Starbucks
Starbucks
Starbucks
Redesigning the rewards app for 30 million customers to encourage them to explore new drinks
Redesigning the rewards app for 30 million customers to encourage them to explore new drinks
Redesigning the rewards app for 30 million customers to encourage them to explore new drinks
For
For
For
Starbucks UX
Research Team
Starbucks UX
Research Team
Starbucks UX
Research Team
Timeline
Timeline
Timeline
August - December 2023
August - December 2023
August - December 2023
Role
Role
Role
Product Designer
Product Designer
Product Designer
User Researcher
User Researcher
User Researcher
Team
Team
Team
Gabriela Buraglia
Gabriela Buraglia
Gabriela Buraglia
Ariana Olalde Keller
Ariana Olalde Keller
Ariana Olalde Keller
Rajath Pai
Rajath Pai
Rajath Pai
Aastha Patel
Aastha Patel
Aastha Patel
Tools
Tools
Tools
Figma
Figma
Figma
Miro
Miro
Miro
Qualtrics
Qualtrics
Qualtrics
Paper Prototyping
Paper Prototyping
Paper Prototyping
problem space
problem space
problem space
According to our point of contact at Starbucks, most existing customers have a routine order that they do not stray from.
According to our point of contact at Starbucks, most existing customers have a routine order that they do not stray from.
According to our point of contact at Starbucks, most existing customers have a routine order that they do not stray from.
Moreover, our independent research indicates that seasonal spikes in popular items like the Pumpkin Spice Latte have diminished in recent years due to market saturation, making it crucial for Starbucks to explore new ways to engage customers.
Moreover, our independent research indicates that seasonal spikes in popular items like the Pumpkin Spice Latte have diminished in recent years due to market saturation, making it crucial for Starbucks to explore new ways to engage customers.
Moreover, our independent research indicates that seasonal spikes in popular items like the Pumpkin Spice Latte have diminished in recent years due to market saturation, making it crucial for Starbucks to explore new ways to engage customers.
Encouraging customers to try new drinks could also make each visit more exciting and enjoyable. For Starbucks, this strategy could boost customer engagement and satisfaction, particularly if the recommended drinks become new favorites among customers. Additionally, leveraging the visibility of featured items and addressing usability issues in the app could further enhance the customer experience and drive exploration.
Encouraging customers to try new drinks could also make each visit more exciting and enjoyable. For Starbucks, this strategy could boost customer engagement and satisfaction, particularly if the recommended drinks become new favorites among customers. Additionally, leveraging the visibility of featured items and addressing usability issues in the app could further enhance the customer experience and drive exploration.
Encouraging customers to try new drinks could also make each visit more exciting and enjoyable. For Starbucks, this strategy could boost customer engagement and satisfaction, particularly if the recommended drinks become new favorites among customers. Additionally, leveraging the visibility of featured items and addressing usability issues in the app could further enhance the customer experience and drive exploration.
How might we use the rewards program to encourage customers to try new drinks?
How might we use the rewards program to encourage customers to try new drinks?
How might we use the rewards program to encourage customers to try new drinks?
Our Solution
Our Solution
Our Solution
We created the Drink Map, a feature in the Starbucks app that showcases trending drinks and customizations at each location, helping customers discover new favorites whether they're at home or on the go. Additionally, the Drink Map offers customers the chance to earn bonus Stars (loyalty points) for trying these popular new drinks.
We created the Drink Map, a feature in the Starbucks app that showcases trending drinks and customizations at each location, helping customers discover new favorites whether they're at home or on the go. Additionally, the Drink Map offers customers the chance to earn bonus Stars (loyalty points) for trying these popular new drinks.
We created the Drink Map, a feature in the Starbucks app that showcases trending drinks and customizations at each location, helping customers discover new favorites whether they're at home or on the go. Additionally, the Drink Map offers customers the chance to earn bonus Stars (loyalty points) for trying these popular new drinks.
The Drink Map offers these key capabilities:
The Drink Map offers these key capabilities:
The Drink Map offers these key capabilities:
Multiple Access Points
Multiple Access Points
Multiple Access Points
Customers can seamlessly explore trending drinks from the Home or Order screens, integrating discovery into their ordering experience.
Customers can seamlessly explore trending drinks from the Home or Order screens, integrating discovery into their ordering experience.
Customers can seamlessly explore trending drinks from the Home or Order screens, integrating discovery into their ordering experience.
Exploration of Nearby Locations
Exploration of Nearby Locations
Exploration of Nearby Locations
The ability to pan the map lets customers discover trending drinks at nearby Starbucks locations, useful when in new or unfamiliar areas.
The ability to pan the map lets customers discover trending drinks at nearby Starbucks locations, useful when in new or unfamiliar areas.
The ability to pan the map lets customers discover trending drinks at nearby Starbucks locations, useful when in new or unfamiliar areas.
Visualization of Location-Based Stats
Visualization of Location-Based Stats
Visualization of Location-Based Stats
Trending drinks and the number of recent orders are displayed to provide transparency and help customers make informed choices based on popular trends.
Trending drinks and the number of recent orders are displayed to provide transparency and help customers make informed choices based on popular trends.
Trending drinks and the number of recent orders are displayed to provide transparency and help customers make informed choices based on popular trends.
Highlighted Customizations
Highlighted Customizations
Highlighted Customizations
Customizations are highlighted with a bold outline, making it easier for customers to replicate trending drinks, especially those popular on social media.
Customizations are highlighted with a bold outline, making it easier for customers to replicate trending drinks, especially those popular on social media.
Customizations are highlighted with a bold outline, making it easier for customers to replicate trending drinks, especially those popular on social media.
Order Reassurance
Order Reassurance
Order Reassurance
The reminder of Starbucks’ Barista Promise reassures customers that they can try new drinks risk-free, reducing hesitation to experiment with new orders.
The reminder of Starbucks’ Barista Promise reassures customers that they can try new drinks risk-free, reducing hesitation to experiment with new orders.
The reminder of Starbucks’ Barista Promise reassures customers that they can try new drinks risk-free, reducing hesitation to experiment with new orders.
research methods
research methods
research methods
Using a range of user-centered research methods such as site observations, surveys, interviews with users and baristas, landscape analysis, and cognitive walkthrough, we uncovered the following findings:
Using a range of user-centered research methods such as site observations, surveys, interviews with users and baristas, landscape analysis, and cognitive walkthrough, we uncovered the following findings:
Using a range of user-centered research methods such as site observations, surveys, interviews with users and baristas, landscape analysis, and cognitive walkthrough, we uncovered the following findings:
Customer Interaction Patterns
Customer Interaction Patterns
Customer Interaction Patterns
Observations at multiple Starbucks locations revealed that customers mainly interacted with baristas to check on their order status and tended to wait at the pickup counter. Some customers mistakenly ordered from nearby Starbucks locations.
Observations at multiple Starbucks locations revealed that customers mainly interacted with baristas to check on their order status and tended to wait at the pickup counter. Some customers mistakenly ordered from nearby Starbucks locations.
Observations at multiple Starbucks locations revealed that customers mainly interacted with baristas to check on their order status and tended to wait at the pickup counter. Some customers mistakenly ordered from nearby Starbucks locations.
Curiosity vs. Barriers to Trying New Drinks
Curiosity vs. Barriers to Trying New Drinks
Curiosity vs. Barriers to Trying New Drinks
Survey results showed that while 79% of customers were interested in trying new drinks, barriers such as concerns about wasting money and dietary restrictions hindered their willingness. Familiar flavors were highly valued, and featured specials were the biggest motivators for trying new items.
Survey results showed that while 79% of customers were interested in trying new drinks, barriers such as concerns about wasting money and dietary restrictions hindered their willingness. Familiar flavors were highly valued, and featured specials were the biggest motivators for trying new items.
Survey results showed that while 79% of customers were interested in trying new drinks, barriers such as concerns about wasting money and dietary restrictions hindered their willingness. Familiar flavors were highly valued, and featured specials were the biggest motivators for trying new items.
Desire for Personalized Recommendations
Desire for Personalized Recommendations
Desire for Personalized Recommendations
Interviews with users and baristas indicated a strong desire for personalized drink recommendations within the app. Customers preferred suggestions based on past orders and were more inclined to try new items if promotions or extra Stars were offered.
Interviews with users and baristas indicated a strong desire for personalized drink recommendations within the app. Customers preferred suggestions based on past orders and were more inclined to try new items if promotions or extra Stars were offered.
Interviews with users and baristas indicated a strong desire for personalized drink recommendations within the app. Customers preferred suggestions based on past orders and were more inclined to try new items if promotions or extra Stars were offered.
Effective Strategies from Other Industries
Effective Strategies from Other Industries
Effective Strategies from Other Industries
The landscape analysis highlighted that successful strategies from other sectors include offering samples (Trader Joe’s, Sephora) and using detailed analytics for accurate service (Chick-fil-A). Additionally, social sharing features (Spotify) enhance discovery, suggesting similar tactics could benefit Starbucks.
The landscape analysis highlighted that successful strategies from other sectors include offering samples (Trader Joe’s, Sephora) and using detailed analytics for accurate service (Chick-fil-A). Additionally, social sharing features (Spotify) enhance discovery, suggesting similar tactics could benefit Starbucks.
The landscape analysis highlighted that successful strategies from other sectors include offering samples (Trader Joe’s, Sephora) and using detailed analytics for accurate service (Chick-fil-A). Additionally, social sharing features (Spotify) enhance discovery, suggesting similar tactics could benefit Starbucks.
design requirements
design requirements
design requirements
Based on our research and analysis, we identified the following design requirements for our feature:
Based on our research and analysis, we identified the following design requirements for our feature:
Based on our research and analysis, we identified the following design requirements for our feature:
Be Transparent About Data
Be Transparent About Data
Be Transparent About Data
The feature should provide data-driven transparency and insight into why a drink is trending.
The feature should provide data-driven transparency and insight into why a drink is trending.
The feature should provide data-driven transparency and insight into why a drink is trending.
Reassure Customers
Reassure Customers
Reassure Customers
The feature should provide risk reduction by reminding users of Starbucks’ Barista Promise.
The feature should provide risk reduction by reminding users of Starbucks’ Barista Promise.
The feature should provide risk reduction by reminding users of Starbucks’ Barista Promise.
Cater to Users’ Contexts
Cater to Users’ Contexts
Cater to Users’ Contexts
The feature should have multiple points of entry and cater to different user scenarios (traveling, daily-use/routine, exploratory mood).
The feature should have multiple points of entry and cater to different user scenarios (traveling, daily-use/routine, exploratory mood).
The feature should have multiple points of entry and cater to different user scenarios (traveling, daily-use/routine, exploratory mood).
Offer Incentives
Offer Incentives
Offer Incentives
The feature should reward desired behaviors (purchasing new items) with bonus Stars. This incentive should be introduced to users early on as an entryway to using the feature.
The feature should reward desired behaviors (purchasing new items) with bonus Stars. This incentive should be introduced to users early on as an entryway to using the feature.
The feature should reward desired behaviors (purchasing new items) with bonus Stars. This incentive should be introduced to users early on as an entryway to using the feature.
Be User Friendly
Be User Friendly
Be User Friendly
The feature should be accessible to all users, including those with visual impairments, by providing alternatives for data interpretation (i.e. alt text and captions).
The feature should be accessible to all users, including those with visual impairments, by providing alternatives for data interpretation (i.e. alt text and captions).
The feature should be accessible to all users, including those with visual impairments, by providing alternatives for data interpretation (i.e. alt text and captions).
Preliminary concepts
Preliminary concepts
Preliminary concepts
We brainstormed over 120 ideas for each design requirement, dot-voted on them in Miro, and, after receiving feedback on priorities and constraints, narrowed down to three preliminary concepts:
We brainstormed over 120 ideas for each design requirement, dot-voted on them in Miro, and, after receiving feedback on priorities and constraints, narrowed down to three preliminary concepts:
We brainstormed over 120 ideas for each design requirement, dot-voted on them in Miro, and, after receiving feedback on priorities and constraints, narrowed down to three preliminary concepts:
Dietary Tags
Dietary Tags
Dietary Tags
Streamlining drink selection by allowing customers to filter menu options according to dietary preferences and displaying relevant tags (e.g., non-dairy, sugar-free, low calorie) under drink names.
Streamlining drink selection by allowing customers to filter menu options according to dietary preferences and displaying relevant tags (e.g., non-dairy, sugar-free, low calorie) under drink names.
Streamlining drink selection by allowing customers to filter menu options according to dietary preferences and displaying relevant tags (e.g., non-dairy, sugar-free, low calorie) under drink names.
Friend Experience
Friend Experience
Friend Experience
Earning bonus stars by recommending drinks to a friend and scheduling a shared coffee date window to try the recommended drinks together.
Earning bonus stars by recommending drinks to a friend and scheduling a shared coffee date window to try the recommended drinks together.
Earning bonus stars by recommending drinks to a friend and scheduling a shared coffee date window to try the recommended drinks together.
Drink Map
Drink Map
Drink Map
Enabling customers to view trending drinks at different Starbucks locations, whether they are at home or traveling.
Enabling customers to view trending drinks at different Starbucks locations, whether they are at home or traveling.
Enabling customers to view trending drinks at different Starbucks locations, whether they are at home or traveling.
After conducting feedback sessions on our three concepts, we chose to proceed with the Drink Map feature as it best addressed our problem statement. However, some users had some concerns about data sources and potentially perpetuating any stereotypes related to coffee.
After conducting feedback sessions on our three concepts, we chose to proceed with the Drink Map feature as it best addressed our problem statement. However, some users had some concerns about data sources and potentially perpetuating any stereotypes related to coffee.
After conducting feedback sessions on our three concepts, we chose to proceed with the Drink Map feature as it best addressed our problem statement. However, some users had some concerns about data sources and potentially perpetuating any stereotypes related to coffee.
mid-fidelity wireframes
mid-fidelity wireframes
mid-fidelity wireframes
In this next iteration, we introduced two entry points for the Drink Map— the store selection map and a banner across the Order screen tabs— to align with users' varied ordering routines. We also added a location-specific page highlighting trending drinks by time of day.
In this next iteration, we introduced two entry points for the Drink Map— the store selection map and a banner across the Order screen tabs— to align with users' varied ordering routines. We also added a location-specific page highlighting trending drinks by time of day.
In this next iteration, we introduced two entry points for the Drink Map— the store selection map and a banner across the Order screen tabs— to align with users' varied ordering routines. We also added a location-specific page highlighting trending drinks by time of day.
evaluation
evaluation
evaluation
After refining our mid-fidelity wireframes into a high-fidelity prototype, we conducted heuristic evaluations and cognitive walkthroughs with 4 UX experts, along with user testing involving 5 members of our target audience.
After refining our mid-fidelity wireframes into a high-fidelity prototype, we conducted heuristic evaluations and cognitive walkthroughs with 4 UX experts, along with user testing involving 5 members of our target audience.
After refining our mid-fidelity wireframes into a high-fidelity prototype, we conducted heuristic evaluations and cognitive walkthroughs with 4 UX experts, along with user testing involving 5 members of our target audience.
After affinity mapping our cognitive walkthrough and user testing notes and averaging the heuristic evaluation scores, we identified the following key findings.
After affinity mapping our cognitive walkthrough and user testing notes and averaging the heuristic evaluation scores, we identified the following key findings.
After affinity mapping our cognitive walkthrough and user testing notes and averaging the heuristic evaluation scores, we identified the following key findings.
Accessibility Considerations
Accessibility Considerations
Accessibility Considerations
For our prototype, the Drink Map pins were hard to see due to varying sizes, and the banners on order screens were too small.
For our prototype, the Drink Map pins were hard to see due to varying sizes, and the banners on order screens were too small.
For our prototype, the Drink Map pins were hard to see due to varying sizes, and the banners on order screens were too small.
For Starbucks, enabling responsive text resizing and adding alternative text for maps would improve usability.
For Starbucks, enabling responsive text resizing and adding alternative text for maps would improve usability.
For Starbucks, enabling responsive text resizing and adding alternative text for maps would improve usability.
Usability Issues
Usability Issues
Usability Issues
Users relied on the list view for drink names due to insufficient map details.
Users relied on the list view for drink names due to insufficient map details.
Users relied on the list view for drink names due to insufficient map details.
The difference between the store locator map and Drink Map confused some users.
The difference between the store locator map and Drink Map confused some users.
The difference between the store locator map and Drink Map confused some users.
Drink Map entry point language was unclear.
Drink Map entry point language was unclear.
Drink Map entry point language was unclear.
The phrase "New to you" was confusing to some users.
The phrase "New to you" was confusing to some users.
The phrase "New to you" was confusing to some users.
Due to time constraints, we were only able to address the accessibility considerations in our prototype.
Due to time constraints, we were only able to address the accessibility considerations in our prototype.
Due to time constraints, we were only able to address the accessibility considerations in our prototype.
RefLEctions
RefLEctions
RefLEctions
This was one of my first projects in Georgia Tech’s MS-HCI program. Collaborating with an industry partner like Starbucks on a mature product added a level of realism that was distinct from our other first-semester project, Klemis Commons, where the constraints were less defined.
This was one of my first projects in Georgia Tech’s MS-HCI program. Collaborating with an industry partner like Starbucks on a mature product added a level of realism that was distinct from our other first-semester project, Klemis Commons, where the constraints were less defined.
This was one of my first projects in Georgia Tech’s MS-HCI program. Collaborating with an industry partner like Starbucks on a mature product added a level of realism that was distinct from our other first-semester project, Klemis Commons, where the constraints were less defined.
Wishes
Wishes
Wishes
Given more time, we would have explored different ways to visualize trending drink information as users mistakenly believed they needed to order the trending drink at the specific location shown on the map, which was not the intended purpose.
Given more time, we would have explored different ways to visualize trending drink information as users mistakenly believed they needed to order the trending drink at the specific location shown on the map, which was not the intended purpose.
Given more time, we would have explored different ways to visualize trending drink information as users mistakenly believed they needed to order the trending drink at the specific location shown on the map, which was not the intended purpose.
Learnings
Learnings
Learnings
We learned that it’s easy to lead users during testing by unintentionally asking biased questions and providing verbal affirmations when they interacted with the prototypes as we intended.
We learned that it’s easy to lead users during testing by unintentionally asking biased questions and providing verbal affirmations when they interacted with the prototypes as we intended.
We learned that it’s easy to lead users during testing by unintentionally asking biased questions and providing verbal affirmations when they interacted with the prototypes as we intended.
Next Steps
Next Steps
Next Steps
Next, we would conduct research to identify more Drink Map categories that align with user preferences and explore accessible ways to present Drink Map information beyond a standard list view for visually impaired users.
Next, we would conduct research to identify more Drink Map categories that align with user preferences and explore accessible ways to present Drink Map information beyond a standard list view for visually impaired users.
Next, we would conduct research to identify more Drink Map categories that align with user preferences and explore accessible ways to present Drink Map information beyond a standard list view for visually impaired users.