Phase 1: User Interview
We began with semi-structured interviews, conducted both in-person and virtually, targeting two user groups: New Users and Frequent Users. The interviews focused on understanding their experiences with usability, navigation, and delivery tracking within the app. With participant consent, all interviews were recorded, providing us with rich, detailed data for post-analysis. This phase helped us gather first-hand insights directly from users about their challenges and preferences.
Phase 2: Think-Aloud Usability Testing
Following the interviews, we conducted 10 think-aloud sessions to observe real-time user behavior while interacting with the app. These sessions provided deeper insights into how users navigated the app, revealing additional usability issues that might not have surfaced during the interviews. Observing users in action allowed us to pinpoint specific areas where the app’s design could be improved.
DoorDash
UXR Study
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Overview
For our research, we conducted an evaluation of the DoorDash app, focusing on both new and
frequent users. DoorDash is a popular food delivery service that allows users to browse menus,
order meals, and track deliveries in real time. Our goal was to understand how well the app caters to these two distinct user groups—those who are using the app for the first time and those who frequently use it for food delivery.
My Role
Research Planning
User Interviews
Data Analysis
Usability Testing and Reporting
Duration
45 days
Our research followed a multi-phase approach to evaluate and improve the usability of the DoorDash app. We used a combination of qualitative and quantitative methods, progressing through three distinct phases. Each phase was essential in gathering comprehensive user feedback, which guided the subsequent stages of analysis and synthesis
For our study, we aimed to recruit a total of 10 participants, divided equally between two groups*
5 frequent users: Individuals who use DoorDash a few times a week
5 new users: Individuals, particularly students, who had started using DoorDash in the past month and placed three or fewer orders.
Why we chose them:
We selected frequent users because their extensive experience with the app allowed us to evaluate long-term usability and how well features like reordering and DashPass meet their needs. New users were chosen to help us understand their initial experiences and identify any potential usability issues they face as they familiarize themselves with the app.
How we recruited participants:
University Networks: We reached out to student clubs and groups to help spread the word.
Social Media Groups: Class group chats were used to identify participants who matched our criteria.
Word of Mouth: Friends and classmates were encouraged to refer anyone they knew who fit the profiles. This recruitment approach ensured a balanced set of users to provide insights into both new and frequent user experiences.
Research Goals
Research Methodology
Recruitment Criteria and Process
Sample Questions Asked
Data Collection Methods
Data Collection Methods
Analysis and Synthesis Process
Phase 1: User Interviews
Thank You!
For sparing some time and review my work.
Do you have great idea and want to share. Let’s make something amazing together
Get in touch with me
Privacy policy
Cookies policy
Behance
Dribbble
E-Commerce App
Gamigo
UX Design | UI Design | Mobile App Design
Productivity App
Timely
UX Design | UI Design | Mobile App Design
Frequent Users
*Those who started using DoorDash in the last three months and have placed three or fewer orders.
Identify any challenges they face with ordering or tracking deliveries.
Assess how easily they can reorder or use features like favorite stores.
Explore what keeps them loyal to the platform and how features like DashPass impact their behavior
Common Pain Points and Feedback
Identify any shared issues between frequent and new users around customising orders and the checkout process.
See how both groups feel about the way the app communicates order status and delivery times.
New Users
*Individuals who use DoorDash at least a few times a month to place food orders.
Understanding how they navigate the app for the first time and what aspects of placing an order are easy or confusing.
Identifying potential issues with payment, finding restaurants, or understanding delivery times.
Gaining feedback on how clear and helpful the delivery and pickup tracking features are for first-time users.
Phase 3: SUS Scoring
To quantify user satisfaction, we conducted System Usability Scale (SUS) scoring with the same participants from the think-aloud sessions. The SUS method allowed us to measure the overall usability of the DoorDash app, providing a numerical score that offered insights into users’ perceived ease of use.
Background
How often do you typically use food delivery apps like DoorDash?
Can you tell me a bit about your daily routine? How does ordering food through DoorDash fit into your day?
Experience with DoorDash
Frequent Users
Can you walk me through your usual process when placing an order on DoorDash? What’s your typical routine?
What’s the one thing that consistently works well for you when using DoorDash?
How would you compare DoorDash to other food delivery apps you’ve used?
New Users
What was your first experience like when you used DoorDash? Was there anything that stood out, positively or negatively?
How did you feel navigating the app? Was anything confusing or frustrating?
Delivery Tracking and Communication
How do you feel about the delivery tracking feature? Do you find it accurate and helpful?
Has there been a time when the estimated delivery time didn’t match your experience?
What Keeps Users Coming Back to DoorDash
Frequent Users
What makes you choose DoorDash over other food delivery apps?
Have you used DashPass or other loyalty features? How do they impact your decision to use DoorDash?
Emotions & Frustrations
Can you tell me about a time when using DoorDash really stood out, either in a good or bad way?
How does using DoorDash generally make you feel when ordering
Wrap-Up
Is there anything else about your experience with DoorDash that you think we should know?
Recording
With participant consent, all interviews were recorded to ensure accurate review and thorough analysis of the discussions.
Transcribing and Reviewing Notes
After completing the interviews, we began with transcribing the recordings and thoroughly reviewing the notes taken during each session. This step ensured that all user feedback was accurately captured fir analysis.
Note-taking
The interviewer took notes on key moments and observations during the sessions, caputring important insights in real-time.
Debrief Sessions
Next, we conducted debrief sessions immediately following each interview. These discussions allowed us to share first impressions and identify any emerging patterns while the interviews were still fresh in our minds. Debriefing helped us make minor djustments to subsequent interviews, ensuring we explored key topics more deeply.
Collabrative Synthesis
The synthesis process was a collaborative effort involving the entire research team. Each member contributed their perspective during the analysis, allowing us to reach a consensus on the most important insights and themes
Affinity Diagramming
The actual analysis of the data started with the creation of affinity diagrams. We used this technique to visually organize and categorize the user feedback, creating separate diagrams for New Users and Frequent Users. This method allowed us to group similar insights, making it easier to spot patterns and recurring themes.
Frequent Users
New Users
Persona Creation
Based on the insights gathered, we developed personas for both user groups. These personas represented typical
users, summarizing their behaviors, motivations, and frustrations, which guided our recommendations
Frequent Users
New User
Key Findings
Discovery and Usage Patterns
Most users learned about DoorDash through friends or social media ads. New users ordered 1-2 times monthly, while frequent users relied on it weekly for convenience during busy schedules.
Key Factors Affecting Users
Promotions like zero delivery fees and discounts attracted users, while DoorDash's affordability and wide restaurant variety made it appealing compared to competitors like UberEats.
Ordering Experience
Users found the ordering process smooth, with frequent users valuing the 'reorder' feature, while new users faced slow loading times and confusing filter options.
Delivery Tracking and Support
Users appreciated the accurate delivery tracking but were frustrated by unresponsive drivers during delays or cancellations and limited in-app support options.
Perception of DashPass
Frequent users often tried DashPass during a free trial but didn’t continue due to the fee, relying on existing discounts. New users were aware of DashPass but didn’t subscribe, as their infrequent orders didn’t justify the cost.
Delays and Driver Cancellations
Users felt anxious during delivery delays, believing tipping upfront might speed up service, and were frustrated by driver cancellations due to the lack of immediate support or alternatives.
Comparison to Competitors
Users preferred DoorDash for its variety and pricing over UberEats but noted that Indian platforms like Swiggy and Zomato offered free delivery with subscriptions, unlike DashPass.
Task Given
Data Collection Methods
Data Collection Methods
Analysis and Synthesis Process
Phase 2: Think-Aloud Usability Testing
Task 1
Find a sushi restaurant using either the filters or search bar
Task 1.1: Once a restaurant is found, explore the menu, identifying what is easy or confusing about the layout and options .
Task 1.2: Pick an item from the menu and customize it (e.g., add/remove toppings, adjust portion sizes). We assessed how intuitive the customization process was and whether users faced any challenges.
Task 2
Use filters to narrow down restaurant options to vegetarian places offering meals under $10
Task 2.1: Review the filtered results, assessing whether the filters worked as expected and how relevant the results were.
Task 2.2: For one of the restaurants, check for available promotions or discounts, and evaluate how easy it was to find and understand the offer
Screen Recording
Sessions were recorded with participants’ consent to capture user interactions, clicks, and navigation pattern.
Think-Aloud Protocol
Participants verbalized their thoughts while performing the tasks, providing insight into their thought processes and frustrations.
Transcribing and Reviewing Notes
After conducting the think-aloud sessions, we transcribed the recordings and thoroughly reviewed the notes from
each session to capture detailed user insights
Developing Common Codes/Themes
Next, we developed common codes or themes to group related issues. This categorization helped us organize the data to deeper analysis.
Calculating Probability of Detecting Issues and Confidence Interval
Using the identified themes and patterns, we calculated the Probability of Detecting Issues and the Confidence
Interval, ensuring statistical reliability in our findings.
Note-taking
Detailed notes were taken to capture real-time reactions and pain points during each task.
Identifying Usability Issues
We then analyzed the gathered data to identify all the usability issues that emerged, focusing on recurring problems
and unique challenges faced by participants
Results from Data
Probability of Detecting Issues
Task 1
5 out of 5 users (100%) successfully completed the task of finding a sushi restaurant and customizing an order.
Task 2
5 out of 5 users (100%) successfully completed the task of using filters to find vegetarian restaurants under $10 and locating promotions.
Based on these results, we calculated the 95% Confidence Interval for the actual population completion rate to be between 59.9% and 85.71%. While the margin of error is relatively high, the data suggests that at least 50% of users can successfully complete the tasks before the next testing cycle.
There is a small chance that the actual completion rate could be below 50%, but the results provide evidence that users are generally able to complete these tasks effectively
Key Findings
Difficulty Finding the “Vegetarian” Filter
6 out of 10 participants struggled to locate the “Vegetarian” filter while completing Task 2, causing frustration and delays in na1qqrrowing down restaurant options
Issues with Horizontal Scrolling Menu Filters
3 out of 10 participants found the horizontal scrolling menu filter confusing or difficult to use, which led to missed opportunities for further customization or selection.
Overlooked Deals Section
2 out of 10 participants overlooked the deals and promotions section due to a cluttered user interface. The placement and design of this section made it hard for users to notice available discounts.
Visibility Problems with Filters After Multiple Selections
2 out of 10 participants reported that filters became less visible or harder to manage after they made multiple selections, which reduced the effectiveness of filtering options.
Analysis and Synthesis Process
Phase 3: SUS Scoring
Following the think-aloud sessions, the same participants were asked to complete the System Usability Scale (SUS). Each participant rated ten usability statements on a 5-point Likert scale, where 1 indicated strong disagreement and 5 indicated
strong agreement.
Once the data was collected, we compiled the responses into an Excel spreadsheet for calculation. The raw ratings were adjusted based on the SUS scoring formula, and then each score was multiplied by 2.5 to obtain the final usability score for each participant. This allowed us to quantify the overall usability of the DoorDash app from the perspective of both new and
frequent users.
Results from Data
The average SUS score for the DoorDash app was 79.5, which is significantly higher than the industry standard score of 67 for good usability. This indicates that the app is generally perceived as easy to use and effective in meeting users’ needs.
Additionally, the 90% Confidence Interval for the mean SUS score was calculated to be between 74.28 and 84.72. This means we can be 90% confident that the true mean usability score lies within this range, suggesting that the app has very few usability issues and performs well overall in terms of user satisfaction.
Improve Filter usability and Visibilty
Think-aloud sessions revealed users struggled with finding specific filters (e.g., vegetarian options) and disliked the horizontal scrolling menu. Recommendations include:
Make key filters prominent and accessible.
Keep filters visible and functional after selections.
Improve filter relevance to match expectations.
Revise the DashPass Model
Many users were aware of DashPass but felt it lacked value due to ongoing delivery fees. Recommendations include:
Reducing fees or offering exclusive promotions.
Educating users on benefits through in-app messages.
Enhance Customization & Order Management
Customization of menu items was challenging, especially for adjusting portions or adding toppings. Recommendations include:
Simplifying the process by reducing steps and clearly labeling options.
Creating an intuitive order flow for easy modifications without restarting.
Clarifying Tipping and Delivery Times
Frequent users were concerned about tipping and its impact on delivery speed. Recommendations include:
Clarifying that tipping does not affect delivery times.
Ensuring consistent delivery times with transparent communication on influencing factors.
Based on the findings from our user interviews, think-aloud usability testing, and SUS scoring, we have identified several key areas for improvement and recommendations for enhancing the DoorDash app. These recommendations are aimed at refining the user experience and addressing the usability concerns uncovered throughout the project.
Recommendations
Improve Delivery Tracking & Communication
Delivery tracking is appreciated, but communication gaps exist during delays or unresponsive drivers. Recommendations include:
Providing frequent, transparent updates with delay explanations.
Ensuring prompt driver responses or automated updates.
Moving forward, these recommendations will be crucial in refining the DoorDash app’s overall usability and addressing pain points raised by both new and frequent users. The next steps should involve.
Next Steps
Iterating on DashPass and promotions based on user feedback to increase subscription adoption and engagement.
Prioritizing high-impact usability fixes such as improving filter functionality and customization flows.
Conducting follow-up testing after these changes have been implemented to assess their effectiveness and measure improvements in user satisfaction.
Phase 1: User Interview
We began with semi-structured interviews, conducted both in-person and virtually, targeting two user groups: New Users and Frequent Users. The interviews focused on understanding their experiences with usability, navigation, and delivery tracking within the app. With participant consent, all interviews were recorded, providing us with rich, detailed data for post-analysis. This phase helped us gather first-hand insights directly from users about their challenges and preferences.
Phase 2: Think-Aloud Usability Testing
Following the interviews, we conducted 10 think-aloud sessions to observe real-time user behavior while interacting with the app. These sessions provided deeper insights into how users navigated the app, revealing additional usability issues that might not have surfaced during the interviews. Observing users in action allowed us to pinpoint specific areas where the app’s design could be improved.
Overview
For our research, we conducted an evaluation of the DoorDash app, focusing on both new and
frequent users. DoorDash is a popular food delivery service that allows users to browse menus,
order meals, and track deliveries in real time. Our goal was to understand how well the app caters to these two distinct user groups—those who are using the app for the first time and those who frequently use it for food delivery.
My Role
Research Planning
User Interviews
Data Analysis
Usability Testing and Reporting
Duration
45 days
Our research followed a multi-phase approach to evaluate and improve the usability of the DoorDash app. We used a combination of qualitative and quantitative methods, progressing through three distinct phases. Each phase was essential in gathering comprehensive user feedback, which guided the subsequent stages of analysis and synthesis
For our study, we aimed to recruit a total of 10 participants, divided equally between two groups*
5 frequent users: Individuals who use DoorDash a few times a week
5 new users: Individuals, particularly students, who had started using DoorDash in the past month and placed three or fewer orders.
Why we chose them:
We selected frequent users because their extensive experience with the app allowed us to evaluate long-term usability and how well features like reordering and DashPass meet their needs. New users were chosen to help us understand their initial experiences and identify any potential usability issues they face as they familiarize themselves with the app.
How we recruited participants:
University Networks: We reached out to student clubs and groups to help spread the word.
Social Media Groups: Class group chats were used to identify participants who matched our criteria.
Word of Mouth: Friends and classmates were encouraged to refer anyone they knew who fit the profiles. This recruitment approach ensured a balanced set of users to provide insights into both new and frequent user experiences.
Research Goals
Research Methodology
Recruitment Criteria and Process
Sample Questions Asked
Data Collection Methods
Data Collection Methods
Analysis and Synthesis Process
Phase 1: User Interviews
Thank You!
For sparing some time and review my work.
Do you have great idea and want to share. Let’s make something amazing together
Get in touch with me
Privacy policy
Cookies policy
Behance
Dribbble
E-Commerce App
Gamigo
UX Design | UI Design | Mobile App Design
Productivity App
Timely
UX Design | UI Design | Mobile App Design
Productivity App
Timely
UX Design | UI Design | Mobile App Design
Frequent Users
*Those who started using DoorDash in the last three months and have placed three or fewer orders.
Identify any challenges they face with ordering or tracking deliveries.
Assess how easily they can reorder or use features like favorite stores.
Explore what keeps them loyal to the platform and how features like DashPass impact their behavior
Common Pain Points and Feedback
Identify any shared issues between frequent and new users around customising orders and the checkout process.
See how both groups feel about the way the app communicates order status and delivery times.
New Users
*Individuals who use DoorDash at least a few times a month to place food orders.
Understanding how they navigate the app for the first time and what aspects of placing an order are easy or confusing.
Identifying potential issues with payment, finding restaurants, or understanding delivery times.
Gaining feedback on how clear and helpful the delivery and pickup tracking features are for first-time users.
Phase 3: SUS Scoring
To quantify user satisfaction, we conducted System Usability Scale (SUS) scoring with the same participants from the think-aloud sessions. The SUS method allowed us to measure the overall usability of the DoorDash app, providing a numerical score that offered insights into users’ perceived ease of use.
Background
How often do you typically use food delivery apps like DoorDash?
Can you tell me a bit about your daily routine? How does ordering food through DoorDash fit into your day?
Experience with DoorDash
Frequent Users
Can you walk me through your usual process when placing an order on DoorDash? What’s your typical routine?
What’s the one thing that consistently works well for you when using DoorDash?
How would you compare DoorDash to other food delivery apps you’ve used?
New Users
What was your first experience like when you used DoorDash? Was there anything that stood out, positively or negatively?
How did you feel navigating the app? Was anything confusing or frustrating?
Delivery Tracking and Communication
How do you feel about the delivery tracking feature? Do you find it accurate and helpful?
Has there been a time when the estimated delivery time didn’t match your experience?
What Keeps Users Coming Back to DoorDash
Frequent Users
What makes you choose DoorDash over other food delivery apps?
Have you used DashPass or other loyalty features? How do they impact your decision to use DoorDash?
Emotions & Frustrations
Can you tell me about a time when using DoorDash really stood out, either in a good or bad way?
How does using DoorDash generally make you feel when ordering
Wrap-Up
Is there anything else about your experience with DoorDash that you think we should know?
Recording
With participant consent, all interviews were recorded to ensure accurate review and thorough analysis of the discussions.
Transcribing and Reviewing Notes
After completing the interviews, we began with transcribing the recordings and thoroughly reviewing the notes taken during each session. This step ensured that all user feedback was accurately captured fir analysis.
Note-taking
The interviewer took notes on key moments and observations during the sessions, caputring important insights in real-time.
Debrief Sessions
Next, we conducted debrief sessions immediately following each interview. These discussions allowed us to share first impressions and identify any emerging patterns while the interviews were still fresh in our minds. Debriefing helped us make minor djustments to subsequent interviews, ensuring we explored key topics more deeply.
Collabrative Synthesis
The synthesis process was a collaborative effort involving the entire research team. Each member contributed their perspective during the analysis, allowing us to reach a consensus on the most important insights and themes
Affinity Diagramming
The actual analysis of the data started with the creation of affinity diagrams. We used this technique to visually organize and categorize the user feedback, creating separate diagrams for New Users and Frequent Users. This method allowed us to group similar insights, making it easier to spot patterns and recurring themes.
Frequent Users
New Users
Persona Creation
Based on the insights gathered, we developed personas for both user groups. These personas represented typical
users, summarizing their behaviors, motivations, and frustrations, which guided our recommendations
Frequent Users
New User
Key Findings
Discovery and Usage Patterns
Most users learned about DoorDash through friends or social media ads. New users ordered 1-2 times monthly, while frequent users relied on it weekly for convenience during busy schedules.
Promotions like zero delivery fees and discounts attracted users, while DoorDash's affordability and wide restaurant variety made it appealing compared to competitors like UberEats.
Ordering Experience
Users found the ordering process smooth, with frequent users valuing the 'reorder' feature, while new users faced slow loading times and confusing filter options.
Delivery Tracking and Support
Users appreciated the accurate delivery tracking but were frustrated by unresponsive drivers during delays or cancellations and limited in-app support options.
Perception of DashPass
Frequent users often tried DashPass during a free trial but didn’t continue due to the fee, relying on existing discounts. New users were aware of DashPass but didn’t subscribe, as their infrequent orders didn’t justify the cost.
Delays and Driver Cancellations
Users felt anxious during delivery delays, believing tipping upfront might speed up service, and were frustrated by driver cancellations due to the lack of immediate support or alternatives.
Comparison to Competitors
Users preferred DoorDash for its variety and pricing over UberEats but noted that Indian platforms like Swiggy and Zomato offered free delivery with subscriptions, unlike DashPass.
Task Given
Data Collection Methods
Data Collection Methods
Analysis and Synthesis Process
Phase 2: Think-Aloud Usability Testing
Task 1
Find a sushi restaurant using either the filters or search bar
Task 1.1: Once a restaurant is found, explore the menu, identifying what is easy or confusing about the layout and options .
Task 1.2: Pick an item from the menu and customize it (e.g., add/remove toppings, adjust portion sizes). We assessed how intuitive the customization process was and whether users faced any challenges.
Task 2
Use filters to narrow down restaurant options to vegetarian places offering meals under $10
Task 2.1: Review the filtered results, assessing whether the filters worked as expected and how relevant the results were.
Task 2.2: For one of the restaurants, check for available promotions or discounts, and evaluate how easy it was to find and understand the offer
Screen Recording
Sessions were recorded with participants’ consent to capture user interactions, clicks, and navigation pattern.
Think-Aloud Protocol
Participants verbalized their thoughts while performing the tasks, providing insight into their thought processes and frustrations.
Transcribing and Reviewing Notes
After conducting the think-aloud sessions, we transcribed the recordings and thoroughly reviewed the notes from
each session to capture detailed user insights
Developing Common Codes/Themes
Next, we developed common codes or themes to group related issues. This categorization helped us organize the data to deeper analysis.
Calculating Probability of Detecting Issues and Confidence Interval
Using the identified themes and patterns, we calculated the Probability of Detecting Issues and the Confidence
Interval, ensuring statistical reliability in our findings.
Note-taking
Detailed notes were taken to capture real-time reactions and pain points during each task.
Identifying Usability Issues
We then analyzed the gathered data to identify all the usability issues that emerged, focusing on recurring problems
and unique challenges faced by participants
Results from Data
Probability of Detecting Issues
Task 1
5 out of 5 users (100%) successfully completed the task of finding a sushi restaurant and customizing an order.
Task 2
5 out of 5 users (100%) successfully completed the task of using filters to find vegetarian restaurants under $10 and locating promotions.
Based on these results, we calculated the 95% Confidence Interval for the actual population completion rate to be between 59.9% and 85.71%. While the margin of error is relatively high, the data suggests that at least 50% of users can successfully complete the tasks before the next testing cycle.
There is a small chance that the actual completion rate could be below 50%, but the results provide evidence that users are generally able to complete these tasks effectively
Key Findings
Difficulty Finding the “Vegetarian” Filter
6 out of 10 participants struggled to locate the “Vegetarian” filter while completing Task 2, causing frustration and delays in na1qqrrowing down restaurant options
Issues with Horizontal Scrolling Menu Filters
3 out of 10 participants found the horizontal scrolling menu filter confusing or difficult to use, which led to missed opportunities for further customization or selection.
Overlooked Deals Section
2 out of 10 participants overlooked the deals and promotions section due to a cluttered user interface. The placement and design of this section made it hard for users to notice available discounts.
Visibility Problems with Filters After Multiple Selections
2 out of 10 participants reported that filters became less visible or harder to manage after they made multiple selections, which reduced the effectiveness of filtering options.
Analysis and Synthesis Process
Phase 3: SUS Scoring
Following the think-aloud sessions, the same participants were asked to complete the System Usability Scale (SUS). Each participant rated ten usability statements on a 5-point Likert scale, where 1 indicated strong disagreement and 5 indicated
strong agreement.
Once the data was collected, we compiled the responses into an Excel spreadsheet for calculation. The raw ratings were adjusted based on the SUS scoring formula, and then each score was multiplied by 2.5 to obtain the final usability score for each participant. This allowed us to quantify the overall usability of the DoorDash app from the perspective of both new and
frequent users.
Results from Data
The average SUS score for the DoorDash app was 79.5, which is significantly higher than the industry standard score of 67 for good usability. This indicates that the app is generally perceived as easy to use and effective in meeting users’ needs.
Additionally, the 90% Confidence Interval for the mean SUS score was calculated to be between 74.28 and 84.72. This means we can be 90% confident that the true mean usability score lies within this range, suggesting that the app has very few usability issues and performs well overall in terms of user satisfaction.
Improve Filter usability and Visibilty
Think-aloud sessions revealed users struggled with finding specific filters (e.g., vegetarian options) and disliked the horizontal scrolling menu. Recommendations include:
Make key filters prominent and accessible.
Keep filters visible and functional after selections.
Improve filter relevance to match expectations.
Revise the DashPass Model
Many users were aware of DashPass but felt it lacked value due to ongoing delivery fees. Recommendations include:
Reducing fees or offering exclusive promotions.
Educating users on benefits through in-app messages.
Enhance Customization & Order Management
Customization of menu items was challenging, especially for adjusting portions or adding toppings. Recommendations include:
Simplifying the process by reducing steps and clearly labeling options.
Creating an intuitive order flow for easy modifications without restarting.
Clarifying Tipping and Delivery Times
Frequent users were concerned about tipping and its impact on delivery speed. Recommendations include:
Clarifying that tipping does not affect delivery times.
Ensuring consistent delivery times with transparent communication on influencing factors.
Based on the findings from our user interviews, think-aloud usability testing, and SUS scoring, we have identified several key areas for improvement and recommendations for enhancing the DoorDash app. These recommendations are aimed at refining the user experience and addressing the usability concerns uncovered throughout the project.
Recommendations
Improve Delivery Tracking & Communication
Delivery tracking is appreciated, but communication gaps exist during delays or unresponsive drivers. Recommendations include:
Providing frequent, transparent updates with delay explanations.
Ensuring prompt driver responses or automated updates.
Moving forward, these recommendations will be crucial in refining the DoorDash app’s overall usability and addressing pain points raised by both new and frequent users. The next steps should involve.
Next Steps
Iterating on DashPass and promotions based on user feedback to increase subscription adoption and engagement.
Prioritizing high-impact usability fixes such as improving filter functionality and customization flows.
Conducting follow-up testing after these changes have been implemented to assess their effectiveness and measure improvements in user satisfaction.