Introduction
was assigned to analyze three user interview transcripts for a user-centered design course at Flatiron School. The aim was to develop a travel app called “Bon Voyage.” I used the transcripts to identify key insights and information about the target audience, which I then synthesized into meaningful data points that would inform the app’s design. The app would provide information and recommendations about different cities worldwide.
Profile of Participants:
- Christina Wang: 32-year-old copywriter in Chicago. She travels for cultural enrichment, plans trips 2-4 months in advance, and is tech-savvy. She relies on local recommendations and influencers such as Eater blogs, Thrillist’s curated top 10 lists, TripAdvisor, Airbnb, and Yelp reviews. Frustrations include discomfort or safety concerns, frequent tourist traps, unreliable phone service or wi-fi, and inadequate planning, communication, and collaboration.
- Oliver Hammond: 31-year-old motion graphic designer based in New York City. He travels 2-3 times annually and plans trips 3-4 months in advance. He seeks a personalized experience and recommendations from friends, top 10 lists from influencers, airfare booking points programs, and hashtags on Instagram influence him. He is motivated by cultural enrichment and having fun. Frustrations include non-customizable pre-packaged experiences, inaccurate attraction information, non-objective reviews, and poor planning.
- Michael: 34-year-old contractor, filmmaker, and advertiser based in St. Louis. He travels 6-8 times yearly for work and leisure. He is budget-conscious and seeks culturally significant landmarks, information on nearby businesses, and promotional deals. He uses travel apps and friends’ recommendations. He seeks more accurate information on attractions, businesses, dietary restrictions, and non-biased reviews.
Analysis Process
I used thematic analysis to read the transcripts and identify patterns and themes. I then coded the data, organized it, synthesized the findings, quantified them, visualized the results, and made conclusions and recommendations. I used Miro, a whiteboard tool, to help illustrate my discoveries. The ultimate goal was to create the best user experience possible for the “Bon Voyage” app through a user-centered design approach.
Challenges:
The main challenge during the project was the limited three-day time frame to complete the assignment. The school did not provide instruction on thematic analysis. Still, I taught myself using a Google Sheets spreadsheet with Miro. I also learned the basics of affinity mapping and applied them in my submission.
Coding the Transcripts
I read the transcripts and noted quotes and themes related to travelers’ goals, motivations, frustrations, influences, and behaviors. I found taking notes directly on the worksheet challenging, so I used a color-coded spreadsheet matrix to categorize the information.
A psychographic refers to a person’s personality, values, attitudes, interests, and lifestyle. I focused on five psychographics in this project: goals, motivations, frustrations, influences, and behaviors. I assigned codes or labels to the quotes and themes, which helped me organize the data according to each psychographic.
I created a tab for each user interview and assigned each a color. I also added columns for the four demographics and the five psychographics. Then, I placed the relevant data under the appropriate columns.
In hindsight, highlighting the psychographics in the transcripts would have been more efficient before using a matrix to organize the information.
Organizing the Coded Data
After somewhat coding the transcripts, I moved on to the next stage of the thematic analysis: organizing the coded data. I already had a matrix, so I used affinity mapping to arrange the coded data meaningfully and identify patterns and relationships. Affinity mapping involves grouping related ideas and concepts on a visual board.
Flatiron School’s assignment only suggested using the Miro app to synthesize findings into quantitative data; however, they didn’t cover coding, segmentation, or affinity mapping at that stage. I created a semblance of an affinity diagram in Miro, recording one idea per sticky note and using a similar color for each note corresponding to the color of the user interview’s spreadsheet tab.
Re-arranging the data allowed me to identify relationships and connections, which I summarized into labels of coded language or codes. However, this step was challenging because of the subjective nature of creating new codes within the overall demographic and psychographic categories. My interpretation could differ from that of the instructor or another researcher.
Since the user persona assignment coincided with this thematic analysis, learning empathy mapping may have proved a practical framework in addition to affinity mapping.
Empathy mapping is a user-centered design technique that helps designers understand their target audience and create a visual representation of their thoughts, feelings, behaviors, and motivations. An aggregate empathy map of all three users could have helped segment the data and deduce new codes.
Analyzing the Coded Data
The next step was analyzing the coded data to gain deeper insights into the user experience. By examining the patterns, themes, and relationships, I discovered new understandings that I may have missed.
I used my attempts at creating empathy and affinity maps, both singular and aggregated, to turn the codes into meaningful insights and form informed hypotheses. These insights and hypotheses guided my design decisions and helped to enhance the user experience.
Synthesizing the Findings
To summarize the findings, I quantified the key insights by counting the number of interview subjects for each discovery and presented the information in bullet points as instructed: I formatted them according to the assignment guidelines. For example, 60% of the interview participants are from {insert location}.
However, upon reflection, using percentages with a small sample size (3 participants) may not accurately reflect statistical significance. It’s better to use the amount-of-total method (e.g., ‘2 out of 3 participants…’) to illustrate the sample size’s relationship patterns.
Visualizing the Results
I created a visual representation of my aggregated empathy/affinity map using a screenshot from Miro. I included this visual aid and the spreadsheet in the word document deliverable to showcase my process and findings. Although it was not required, it helped enhance my understanding and presentation of my results.
Conclusions and Recommendations
n this section, I summarized the key insights from my research into bullet points. The main findings are:
- 66.67% of the interviewees are in their early to mid-thirties, work in advertising or a creative field, and live in urban areas in the US. They all own pets and are tech-savvy, frequently using their phones for various purposes. They also enjoy traveling and plan trips three months in advance on average, seeking to maximize their time.
- The motivations for traveling among the participants include cultural enrichment, experiencing local daily lifestyles, avoiding FOMO, making connections, and having fun. They seek recommendations from locals, using sources such as Eater blogs, curated top 10 lists, TripAdvisor, Airbnb, The New York Times, Yelp, and friends’ recommendations.
- The participants have faced challenges such as discomfort and lack of safety, tourist traps, unreliable phone service/wi-fi, poor planning, communication, collaboration, and pre-packaged experiences that the user can’t customize. They need access to accurate information on attractions and businesses, non-biased reviews, and the consideration of dietary restrictions.
- It’s crucial to incorporate personalization, customization, and season-appropriate recommendations in the design of travel-related products and services to meet the needs and expectations of the target audience. I must also consider budget consciousness and airfare booking points programs.
Based on these findings, I can incorporate these insights into the design process of travel-related products and services to improve the user experience.
Reflection on the Project’s Role within Flatiron School
The user research conducted for the mobile travel app project was crucial in understanding the target audience’s needs, behaviors, and motivations. If done before or in tandem with competitive analysis and secondary domain research, the interviews’ primary research would better help me conduct relevant market analysis and position my product in the market.
While the boot camp offered an opportunity to learn, I was disappointed with the teaching method as it lacked the promised hands-on and apprenticeship-like approach. Learning particular frameworks would have been more effective in helping me reach my full potential as a UX design student than merely providing curated internet resources.
Regardless, the boot camp helped me identify areas where I lacked knowledge and forced me to improve through self-study and seek additional resources. I also developed my technical and soft skills, such as problem-solving, time management, and self-motivation, by teaching myself a professional workflow process of thematic analysis and affinity mapping.
Evaluation and Grading
The instructor evaluated my work based on its thoroughness and insightfulness. Thoroughness measured if I had thoroughly read the interviews and gathered all relevant insights about the target audience. Insightfulness assessed the quality of quantifying the information and the presence of patterns in the user’s goals, motivations, frustrations, influences, and travel behaviors.
Flatiron divided the grading scale for the user interview analysis and synthesis into five categories, ranging from 0 to 5 points. If I received a score of 1 or 2, I was required to resubmit the assignment after considering the instructor’s feedback. The focus was on the feedback, not just the score, and I was encouraged to use the feedback to improve my work, even if I passed.
Instructors rarely gave out a score of 5, as they believed it represented senior-level work, a ranking at which they didn’t consider any enrolled students. Due to the intensive nature of the program, students had limited time for iteration.
For my user interview synthesis and analysis assignment, I received a score of 4 out of 5. The instructor praised my ability to gather valuable insights from the interviews. However, the instructor also provided suggestions for improvement, such as including gender and relationship status in the top-level demographics, separating different interviews onto different pages, and presenting quantitative data with a storytelling paragraph format instead of bullet points. Despite these suggestions, the overall feedback was positive, and the instructor expressed excitement about my final persona.
I had two main issues with the instructor’s feedback on my thematic analysis assignment. Firstly, the instructor deducted points for not including gender and relationship status in the template provided by Flatiron School, even though I had included this information in my Google Sheets spreadsheet and Miro visual synthesis. Secondly, I was penalized for not adding page breaks between interviews in my deliverable, even though Flatiron did not specify this in the grading rubric. I also needed clarification about the format for presenting quant data, as the worksheet instructions stated that students should write it in a paragraph. Yet, the workflow video instructions said to show it in bullet points.
My second issue was that the instructor graded me for not adding page breaks between interviews in the deliverable. However, Flatiron did not specify this formatting in the rubric. Flatiron should have provided the template formatted differently if this was an expectation. Or they should have added a grading rubric for visual design. Instructors downgraded me for not going above and beyond and not just providing what Flatiron requested in the worksheet template.
I reached out to the instructor to seek a better understanding of the grading criteria. How could I use his feedback to improve my score of 4 to 5? Some areas where he devalued me needed to be reflected in the grading criteria or covered in the lesson videos or readings. However, the instructor didn’t seem open to my inquiries and instead told me not to focus on the number grade as much as the feedback.
Reflecting on this advice, I understand that the grade and feedback are inextricably linked. Gaining a clear understanding of the expectations and requirements is crucial to excelling in future assignments and iterations and reaching senior-level proficiency.
