New End-to-End Customer Experience
New End-to-End Customer Experience
New End-to-End Customer Experience
04
RESPONSIBILITIES
UX RESEARCH
UX RESEARCH
UX DESIGN
UX DESIGN
Video Editing
UX DESIGN
UX DESIGN
DELIVERABLES
Concept Video
OVERVIEW
Designing the North Star Vision for a New End-to-End Customer Experience
Designing the North Star Vision for a New End-to-End Customer Experience
Designing the North Star Vision for a New End-to-End Customer Experience
As a UX Design Intern at Motorola Solution’s service design department, I was tasked with defining the North Star vision of the end-to-end customer experience for the TLK-25 product line—a wearable communications device designed for the hospitality industry. The final output was a comprehensive video showing the full experience. Due to NDA, I cannot display the final concept video.
As a UX Design Intern at Motorola Solution’s service design department, I was tasked with defining the North Star vision of the end-to-end customer experience for the TLK-25 product line—a wearable communications device designed for the hospitality industry. The final output was a comprehensive video showing the full experience. Due to NDA, I cannot display the final concept video.
As a UX Design Intern at Motorola Solution’s service design department, I was tasked with defining the North Star vision of the end-to-end customer experience for the TLK-25 product line—a wearable communications device designed for the hospitality industry. The final output was a comprehensive video showing the full experience. Due to NDA, I cannot display the final concept video.
PROJECT DETAILS
Motorola Solutions' provisioning portal allows users to set up devices by adding them to talk groups or group chats. While the system was mainly used by dealers with expert experience, it became clear that without dealer's help, customers will struggle to navigate the portal effectively on their own.
With the new TLK-25 product line, addressing this challenge is critical to empowering customers, improving their experience, and reducing inefficiencies for both users and dealers.
Among the 4 stages of customer experience, I primarily focused on the configuration the experience.
This is what a Radar look like, but there are more than 20 more them!
This is what a Radar look like, but there are more than 20 more them!
This is what a Radar look like, but there are more than 20 more them!
ABOUT
Motorola Solutions powers critical communications
Motorola Solutions powers critical communications
Motorola Solutions powers critical communications
As a global leader in mission-critical communications and enterprise software, Motorola Solutions supports millions of users across public safety, manufacturing, hospitality, and more. From two-way radios to advanced software platforms, our solutions enable teams to stay connected and informed.
As a global leader in mission-critical communications and enterprise software, Motorola Solutions supports millions of users across public safety, manufacturing, hospitality, and more. From two-way radios to advanced software platforms, our solutions enable teams to stay connected and informed.
As a global leader in mission-critical communications and enterprise software, Motorola Solutions supports millions of users across public safety, manufacturing, hospitality, and more. From two-way radios to advanced software platforms, our solutions enable teams to stay connected and informed.
Discover Bigger Picture
Discover Bigger Picture
Discover Bigger Picture
Build Depth for Personalized Path
Build Depth for Personalized Path
Build Depth for Personalized Path
Timeline
2022 May-2022 September
Timeline
2022 May-2022 September
Timeline
2022 May-2022 September
Small, precise movements based on tactile feedback
Operating a real micropipette relies on small, precise thumb movements, with tactile feedback distinguishing the first and second stops.
Small, precise movements based on tactile feedback
Operating a real micropipette relies on small, precise thumb movements, with tactile feedback distinguishing the first and second stops.
Small, precise movements based on tactile feedback
Operating a real micropipette relies on small, precise thumb movements, with tactile feedback distinguishing the first and second stops.
PROPOSED SOLUTIONS
Uncertainty about where to start in the provisioning portal, but not following an optimal setup sequence can lead to additional manual work.
Uncertainty about where to start in the provisioning portal, but not following an optimal setup sequence can lead to additional manual work.
Uncertainty about where to start in the provisioning portal, but not following an optimal setup sequence can lead to additional manual work.
My Role
User Experience Design Intern
My Role
User Experience Design Intern
My Role
User Experience Design Intern
Galaxy Visualization: Enables open-ended exploration, revealing hidden connections through an intuitive, visual map.
Galaxy Visualization: Enables open-ended exploration, revealing hidden connections through an intuitive, visual map.
Galaxy Visualization: Enables open-ended exploration, revealing hidden connections through an intuitive, visual map.
Personal Dashboard: Adapts to individual roles and goals, surfacing timely, relevant insights that support day-to-day decisions.
Personal Dashboard: Adapts to individual roles and goals, surfacing timely, relevant insights that support day-to-day decisions.
Personal Dashboard: Adapts to individual roles and goals, surfacing timely, relevant insights that support day-to-day decisions.
From passive watching to hands-on practice
Based on these research insights, we proposed the following features to make the virtual lab experience more accessible:
Multimodal instructions: Offer multimodal instruction combining video, text, and narration to accommodate varying learning preferences.
Streamlined Interactions: Minimize task-switching by integrating instructions and immediate feedback directly into the workflow to guide user focus.
Open and Observable Environment: Create a shared, open environment where peers can observe each other’s progress, enabling body doubling while maintaining an immersive and realistic practice experience.
Based on these research insights, we proposed the following features to make the virtual lab experience more accessible:
Multimodal instructions: Offer multimodal instruction combining video, text, and narration to accommodate varying learning preferences.
Streamlined Interactions: Minimize task-switching by integrating instructions and immediate feedback directly into the workflow to guide user focus.
Open and Observable Environment: Create a shared, open environment where peers can observe each other’s progress, enabling body doubling while maintaining an immersive and realistic practice experience.
Based on these research insights, we proposed the following features to make the virtual lab experience more accessible:
Multimodal instructions: Offer multimodal instruction combining video, text, and narration to accommodate varying learning preferences.
Streamlined Interactions: Minimize task-switching by integrating instructions and immediate feedback directly into the workflow to guide user focus.
Open and Observable Environment: Create a shared, open environment where peers can observe each other’s progress, enabling body doubling while maintaining an immersive and realistic practice experience.
Currently, actions in the portal are not presented in a clear, linear sequence, which can lead to users skipping steps or configuring devices in the wrong order. This misalignment forces users to go back and redo tasks, increasing the likelihood of errors and wasted effort. As organizations grow larger and their setups become more complex, minimizing repetitive manual work becomes critical to ensuring efficient and error-free configurations.
Currently, actions in the portal are not presented in a clear, linear sequence, which can lead to users skipping steps or configuring devices in the wrong order. This misalignment forces users to go back and redo tasks, increasing the likelihood of errors and wasted effort. As organizations grow larger and their setups become more complex, minimizing repetitive manual work becomes critical to ensuring efficient and error-free configurations.
Currently, actions in the portal are not presented in a clear, linear sequence, which can lead to users skipping steps or configuring devices in the wrong order. This misalignment forces users to go back and redo tasks, increasing the likelihood of errors and wasted effort. As organizations grow larger and their setups become more complex, minimizing repetitive manual work becomes critical to ensuring efficient and error-free configurations.
Technology View
What it does: Groups projects by the technologies they apply or explore.
Hierarchy: Tech field → Specific methods/models → Projects
Why it’s helpful: Ideal for identifying innovation trends, technical overlaps, or evaluating tech adoption maturity.
Technology View
What it does: Groups projects by the technologies they apply or explore.
Hierarchy: Tech field → Specific methods/models → Projects
Why it’s helpful: Ideal for identifying innovation trends, technical overlaps, or evaluating tech adoption maturity.
Technology View
What it does: Groups projects by the technologies they apply or explore.
Hierarchy: Tech field → Specific methods/models → Projects
Why it’s helpful: Ideal for identifying innovation trends, technical overlaps, or evaluating tech adoption maturity.
Domain View
What it does: Groups projects based on problem space within SLB, application area, or impact field (e.g., “Subsurface,” “Grid Modernization”).
Hierarchy: Domain → Product → Projects
Why it’s helpful: Useful for strategists or external partners to see applied impact areas and identify gaps or overlaps in research.
Domain View
What it does: Groups projects based on problem space within SLB, application area, or impact field (e.g., “Subsurface,” “Grid Modernization”).
Hierarchy: Domain → Product → Projects
Why it’s helpful: Useful for strategists or external partners to see applied impact areas and identify gaps or overlaps in research.
Domain View
What it does: Groups projects based on problem space within SLB, application area, or impact field (e.g., “Subsurface,” “Grid Modernization”).
Hierarchy: Domain → Product → Projects
Why it’s helpful: Useful for strategists or external partners to see applied impact areas and identify gaps or overlaps in research.
Team View
What it does: Organizes projects by contributing teams (e.g., AI Lab, Frontend, Robotics).
Hierarchy: Team → Sub teams within a Lab → Projects
Why it’s helpful: Great for internal alignment, performance tracking, and collaboration mapping across the org.
Team View
What it does: Organizes projects by contributing teams (e.g., AI Lab, Frontend, Robotics).
Hierarchy: Team → Sub teams within a Lab → Projects
Why it’s helpful: Great for internal alignment, performance tracking, and collaboration mapping across the org.
Team View
What it does: Organizes projects by contributing teams (e.g., AI Lab, Frontend, Robotics).
Hierarchy: Team → Sub teams within a Lab → Projects
Why it’s helpful: Great for internal alignment, performance tracking, and collaboration mapping across the org.
From passive watching to hands-on practice
Due to the limitation of time, we didn't get to implement all the features. Below are the proposed features that are possible with available data from radar.
What it is like to use a real micropipette?
What it is like to use a real micropipette?
What it is like to use a real micropipette?
Inspiration Prompt:
Inspire user about what question to ask
Presentation of popular questions
Build mental model of how the system work
Inspiration Prompt:
Inspire user about what question to ask
Presentation of popular questions
Build mental model of how the system work
Inspiration Prompt:
Inspire user about what question to ask
Presentation of popular questions
Build mental model of how the system work
Intelligent Search & Filters:
Help user ask better questions by:
Evaluating if the system has enough parameters from user input
Ask follow up questions and give suggestions on refinement
Intelligent Search & Filters:
Help user ask better questions by:
Evaluating if the system has enough parameters from user input
Ask follow up questions and give suggestions on refinement
Intelligent Search & Filters:
Help user ask better questions by:
Evaluating if the system has enough parameters from user input
Ask follow up questions and give suggestions on refinement
Issues with translating it to a digital environment
Issues with translating it to a digital environment
Issues with translating it to a digital environment
The interactive timeline serves as both a filter and a line graph that indicates change in activity over time.
The interactive timeline serves as both a filter and a line graph that indicates change in activity over time.
The interactive timeline serves as both a filter and a line graph that indicates change in activity over time.
Moving from real to digital interaction in low fidelity
Moving from real to digital interaction in low fidelity
Moving from real to digital interaction in low fidelity
See projects with related domains, tech, team easily
See projects with related domains, tech, team easily
See projects with related domains, tech, team easily
From passive watching to hands-on practice
Make it bigger to make it clear:
Using larger motions to better distinguish between stops
Make it bigger to make it clear:
Using larger motions to better distinguish between stops
Make it bigger to make it clear:
Using larger motions to better distinguish between stops
Identified key touchpoints to streamline the device management experience
Identified key touchpoints to streamline the device management experience
Identified key touchpoints to streamline the device management experience
visual parameter
Mapped to
What’s needed to implement
Planet size
effort invested (time or money)
Actual effort metrics based on e.g. time and money
Star Brightness
Impact or visibility
quantitive impact score, or stakeholder priority
Rotation speed (within the trail or self-rotation)
Update frequency within stages, major updates
More granular way of documenting updates in projects
Split off trails
if multiple spin-off projects emerged from an original one
More relationship data to indicate relationships between projects
Satellite (Level 3 Category)
work (tech evaluation, partner, spin off) that supported that specific projects
Evaluation of DataOS
Planet shape
Entity type
Project, tech evaluation, partner
Domain star cluster
Product sub concepts
product line-features
My takeaways
These touchpoints focused on eliminating uncertainty, minimizing manual effort, and guiding users through an efficient device setup process.
These touchpoints focused on eliminating uncertainty, minimizing manual effort, and guiding users through an efficient device setup process.
These touchpoints focused on eliminating uncertainty, minimizing manual effort, and guiding users through an efficient device setup process.
Our approach enables adaptive interfaces through conversational feedback. Users can directly express what they want to track or explore.
By entering their goal or question into a prompt input box, the system performs intent tagging to categorize the query and automatically surfaces the most relevant UI components.
Step 1: Intent Tagging: Understanding the ask
On interpreting the user input side, I defined 5 parameters to tag a questions.
On interpreting the user input side, I defined 5 parameters to tag a questions.
On interpreting the user input side, I defined 5 parameters to tag a questions.
For example ☝️
How did I come up with these parameters? Why?
How did I come up with these parameters? Why?
How did I come up with these parameters? Why?
During the user interview, I asked each interviewee: " If you can ask the galaxy page any question, what would you ask?" and looked for recurring patterns in what they were fundamentally asking for.
While an LLM could infer UI responses directly, defining a parameter tagging framework adds a structured, interpretable layer between user intent and system response. Putting LLM on rails as oppose to letting it range free.
During the user interview, I asked each interviewee: " If you can ask the galaxy page any question, what would you ask?" and looked for recurring patterns in what they were fundamentally asking for.
While an LLM could infer UI responses directly, defining a parameter tagging framework adds a structured, interpretable layer between user intent and system response. Putting LLM on rails as oppose to letting it range free.
During the user interview, I asked each interviewee: " If you can ask the galaxy page any question, what would you ask?" and looked for recurring patterns in what they were fundamentally asking for.
While an LLM could infer UI responses directly, defining a parameter tagging framework adds a structured, interpretable layer between user intent and system response. Putting LLM on rails as oppose to letting it range free.
Step 2: UI Matching: How to Answer with Different UI Components
On the system output side, for each of the potential intent, I have a set of corresponding UI components to answer.
On the system output side, for each of the potential intent, I have a set of corresponding UI components to answer.
On the system output side, for each of the potential intent, I have a set of corresponding UI components to answer.
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For example, for "Discover" intent, an UI component like this be fetched☝️
Step 3: Curate Dashboard Space with Feedback
For hi-fi user testing, we wanted to make an effort to recruit students who had LDs in order to assess the target audiences' needs. To do this, we created a functional needs survey that asked users whether they identified with common needs that are present in students with LDs, such as ADHD and dyslexia.
We were able to test 5 college students, 2 of which self-reported as having light ADHD/executive dysfunction, and 3 students who scored above average on the survey. None of our users had previous experience with micropipetting.
For hi-fi user testing, we wanted to make an effort to recruit students who had LDs in order to assess the target audiences' needs. To do this, we created a functional needs survey that asked users whether they identified with common needs that are present in students with LDs, such as ADHD and dyslexia.
We were able to test 5 college students, 2 of which self-reported as having light ADHD/executive dysfunction, and 3 students who scored above average on the survey. None of our users had previous experience with micropipetting.
For hi-fi user testing, we wanted to make an effort to recruit students who had LDs in order to assess the target audiences' needs. To do this, we created a functional needs survey that asked users whether they identified with common needs that are present in students with LDs, such as ADHD and dyslexia.
We were able to test 5 college students, 2 of which self-reported as having light ADHD/executive dysfunction, and 3 students who scored above average on the survey. None of our users had previous experience with micropipetting.
Proposed Feature:
Proposed Feature:
Proposed Feature:
Superior accessibility, affordability, and gesture transferability compared to competitors
Superior accessibility, affordability, and gesture transferability compared to competitors
Superior accessibility, affordability, and gesture transferability compared to competitors
During the process of brainstorming how to leverage the power of LLM to empower better search, I talked to a start up company called glean, which provides a software that combines all source of information across platforms and domain and fuse them into smart search that's specific to the company.
Reflection
Final User Testing Result: Successful concept transfer and memory reinforcement through gestures
Effectively transfer conceptual learning from digital to real micropipette.
This project taught me the importance of bridging the senses—finding ways to connect tactile, visual, and auditory cues to help users build fluency and confidence in their learning. It was a delicate balancing price, conceptual understanding, and motion precision, but it was rewarding to see how these elements came together to create a seamless connection between digital learning and real-world practice.
This project taught me the importance of bridging the senses—finding ways to connect tactile, visual, and auditory cues to help users build fluency and confidence in their learning. It was a delicate balancing price, conceptual understanding, and motion precision, but it was rewarding to see how these elements came together to create a seamless connection between digital learning and real-world practice.