GloMirror is a smart mirror prototype designed to deliver a personalized experience tailored to help make the user's unique beauty needs and routine easier. Working collaboratively with a team of four, we utilized a design process called Goal-Directed Design (GDD) to develop this beauty smart mirror, grounded in extensive research. In order to effectively address both the needs of our users and business requirements, GloMirror was guided by the following objectives:
Team Lead, Research, User Interface, Interaction
Goal-Directed Design
Figma, FigJam, Illustrator, Photoshop
13 Weeks (January - April 2023)
For my capstone project in spring of 2023, we were tasked with utilizing Goal-Directed Design (GDD)—which we read from About Face (4th Edition) by Alan Cooper—to design a prototype of our choice.
My peers and I have designed mobile prototypes, and for our capstone project, we wanted to create something that would stand out. Additionally, as technology continues to get more advanced, normal everyday objects are starting to have a technological aspect being integrated with them. Thus, inspired by the integration of technology with everyday objects, I pitched an idea to my classmates of creating a beauty smart mirror called “GloMirror”. After several people expressed interest in this project, I became the team leader.
As team leader, I coordinated meetings and interviews, facilitated workflow, tracked deadlines, and provided support to my team. In collaboration with my peers, we designed a prototype that aimed to create a beauty smart mirror that solves a real problem for users.
To ensure our product was user-centered, we utilized the Goal-Directed Design methodology. This approach allowed us to identify our users' goals, needs, and motivations prior to creating the product, ensuring that it was designed with the user in mind. Hence, this process page outlines the different stages of GDD, how it has been adapted to fit the time constraints of our college course, and how we created this chain of evidence where our research feeds into each subsequent stage.
In the Research phase of GDD, designers gather essential information about the project, including stakeholder expectations, user goals, relevant contexts, how the project will be used (in this case, the smart mirror), environmental considerations, and similar existing smart mirrors. This phase is critical for GDD because the insights gathered inform design decisions for the mirror and provide a foundation for traceability back to the research results.
The Research phase encompasses a Kickoff Meeting, Literature Review, Competitive Audit, Stakeholder Interviews, Subject Matter Expert (SME) Interviews, and User Interviews, ensuring a comprehensive understanding of the project. By conducting thorough research, we were able to make informed design decisions that align with the user's needs and goals.
The official kickoff meeting is typically held to establish a project by meeting with business stakeholders; however, as this is a class project, our team did not have the opportunity to meet with any potential stakeholders. To simulate a real kickoff meeting, we used a worksheet provided by our instructor to put ourselves in the position of a stakeholder. This allowed us to create a problem statement with various assumption statements, which we used to launch our project. During a detailed discussion about our smart mirror’s goals and future projections, we utilized the kickoff meeting worksheet to guide us.
The Literature Review is a critical research step in GDD, providing designers with a thorough understanding of the product's context. It helps the team conduct effective interviews with Subject Matter Experts (SMEs) and stakeholders, and gain better knowledge throughout the design process.
During the Competitive Audit phase of GDD, we analyze and compare existing competitors in the product domain. This process helped us identify potential competitors in the beauty and smart mirror industry and allowed us to incorporate features that competing applications lacked. We reviewed four smart mirrors. We then compared them side-by-side in a chart that illustrated several important features. This information was taken into consideration during the design process to ensure that our product had the necessary features to stand out in the market.
Competitive Audit Chart Comparing Various Features Across Competitors
We designed two different charts. One of them illustrates whether or not the mirror has the feature, and the second chart focuses on how effective that feature was implemented into the mirror. Color-coding was used to determine the effectiveness of each feature. Green means the feature is effective, yellow means it is somewhat effective, and red means it is not effective at all.
As GloMirror is a class project, we were not able to conduct stakeholder interviews; however, we learned that stakeholder interviews are a valuable opportunity to gather more specific information from those with authority or responsibility for the product. These interviews can cover topics such as the product vision, budget constraints, technical limitations, and stakeholder perceptions of the users. If we were able to conduct stakeholder interviews, some example questions we would have asked include:
Although not required for the class, we believed conducting a SME interview was essential. A SME is someone with extensive knowledge in a specific field, and we sought to gain a deeper understanding of both the technological aspects of a smart mirror and the beauty domain. As a result, our team conducted three SME interviews, two of which had experience in the beauty domain and one with experience in technology and working with smart mirror use cases.
For one of our SME interviews, we spoke with Sandeep Mehta, a Senior Solutions Architect at Amazon Web Services. We learned about the two types of smart mirrors: general and specific use cases. Mehta explained that general use cases include basic features like checking the weather, viewing the calendar, etc. Specific use cases, on the other hand, are tailored to a particular use and have features that cater to that use. Mehta gave an example of a smart mirror she worked on with optometrists that had augmented reality (AR) features, which allowed users to see what glasses would look like on their face before purchasing them. Overall, Mehta's insights were invaluable, and with the information she provided us, it guided us to include general features for our smart mirror (i.e., weather, time, etc.). Our other SME interviews were just as informative in guiding our design decisions, but instead, it was catered towards beauty such as adding a lighting feature with different temperatures.
To begin user interviews, we needed to identify potential users and determine if they were suitable for our research. To achieve this, we developed a persona hypothesis, which involved brainstorming and identifying user types, their goals, needs, environment, and behavior. We started the process by setting up questions to define our ideal persona(s).
Our persona hypothesis helped us create specific research questions and identify potential participants for our user interviews. We conducted a total of eight interviews, both in-person and virtually using Zoom and Discord. To ensure the interviews were effective, we followed guidelines such as avoiding fixed questions, assuming the role of an apprentice, using open-ended and closed-ended questions, prioritizing goals over tasks, and avoiding leading questions.
After conducting the user interviews, we identified overlapping characteristics among them and created affinity maps for each interview. These maps helped us group key observations, behaviors, and thoughts while also identifying common themes and patterns across all interviews. The result was a set of clusters of sticky notes that represented the main takeaways from each participant.
During our analysis of the affinity maps, we observed that most participants desired a lighting feature due to the different effects of various lightings had on their makeup. In addition, the majority of participants preferred to use media while doing their makeup, such as listening to music or watching YouTube tutorials. Although we discovered some common themes, there were also differences in preferences, such as some participants being receptive to product recommendations while others felt like they were being pressured to purchase something. Overall, we gained valuable insights into the participants' characteristics, thoughts, and behaviors during the user interviews.
In the Modeling phase, we translate significant behavior patterns from our research into a persona. This creates a narrative for our users, helps stakeholders visualize our target audience, and keeps design teams focused on designing with our users' intentions in mind.
Our team analyzed the data from the User Research Interview phase and identified shared patterns of behavior among participants using the affinity maps, notes, and observations we collected.
We analyzed 26 different behavioral variables and created a scale for each of them. Next, we mapped each of our participants on a behavioral variable scale to identify any significant behavior patterns. After noticing a pattern between our participants, we categorized them into two groups based on their makeup and skincare knowledge: beginner (green) and intermediate (blue). Using these patterns, we identified characteristics and goals for each group, resulting in one user type with two personas. With this information, we synthesized personas for our product.
An Example of Mapping Our Participants
Our team created two personas using data from our interviews to model user behavior. These personas provide a simplified representation of our research and enhance our understanding of our users’ thoughts and actions.
Now, Michaela, the primary persona, is the outgrowth of the green circles above, and she represents beginners in makeup and skincare, whereas Tatiana represents the more experienced and is the outgrowth of the blue circles. Michaela was chosen as the primary persona due to her alignment with the main behavior patterns identified. While the beauty smart mirror addresses Michaela's goals, it also satisfies some of Tatiana's needs. As a result, our team believes the mirror can help both personas without disrupting their experiences.
In the Requirements phase, we created a context scenario and a list of requirements to determine what our primary persona, Michaela Lacey, needs to successfully meet her goals. By addressing Michaela's goals, we can also fulfill some of Tatiana's needs as our secondary persona. Our team is confident that this mirror can serve both personas without disrupting their user experiences.
Our team developed a context scenario for our primary persona, Michaela, which outlines her typical use of GloMirror, and how it meets her needs. We held a brainstorming session to explore Michaela's motivations, actions, and thought process. As the team leader, I facilitated the meeting, and together we created the scenario.
Our context scenario describes Michaela's typical day, starting with her getting ready for work and ending with her preparing for a party. It shows how she uses GloMirror's features to assist in her beauty routine. When Michaela notices a new pimple on her face, she uses the skin analysis feature to find a solution. she also uses the weather feature to help her decide what type of makeup to wear. While doing her makeup, she listens to music through the mirror. Later, when she's getting ready for the party, she uses the makeup assistance feature and lighting to achieve her desired look.
After putting ourselves in our users' shoes, we identified requirements that our primary user, Michaela, would need for our beauty smart mirror. We used our context scenario and requirements list as the foundation for our prototype framework. Our general requirements include a home screen, skin analyzer, makeup assistance, lighting feature, magnifying feature, ingredient recommendations, problem area tracker, media casting, settings, and onboarding.
Once the requirements for our persona were established, we moved on to the Frameworks phase of our project. Here, we created pathways to help our persona achieve their goals, using a low-fidelity prototype. Once we determined the layout of the app, we then created a high-fidelity prototype of our wireframe.
To prepare for prototyping the smart mirror, we first created a low-fidelity wireframe using FigJam, a digital whiteboarding tool. This wireframe allowed us to establish the information architecture and layout of the mirror while referencing our context scenario and requirements list to identify necessary screens. Within the wireframe, we considered how our personas would interact with the mirror and mapped out the likely paths they would take.
We identified our primary persona's key path scenario by utilizing the context scenario. The key path scenario, represented by the pink line, illustrates the primary persona's most common way of interacting with the mirror on a daily basis. In contrast, the blue lines represent validation scenarios, which are secondary tasks or less frequently used paths that the user may take with the mirror.
After completing our wireframe, we moved on to building our prototype in Figma. Our plan included dividing the prototype into sections, assigning each team member a specific part to work on, establishing a design system, and implementing an 8pt grid that will be used as our redlining. After this phase, we moved into Refinement, where we conduct usability tests to further enhance the prototype.
To maintain a consistent aesthetic throughout the mirror, I collaborated with my team members and we created a design system with various headings and colors.
The following are some of the screens and sections that I’ve designed for the prototype:
Redlining is a crucial approach in the handoff process to developers that involves documenting the elements of a design with distances shown between content. My group used an 8pt grid ratio to maintain consistent spacing throughout the project.
After creating our prototype, we conducted eight usability tests. To ensure optimal results, we followed Jakob Nielsen's recommendation that 5 users provide an 85% return of the findings to be uncovered. Further testing may result in repeating findings.
We utilized various methods during our usability tests including the think aloud protocol (TAP), A/B testing, and assigning task-based scenarios to each participant. As we conducted the tests, we carefully documented the feedback and made necessary modifications to the smart mirror prototype. Through this iterative process, we were able to make significant improvements to enhance the overall user experience.
Scenario: Our research revealed that beauty smart mirrors should include both a skin analysis and a skin tracker. The skin analysis would evaluate the user's skin and identify problem areas, while the skin tracker would monitor changes in the user's skin over time.
Problem: We observed that many of our users were confusing the skin analysis and skin tracker screens, and were anticipating to find solutions and explanations for their skin on the skin analysis screens instead of the skin tracker.
Solution: As a team, we decided to revise the design of our skin analysis and tracker screens due to user confusion. Our new approach includes displaying the user's most recent skin analysis results in the skin analysis screen, with potential solutions for identified problem areas. The tracker feature functions as a calendar, allowing users to monitor changes in problem areas over time and take photographs of those areas.
As the course came to an end, we were proud of the final product that we created together. We challenged ourselves by building a smart mirror instead of our usual websites and apps. As the team leader, I learned the value of effective communication and building relationships with my team members. This experience highlighted the importance of thorough research in creating a product that delivers an enjoyable user experience. It was gratifying to work with an enthusiastic team that evolved our product from research to prototype. Overall, this project was a rewarding experience.
Aside from the importance of communication and building relationships with my team members, I also gained other valuable insights: