A pricing insights feature that empowers shoppers to make smarter choices by highlighting when groceries are cheaper than average.
TIMELINE
TIMELINE
6 Weeks, Summer 2025
6 Weeks, Summer 2025
6 Weeks, Summer 2025
ROLE
ROLE
Product Design Intern
Product Design Intern
TEAM
TEAM
Grocery & Retail
Grocery & Retail
TOOLS
TOOLS
Figma, Origami, dScout
Figma, Origami, dScout
Data Accuracy & Availability
Price comparisons depend on real-time and historical data across multiple stores.
Brand Transparency
We couldn't legally show many of the brands name and logo, making it challenging to show comparison.
UI Real Estate & Density
Adding a “Low Price” or “Great Price” badge had to be visually lightweight but still noticeable.
Market Regional Differences
Insights had to scale across different marketplaces.
Constraints
User Problem
User Problem
User Problem
Consumers perceive groceries on Uber Eats as overpriced due to the lack of clear price benchmarks.
This perception creates a significant barrier to adoption and trust, even in cases where Uber Eats prices are aligned with or lower than competitors.
Constraints
Constraints
Data Accuracy & Availability
Price comparisons depend on real-time and historical data across multiple stores.
Brand Transparency
We couldn't legally show many of the brands name and logo, making it challenging to show comparison.
UI Real Estate & Density
Adding a “Low Price” or “Great Price” badge had to be visually lightweight but still noticeable.
Market Regional Differences
Insights had to scale across different marketplaces.
Solution
Surface market comparison features to help consumers confidently recognize value.
By highlighting when an item is priced lower than usual or compared to nearby stores, the feature reduces second-guessing, builds trust, and supports smarter decision-making.
Solution
Surface market comparison features to help consumers confidently recognize value.
By highlighting when an item is priced lower than usual or compared to nearby stores, the feature reduces second-guessing, builds trust, and supports smarter decision-making.
Messaging Framework
Messaging framework was the biggest challenge.
I collaborated with content design to refine terminology like Low Price and Great Price so they felt clear and trustworthy, while also helping define which pricing strategies users actually wanted to see. Through multiple rounds of testing and iteration, we created a framework that paired the right message with the right logic that users wanted to see when comparing prices.
Define
Designing for blue sky meant designing wide and then narrowing down my ideas.
At the start of this project, I was encouraged to think without constraints, to imagine all the possible ways price transparency could exist within Uber Eats. I explored everything from interactive comparison charts to contextual badges and marketplace-wide dashboards.
Define
Two price insights, two concept models and each required distinct design approaches.
Early in the process, we defined two key messaging pillars: “Low Price”, which highlighted items cheaper than nearby stores, and “Great Price”, which surfaced products priced lower than usual. While the underlying goal was the same — to build trust and drive purchases through price transparency. We realized that each message represented a different user mindset. This led us to design two distinct concepts with tailored data visualizations: one that compared across locations, and one that compared across time.
To determine where and how these insights should surface, we mapped each concept’s flow in detail, drawing out entry points, trigger moments, and contextual placements across the marketplace and product detail pages. These flows helped us define what kind of price message to show, when to prompt it, and how much detail to reveal depending on the user's level of intent.
Solution
Surface market comparison features to help consumers confidently recognize value.
By highlighting when an item is priced lower than usual or compared to nearby stores, the feature reduces second-guessing, builds trust, and supports smarter decision-making.
Messaging Framework
Messaging framework was the biggest challenge.
I collaborated with content design to refine terminology like Low Price and Great Price so they felt clear and trustworthy, while also helping define which pricing strategies users actually wanted to see. Through multiple rounds of testing and iteration, we created a framework that paired the right message with the right logic that users wanted to see when comparing prices.
Messaging Framework
Messaging framework was the biggest challenge.
I collaborated with content design to refine terminology like Low Price and Great Price so they felt clear and trustworthy, while also helping define which pricing strategies users actually wanted to see. Through multiple rounds of testing and iteration, we created a framework that paired the right message with the right logic that users wanted to see when comparing prices.
Define
Two price insights, two concept models and each required distinct design approaches.
Early in the process, we defined two key messaging pillars: “Low Price”, which highlighted items cheaper than nearby stores, and “Great Price”, which surfaced products priced lower than usual. While the underlying goal was the same — to build trust and drive purchases through price transparency. We realized that each message represented a different user mindset. This led us to design two distinct concepts with tailored data visualizations: one that compared across locations, and one that compared across time.
To determine where and how these insights should surface, we mapped each concept’s flow in detail, drawing out entry points, trigger moments, and contextual placements across the marketplace and product detail pages. These flows helped us define what kind of price message to show, when to prompt it, and how much detail to reveal depending on the user's level of intent.
Develop Concepts
Two price insights, two concept models and each required distinct design approaches.
Early in the process, we defined two key messaging pillars: “Low Price”, which highlighted items cheaper than nearby stores, and “Great Price”, which surfaced products priced lower than usual. While the underlying goal was the same — to build trust and drive purchases through price transparency. We realized that each message represented a different user mindset. This led us to design two distinct concepts with tailored data visualizations: one that compared across locations, and one that compared across time.
To determine where and how these insights should surface, we mapped each concept’s flow in detail, drawing out entry points, trigger moments, and contextual placements across the marketplace and product detail pages. These flows helped us define what kind of price message to show, when to prompt it, and how much detail to reveal depending on the user's level of intent.
Validating
Then I A/B tested these two messaging frameworks.
I tested with 8 users to understand their expectations when encountering Low Price labels. The goal was to validate the concept and refine how these insights should be framed to maximize clarity.
Goal: Whether they find the indepth insights trustworthy and what supporting info they need to feel confident in the purchase.
Insights:
Low price is better used universally to indicate both messaging framework
100% of users wanted to know which specific stores or sources the price insights were based on.
75% said historical comparison insights were repetitive or lacked meaningful details.
Only half the users found the insight untrustworthy, the other half mentioned that it wasn’t specific enough to feel meaningful.
Validating
Then I A/B tested these two messaging frameworks.
I tested with 8 users to understand their expectations when encountering Low Price labels. The goal was to validate the concept and refine how these insights should be framed to maximize clarity.
Goal: Whether they find the indepth insights trustworthy and what supporting info they need to feel confident in the purchase.
Insights:
Low price is better used universally to indicate both messaging framework.
100% of users wanted to know which specific stores or sources the price insights were based on.
75% said historical comparison insights were repetitive or lacked meaningful details.
Iterating
Users needed a faster, clearer way to compare prices at a glance.
Through multiple iterations, I used data visualization to test how different visual treatments helped users quickly scan and understand price differences. Each round of testing refined how price insights were surfaced, ultimately showing that simplified, visual cues improved user confidence and decision speed when determining if an item was a great deal.
Iterating
Users needed a faster, clearer way to compare prices at a glance.
Through multiple iterations, I used data visualization to test how different visual treatments helped users quickly scan and understand price differences. Each round of testing refined how price insights were surfaced, ultimately showing that simplified, visual cues improved user confidence and decision speed when determining if an item was a great deal.
Adding Motion
After validation, delightful UX was introduced through animations.
Subtle animations created moments of delight while staying functional. Balancing clarity with a click glance for a seamless shopping experience.
Final Design
Compare your grocery prices with other stores within your vicinity.
The final designs introduce market comparison, allowing users to see how Uber Eats grocery prices stack up against nearby stores — tackling the perception of higher costs, building trust, and encouraging more confident purchasing decisions.
Adding Motion
After validation, delightful UX was introduced through animations.
Subtle animations created moments of delight while staying functional. Balancing clarity with a click glance for a seamless shopping experience.
Reflection
Smooth Scroll
This will hide itself!
This will hide itself!
Smooth Scroll
This will hide itself!
This will hide itself!
Smooth Scroll
This will hide itself!
This will hide itself!
Final Design
Compare your grocery prices with other stores within your vicinity.
The final designs introduce market comparison, allowing users to see how Uber Eats grocery prices stack up against nearby stores — tackling the perception of higher costs, building trust, and encouraging more confident purchasing decisions.
Adding Motion
After validation, delightful UX was introduced through animations.
Subtle animations created moments of delight while staying functional. Balancing clarity with a click glance for a seamless shopping experience.
Iterating
Users needed a faster, clearer way to compare prices at a glance.
Through multiple iterations, I used data visualization to test how different visual treatments helped users quickly scan and understand price differences. Each round of testing refined how price insights were surfaced, ultimately showing that simplified, visual cues improved user confidence and decision speed when determining if an item was a great deal.
Validating
Then I A/B tested these two messaging frameworks.
I tested with 8 users to understand their expectations when encountering Low Price labels. The goal was to validate the concept and refine how these insights should be framed to maximize clarity.
Goal: Whether they find the indepth insights trustworthy and what supporting info they need to feel confident in the purchase.
Insights:
Low price is better used universally to indicate both messaging framework
100% of users wanted to know which specific stores or sources the price insights were based on.
75% said historical comparison insights were repetitive or lacked meaningful details.
Only half the users found the insight untrustworthy, the other half mentioned that it wasn’t specific enough to feel meaningful.
Final Design
Compare your grocery prices with other stores within your vicinity.
The final designs introduce market comparison, allowing users to see how Uber Eats grocery prices stack up against nearby stores — tackling the perception of higher costs, building trust, and encouraging more confident purchasing decisions.
Reflection
Access Required
Due to NDA, I can only share a high-level overview of my work at Uber. This project is intended solely for professional viewing.
To request access, please email queenie2000824@gmail.com
Access Required
Due to NDA, I can only share a high-level overview of my work at Uber. This project is intended solely for professional viewing.
To request access, please email queenie2000824@gmail.com
Access Required
Due to NDA, I can only share a high-level overview of my work at Uber. This project is intended solely for professional viewing.
To request access, please email queenie2000824@gmail.com
Discover
Designing for blue sky meant designing wide and then narrow down my ideas.
At the start of this project, I was encouraged to think without constraints , to imagine all the possible ways price transparency could exist within Uber Eats. I explored everything from interactive comparison charts to contextual badges and marketplace-wide dashboards.
Discover
Designing for blue sky meant designing wide and then narrow down my ideas.
At the start of this project, I was encouraged to think without constraints , to imagine all the possible ways price transparency could exist within Uber Eats. I explored everything from interactive comparison charts to contextual badges and marketplace-wide dashboards.