborated with frontend and email teams to deliver updates in-app and via email. The goal was to reduce “Where is my point back?” inquiries by at least 30% among top 10 merchants, aligned with reducing CS workload and improving retention.
We launched the updates within a 2-month window ahead of the Q3 Super Sale and saw a 50% drop in related inquiries after rollout.
Overview
Rakuten Rebates is a Point Back platform in Japan that rewards users with Rakuten Points when they shop online through affiliated stores.
Before this project, and due to how the system was set up, a user may have to wait several days or up to two month before they are notified that they have received points from a purchase.
Down the line, this ends up impacting the customer service team during high volume campaigns like the quarterly Super Sale, and costing money (in the form of points) to keep customer satisfaction from dtopping.
Understanding the Problem
The highest inquiry reported to the Customer Service team is the “Where is my point back” form. This issue is also highlighted in App reviews with lower ratings of 1 to 3 stars. The core of this issue is in the Rebates backend code that controls how and when Rakuten Points are awarded to a user’s account. Due to technical difficulties, this process can take up to 2 months, which is too long of a wait and tends to feel like a bait and switch to most new members trying the service for the first time.
Hypothesis
If we know when a purchase was made at a store and the amount spent, we can predict the estimated reward and send a notification on the spot.
Finding a Solution
Rebates offers deals at 900+ merchants spanning across several categories,
(Products, Travel, Experiences, Rental…)
My solution needed to be
Scalable by design – The solution needed to cover as many of the 900+ merchants as possible to make a meaningful impact.
Low maintenance – Avoid one-off fixes. One change should apply across many merchants without duplicating effort.
Flexible content – Text and messaging must be dynamic and editable without hardcoding, to allow fast updates if issues arise.
Future-proof – The system should scale smoothly as more merchants and categories are added.
Strategic add-ons – I often pair big projects with low-effort improvements like onboarding tips or tutorials to expand reach and catch related issues early.
I use a mix of UX worksheets for initial ideation, such as: Mind Mapping, Crazy Eight, Problem Statement & User Stories…
Looking at the Data
I noticed that the top 10 merchants made up over 75% of all product purchases.
With that in mind, I started narrowing down my solutions to those that would make the biggest impact based on this data.
Phase 1
Improve store purchase tracking for top 10 merchants.
(no user facing impact)
Phase 2
User facing improvements for messaging about confirmed purchases.
Phase 3
Enhance user experience and expand tracking to more merchants.
Phase 1
I worked with a US based backend team to use our in-app shopping experience to scrape checkout cart and confirmation screen data in order to predict successful purchases made by users.
I also worked with our Business Indulgence (data) team to set up a flag if any of our scripts failed or reported a value that was different from the Point Reward officially granted by the merchant later in the process.
This phase was purely on the backend with no user facing changes. My goal was to prove that we can accurately predict when a user made an eligible purchase resulting in point back reward.
I was able to get the first 10 stores working, bug free, within 2 weeks.
Phase 2
For the second phase, I started to roll out user facing improvements such as:
A confirmation email once a purchase was detected (predicted)
Better messaging in My Account with info about the purchase detection and information about point earning schedules
Improving the “Where is my point back” inquiry form to include educational content about point earning
Old Monthly Email
New Monthly Email
Order Detected Email
Confirmation Email
Phase 3
The initial implementation was done on the Rebates Mobile App. The app features an in-app browser which allows us to keep track of the user when they shop at a merchant’s website.
Expand the reach of Instant Point Back to Web users
Add educational content on the Merchant page on Rebates website with reward time estimates for each merchant
Add a prominent link to point reward educational content to large promotional campaigns such as the Super Sale
Due to the nature of web browsers, Rebates loses track of a user after they click an affiliate link, making it impossible for us to know if the user has made a purchase or not (at least until the merchant notifies us).
To over come this obstacle, I negotiated with the Rebates extension team to introduce this feature to allow us to bring this experience to our web users.
The chrome extension is build and managed by a separate dev team from the one I normally work with. Though our conversations, I learned that their main KPI is new user adoption. So i proposed we advertise this feature as a perk for downloading the extension.
“Get instant point back reports when you use our Rebates extension!”
This idea got them on board 👍🏻
Old Logged-out PC Experience
New Logged-out PC Experience
“Where is my point back” inquiries were reduced by 50% for the top 10 merchants.
Unexpected Issue
Since the experience was not consistent across all merchants, some users assumed there is an issue when they did not receive an “order detected” email.
This was seen as an acceptable side-effect, and the CS team was able to handle it on a case by case basis.
Over time, we ramped up the number of supported stores for this feature to cover 90% of all product purchases.