MS3 - Moviles-SEC-2-G25/Wiki GitHub Wiki

1. Brainstorming Process

1. Objective of the Brainstorming Phase

The purpose of this new brainstorming phase was to transform the insights obtained from the interview, What–How–Why situations, and Customer Journey Map into possible solutions for the selected problem:

Side-quests: Breaking Out of the Routine

People often struggle to break out of their routines and find the motivation to try new things. Although they may be interested in exploring different activities, remaining inside their comfort zone usually requires less effort, planning, and social exposure.

The brainstorming process followed a user-centered Design Thinking approach:

Empathize — Understand actual behaviors and motivations.
Define — Identify the main barriers behind routine inertia.
Ideate — Generate multiple possible solutions using divergent thinking.
Converge — Compare, classify, and combine the most promising ideas.
Prototype — Define a final concept that can later be tested with users.

2. Empathize Phase — Interview Insights

The process started by analyzing the interview conducted with Camilo Sánchez, a 22-year-old student.

The interview revealed several important behaviors:

Around 90% of his free time is spent repeating familiar activities.
He is willing to try new activities when someone else has already organized the plan.
Planning and initiating a different activity by himself creates additional friction.
Unfamiliar social environments can prevent him from accepting a new experience.
Strong personal interest can overcome this social barrier.
Small and simple challenges are more attractive than complex activities that require significant time or preparation.
Sharing achievements is not necessarily a primary motivation; the experience itself can be enough.

These findings suggested that the problem is not simply a lack of activities. A major opportunity is to reduce the effort required to discover, select, and start something different.

These insights were documented and later validated through empathy maps and journey mapping

3. Situation Analysis — What, How, Why, Who

The interview findings were structured into four situations using the What–How–Why–Who method.

Situation 1 — Repetitive Free-Time Routine

What:
Camilo spends most of his free time repeating the same activities.

How:
After work, he usually chooses familiar activities such as watching movies, talking to his sister, or playing basketball.

Why:
These activities require almost no planning or uncertainty and represent his immediate comfort zone.

Who:
Camilo is a 22-year-old student with a highly repetitive free-time routine. He tends to prefer familiar activities that require little planning and allow him to remain within a comfortable and predictable environment.

Situation 2 — Joining Externally Organized Plans

What:
Camilo sometimes participates in activities outside his routine.

How:
He usually joins when another person has already proposed and organized the activity.

Why:
Removing the planning and coordination effort significantly lowers the barrier to participation.

Who:
Camilo and his close friends are involved in this situation. Camilo is open to new experiences, but he tends to rely on his social circle to initiate and organize alternative plans before deciding to participate.

Situation 3 — Social Barrier

What:
Camilo rejects some opportunities to try unfamiliar activities.

How:
He avoided a mountain-climbing activity because it involved people he did not know.

Why:
The combination of an unfamiliar activity and unfamiliar people created too much social friction.

Who:
Camilo and a group of unfamiliar people are involved. Camilo has a small and close social circle, so interacting with strangers while simultaneously trying an unfamiliar activity can make him feel outside his usual environment and reduce his willingness to participate.

Situation 4 — Intrinsic Interest Overcomes Friction

What:
Camilo sometimes voluntarily tries completely new experiences.

How:
He is willing to enter unfamiliar environments when the activity strongly interests him.

Why:
Personal curiosity can become strong enough to overcome uncertainty and social discomfort.

Who:
Camilo is the main person involved, potentially interacting with unfamiliar people or environments. Although he usually prefers familiar social settings, he becomes more adventurous and willing to take risks when an activity strongly matches his personal interests.

These situations helped identify the main design opportunities:

Reduce planning effort.
Reduce choice overload.
Match activities with personal interests.
Allow different levels of social exposure.
Make the first step extremely easy.

4. Customer Journey Map Analysis

A Customer Journey Map was created to explore how a user could move from routine inertia to trying new activities.

The journey was divided into five stages:

Spark of Interest and Inertia
Quest Discovery and Choice
Quest Execution and Experience
Post-Quest Reflection and Loot
Integration and Behavior Change

The map identified important needs and barriers throughout the experience.

Stage 1 — Spark of Interest

Main barriers:

“I am too tired.”
“I will do it later.”
Routine habit inertia.

Opportunity:

Provide a small, playful, low-commitment prompt that makes starting feel easy.

Stage 2 — Quest Discovery

Main barriers:

Too many options.
Choice paralysis.
Vague descriptions.
Complex interfaces.

Opportunity:

Show a small number of clearly categorized and relevant side-quests based on context.

Stage 3 — Quest Execution

Main barriers:

Unexpected difficulty or cost.
Social anxiety.
Physical or environmental limitations.

Opportunity:

Provide simple instructions and adapt activities to the user's situation.

Stage 4 — Reflection and Rewards

Main barriers:

Rewards may feel meaningless or childish.
Lack of feedback.
Lack of perceived progress.

Opportunity:

Use meaningful reflection, progress tracking, and optional achievements instead of rewards only for their own sake.

Stage 5 — Long-Term Integration

Main barriers:

Novelty may disappear.
Too much planning.
Lack of long-term motivation.

Opportunity:

Build an explorer identity through personalized progress and continuously refreshed experiences.

5. Define Phase — Problem Framing

After combining the interview, situations, and journey map, the problem was reframed into the following design question:

How might we make trying new experiences easy, personally relevant, and playful enough that users can break routine inertia without requiring significant planning or social effort?

This framing focuses on four main needs:

Low friction
Personal relevance
Small achievable actions
Playful motivation

6. Divergent Thinking — Idea Generation

The ideation phase initially followed a divergent thinking process.

Each team member independently generated possible solutions based on the findings from their interviews, situations, and journey maps. No ideas were rejected during this stage.

The rules followed were:

Prioritize quantity before evaluation.
Avoid criticism during idea generation.
Explore both realistic and unconventional ideas.
Build solutions from observed user needs.
Avoid limiting ideas according to current technical constraints.

All ideas were then placed on a shared whiteboard so they could be reviewed together.

Evidence

7. Solutions Generated for Breaking Out of the Routine

From the interview and research related to this problem, five main solution concepts were generated.

1. Playful Challenge Application

An application that periodically gives users small and playful challenges that encourage them to try something different.

Example:

“Take a different route home today.”

2. Side-Quest Discovery Platform

A platform containing different categories of optional side-quests that users can explore according to their interests, available time, and desired difficulty.

Possible categories:

Food
Sports
Creativity
Nature
Social
Exploration
Learning

3. Shared Discoveries and Challenges

Users could optionally share completed activities or discoveries with friends, allowing one person's experience to inspire another person's next side-quest.

4. Long-Term Quest Challenges

The application could create longer challenges such as:

“Complete 10 different side-quests this month.”

This would encourage users to progressively introduce more variety into their routines.

5. Community Side-Quests

Users could participate in challenges linked to predefined public locations, events, or communities, creating game-like opportunities to interact with other people.

This idea directly explores the social barrier identified in the interview, but requires careful design because unfamiliar social situations can also discourage participation.

8. Convergent Thinking — Idea Classification

After the divergent stage, the team performed a convergent thinking process during class.

Instead of keeping every idea as an independent solution, the ideas were discussed and organized according to four categories taught in class:

The Rational Choice

The solution that best balances user value, feasibility, and direct connection to the identified problem.

Selected concept:
Side-Quest Discovery Platform

It directly reduces planning effort while allowing users to choose activities according to their interests and availability.

The Most Likely to Delight

The idea most likely to create an enjoyable and memorable user experience.

Selected concept:
Playful Challenge Application

Receiving unexpected but achievable mini-challenges could introduce spontaneity into an otherwise repetitive routine.

The Darling

The concept the team finds particularly attractive because of its potential to create deeper engagement.

Selected concept:
Long-Term Quest Challenges

Progression systems and collections of completed quests could help users gradually build an identity around exploration.

The Long Shot

A more ambitious or uncertain idea with interesting potential but higher implementation or adoption risk.

Selected concept:
Community Side-Quests

Connecting users through real-world challenges could create unique experiences, but the interview showed that unfamiliar social environments can also become a significant barrier.

Sharing as a Supporting Feature

The Shared Discoveries and Challenges idea was not selected as the core concept because the interview indicated that sharing is not necessarily a strong motivation.

Instead, sharing was retained as an optional supporting feature.

Evidence

9. Evaluation Criteria

The ideas were compared using the following criteria:

Criterion	Description
User Value	Does the idea solve a need found in the interview or journey map?
Friction Reduction	Does it make trying something new easier?
Personal Relevance	Can the experience adapt to individual interests?
Feasibility	Can the concept realistically be implemented in a mobile application?
Engagement Potential	Can it motivate users to return without becoming repetitive?
Scalability	Can more activities, categories, or contexts be added over time?

The Side-Quest Discovery Platform performed strongly because it addresses the main problem while also allowing other ideas to become features inside the same product.

Idea Evaluation Matrix

The main ideas generated during the brainstorming process were evaluated using a 1–5 scale across five criteria: Feasibility, Impact, Engagement, Personalization, and Scalability.

Idea	Feasibility	Impact	Engagement	Personalization	Scalability	Total Score
Playful Challenge Application	5	4	5	3	5	22
Side-Quest Discovery Platform	4	5	5	5	5	24
Shared Discoveries and Challenges	4	3	4	3	4	18
Long-Term Quest Challenges	5	4	5	4	5	23
Community Side-Quests	3	4	5	4	4	20

Evaluation Criteria

Feasibility: How realistic the idea is to implement as a mobile application.
Impact: How strongly the idea addresses the problems identified during the research.
Engagement: How likely the solution is to motivate users to participate and return.
Personalization: How well the experience can adapt to individual interests, preferences, and comfort levels.
Scalability: How easily the solution can grow by adding new users, categories, quests, or contexts.

Evaluation Result

The Side-Quest Discovery Platform obtained the highest score (24/25) because it combines strong user impact, engagement, personalization, and scalability while remaining technically feasible.

The Long-Term Quest Challenges concept also scored highly (23/25), making it a strong complementary feature for maintaining motivation and progression over time.

For this reason, the Side-Quest Discovery Platform was selected as the core solution, while elements from the other ideas were incorporated as supporting features.

10. Final Selected Solution

The final concept selected was: Side-quests: Discovery Platform

The application provides users with small, personalized, game-like activities designed to introduce variety into everyday life without requiring significant planning.

Instead of asking users to independently search for something new, the application reduces the effort of deciding:

“What could I do differently today?”

A typical interaction could be:

The user opens the application.
The system identifies their available time, interests, and preferred difficulty.
A small set of side-quests is suggested.
The user selects one.
The app provides simple instructions.
The user completes the activity.
A short reflection or progress update is recorded.
Future quests improve according to previous preferences.

The final concept therefore combines elements from several brainstorming ideas rather than selecting only one Post-it:

Side-Quest Platform → Core experience.
Playful Challenges → Engagement mechanism.
Long-Term Quests → Progression.
Sharing → Optional social feature.
Community Quests → Possible future extension.

This convergence step transformed multiple isolated ideas into one coherent product concept.

11. Smart Features

Smart features can improve the experience by reducing the exact types of friction identified during the research.

The objective is not to include AI simply as an additional feature, but to use intelligent behavior where it directly improves the user journey.

11.1 Smart Quest Recommendation

The application could learn from:

User interests.
Previously completed quests.
Skipped quests.
Preferred categories.
Available time.
Preferred level of social interaction.

The system could then recommend quests with a higher probability of being accepted.

Example:

“You have 25 minutes free and usually enjoy sports. Try shooting 20 basketball free throws from a position you normally avoid.”

11.2 Context-Aware Quest Filtering

The app could automatically reduce irrelevant options using contextual information such as:

Available time.
Location.
Time of day.
Quest duration.
Indoor/outdoor preference.
Desired difficulty.

This directly addresses the choice paralysis identified in the Journey Map.

11.3 Adaptive Difficulty

The system could progressively modify challenge intensity according to previous behavior.

For example:

Level 1:
Try a different drink.

Level 2:
Visit a café you have never visited.

Level 3:
Attend a small event related to one of your interests.

This allows users to move outside their comfort zone gradually instead of immediately confronting high-friction challenges.

11.4 Smart Social Comfort Settings

Because social anxiety emerged as an important barrier, the application could personalize quests according to the user's preferred social exposure:

Solo.
With close friends.
With any friend.
Small public interaction.
Community activity.

The system could progressively suggest more socially challenging quests only if the user is comfortable doing so.

11.5 Personalized Learning from Feedback

After completing or skipping a quest, the app could ask for extremely simple feedback:

👍 I would do something like this again
👎 Not for me

This information could improve future recommendations without requiring long questionnaires.

These smart features were derived directly from the barriers identified in the interview, What–How–Why situations, and Customer Journey Map, particularly planning friction, choice overload, social discomfort, and the need for personally relevant challenges.

12. Validation Against the Customer Journey

The final solution was also mapped against each stage of the Customer Journey.

Journey Stage	User Need	Solution
Spark of Interest	External inspiration with low commitment	Small personalized quest notification
Quest Discovery	Avoid choice overload	Smart recommendations and filters
Quest Execution	Clear and simple guidance	Step-by-step quest instructions
Reflection & Loot	Meaningful feedback	Reflection, achievements, and progress
Behavior Change	Maintain novelty over time	Adaptive recommendations and explorer progression

This ensures that the selected concept addresses the complete experience rather than only the initial discovery stage.

13. Application of Concepts Taught in Class

The new brainstorming process explicitly applied the following concepts:

Empathy-driven design
What–How–Why analysis
Customer Journey Mapping
Problem framing
Divergent thinking
Convergent thinking
The Rational Choice
The Most Likely to Delight
The Darling
The Long Shot
Evidence-based ideation
User-centered feature prioritization
Smart and adaptive features

The main improvement compared with the previous brainstorming exercise was making the convergence stage explicit.

The process did not end after generating multiple Post-its. Instead, the team:

Generated alternatives.
Compared their potential.
Classified them using the four ideation categories.
Identified strengths and risks.
Combined complementary ideas.
Selected one final product direction.

14. Conclusion

The brainstorming process moved from user evidence to a concrete solution rather than starting with a predetermined application idea.

The interview showed that users may want to try different experiences but remain inside their routines because familiar activities require less planning, uncertainty, and social effort.

The situations and Journey Map transformed these observations into design opportunities, while divergent brainstorming generated several alternatives.

The convergence process then identified the Side-Quest Discovery Platform as the strongest foundation and incorporated the most valuable elements of the other ideas.

The resulting concept, Side-quests: Breaking Out of the Routine, combines:

Low-friction discovery.
Personalized challenges.
Playful interaction.
Gradual difficulty.
Progression.
Optional social experiences.
Smart recommendations.

The final solution therefore addresses the root causes identified during the research while creating a flexible foundation for future prototyping and user validation.

2. Decision and Convergence Process

2.1 From Four Problems to One

During MS2, the team explored four different problems instead of committing to a single problem from the beginning:

Side-quests: Breaking Out of the Routine
Wellness Made Fun
Content Centralization
Skip the Line Campus Lunch Pickup

Each problem was explored through interviews and later analyzed using the What–How–Why methodology. The team also developed Journey Maps for selected problems and used the findings obtained during the research process to identify behaviors, barriers, needs, and design opportunities.

The purpose of the convergence process was to compare the four alternatives and select one problem that could provide a strong foundation for the following stages of the project.

2.2 Analysis of the Four Problems

Side-quests: Breaking Out of the Routine

The research showed that wanting to try something different does not necessarily mean that a person will actually do it.

During the interview related to this problem, the participant reported spending approximately 90% of his free time doing familiar activities. He also explained that he is more likely to participate in a different activity when somebody else has already organized the plan, suggesting that planning and initiation can become important barriers.

The interview also revealed an interpersonal barrier. The participant described rejecting an unfamiliar activity when it involved people he did not know. However, strong personal interest in an activity could motivate him to overcome that discomfort.

Finally, the participant reacted more positively to small, low-commitment challenges than to complex challenges requiring considerable time or preparation.

These findings suggested that the opportunity was not simply to provide more activities. The solution could instead reduce the effort, uncertainty, choice, and social friction involved in starting something different.

Wellness Made Fun

The research related to this problem showed that university students can experience emotional overload and already use different strategies to regulate stress.

The interview suggested that dedicated wellness applications do not only compete with other wellness applications. Familiar everyday tools that students already use, such as music applications, can become the preferred option because they require very little effort during stressful moments.

The problem presented opportunities related to immediate support, personalization, low-friction interactions, self-care activities, and access to professional resources.

At the same time, this domain would require particularly careful consideration of privacy, trust, professional validation, and the limits of the support that a mobile application should provide.

Content Centralization

The interviews related to this problem showed that users save content across multiple platforms and can later experience difficulties finding or organizing it.

The research also revealed that saved content does not always have enough perceived value for users to invest additional effort in organizing it. Manual organization can therefore become another source of friction.

Participants reacted more positively to concepts such as automatic organization, centralized retrieval, and reduced manual effort.

This problem presented a clear opportunity around automation, search, retrieval, and organization of fragmented digital content.

Skip the Line Campus Lunch Pickup

The interviews provided direct evidence that cafeteria waiting times can influence students' decisions.

Participants described losing a considerable part of their available break waiting to order and receive food. This could result in choosing a less desirable alternative, changing restaurants, or avoiding the cafeteria altogether.

The interviews also showed that students value solutions that reduce waiting time and allow them to make better use of limited periods between academic responsibilities.

This made the problem concrete and observable and revealed opportunities around pre-ordering, payment, food availability, scheduled pickup, and waiting-time reduction.

2.3 Comparison Criteria

After analyzing the evidence collected for the four problems, the team reflected on the alternatives using the following criteria to make the convergence rationale explicit:

Criterion	Description
User Relevance	Whether the research revealed a meaningful behavior, barrier, or unmet need.
Design Opportunity	Whether the problem allows different possible solutions instead of immediately implying a single feature.
Context-Awareness Potential	Whether variables such as time, location, preferences, or the user's situation could meaningfully modify the experience.
Engagement Potential	Whether the solution could create continued interaction instead of solving only an isolated task.
Solution Flexibility	Whether different findings from the research could be addressed within the same product concept.
Project Potential	Whether the problem provides enough depth to continue exploring users, smart features, scenarios, and future iterations.

The objective of these criteria was not to determine that the other problems were invalid. The research provided meaningful evidence for all four alternatives. Instead, the criteria helped the team identify which problem provided the most appropriate design space for the following stages of the project.

2.4 Selected Problem — Side-quests: Breaking Out of the Routine

After comparing the four alternatives, the team selected Side-quests: Breaking Out of the Routine as the problem to continue developing.

The decision was not based on the assumption that the other problems were irrelevant. In fact, the interviews provided meaningful evidence and design opportunities for each alternative.

Side-quests was selected because the research revealed a problem influenced by several interacting barriers rather than a single isolated friction point. Trying something different can depend on planning effort, personal interests, available time, social comfort, and the perceived difficulty or commitment required by an activity.

These characteristics create an opportunity for a solution whose behavior can adapt according to the user's situation rather than presenting the same experience every time.

The problem also provides room to explore several mechanisms identified during the research:

Reducing planning effort.
Reducing choice overload.
Matching activities with personal interests.
Considering the user's available time and context.
Adapting the desired level of social interaction.
Using small, achievable challenges instead of requiring high-commitment activities.
Gradually adapting challenge difficulty.
Learning from activities that users accept, complete, skip, or reject.

For these reasons, the team considered Side-quests a strong foundation for a context-aware, personalized, and adaptive mobile experience while maintaining a direct connection with the behaviors identified during the research.

2.5 Second Convergence — From Problem to Solution

After selecting Side-quests as the problem, the team performed a second convergence process to determine which solution concept should be developed.

The divergent brainstorming process generated several alternatives:

Playful Challenge Application.
Side-Quest Discovery Platform.
Shared Discoveries and Challenges.
Long-Term Quest Challenges.
Community Side-Quests.

These alternatives were classified using the four ideation categories discussed during the design process:

The Rational Choice: Side-Quest Discovery Platform.
The Most Likely to Delight: Playful Challenge Application.
The Darling: Long-Term Quest Challenges.
The Long Shot: Community Side-Quests.

Sharing was retained as an optional supporting feature rather than a core concept because the interview evidence did not identify sharing as a primary motivation.

The alternatives were then compared according to feasibility, impact, engagement, personalization, and scalability. The Side-Quest Discovery Platform obtained the strongest overall evaluation and was therefore selected as the core solution.

Instead of discarding the remaining alternatives, complementary elements were incorporated into the selected concept:

Side-Quest Discovery Platform → Core experience.
Playful Challenges → Engagement mechanism.
Long-Term Quest Challenges → Progression mechanism.
Sharing → Optional social feature.
Community Side-Quests → Possible future extension.

Therefore, the convergence process occurred at two different levels:

Problem convergence: Four investigated problems → Side-quests: Breaking Out of the Routine.
Solution convergence: Multiple Side-quest concepts → Side-Quest Discovery Platform.

This process allowed the team to move from broad problem exploration to a single product direction while preserving the strongest ideas identified during the research and brainstorming stages.

3. Empathy Maps

3.1 Empathy Map 1

3.2 Empathy Map 2

3.3 Empathy Map 3

3.3 Empathy Map 4

Empathy Map 5 — Research-Based Prospective User

The interview originally conducted by Sebastián Maldonado during MS2 focused on the Skip the Line Campus Lunch Pickup problem. Since the team later converged on Side-quests: Breaking Out of the Routine, this prospective user was developed using secondary research related to leisure participation, barriers to activities, and engagement in personally meaningful activities. Research on leisure constraints identifies different types of barriers that can influence participation in recreational activities. These include intrapersonal constraints, such as psychological barriers; interpersonal constraints, such as the availability of other people; and structural constraints, such as resources or other conditions that interfere with participation. Research related to behavioral activation also supports the relevance of engaging in pleasurable and personally meaningful activities, frequently incorporating mechanisms such as activity selection, scheduling, and monitoring. Based on these findings, this Empathy Map represents a time-constrained university student who is interested in having enjoyable and varied experiences but whose participation can be limited by time, effort, available companions, and the relevance of the activity.

Sources:

Santopetro, N. J., Jones, D., Garron, A., Meyer, A., Joyner, K., & Hajcak, G. (2024). Examining a fully automated mobile-based behavioral activation intervention in depression: Randomized controlled trial. JMIR Mental Health.
Martin, F., Oliver, T., & Oliver, S. (2021). Behavioral activation as an “active ingredient” of interventions addressing depression and anxiety among young people: A systematic review and evidence synthesis. BMC Psychology.
White, D. D. (2008). A structural model of leisure constraints negotiation in outdoor recreation. Leisure Sciences, 30(4), 342–359.

4. Personas Maps

4.1 Persona Map 1 (Camilo)

4.2 Persona Map 2 (Valentina)

4.3 Persona Map 3 (Daniel)

5. Selected Problem: Side-quests — Breaking Out of the Routine

University students often want to do new things, but it can be hard to actually break out of their usual routine. From our research, we found three main reasons for this. For some students, planning something different feels like too much effort (Camilo). For others, having too many options makes it difficult to decide what to do (Valentina). And for students who also work, free time can be limited or unpredictable, leaving them with little time to even look for activities.

General Solution: Side-Quest Discovery Platform

Our solution is a platform that makes it easier to find something new without having to spend a lot of time planning or deciding.

Instead of opening an app and asking yourself, "What should I do today?", you simply open it and get a few side-quests that match your situation. They can be based on how much free time you have, your interests, your location, and how comfortable you feel doing something alone or with other people.

The solution works through four main ideas:

Simple discovery. The app gives you a small number of relevant activities instead of making you search through hundreds of options. You can quickly find something that fits the time you have available.
Recommendations that fit you. The suggestions change depending on your interests, mood, and comfort level. You might get a solo activity one day and a social activity another day. This makes the experience more personal and less overwhelming.
Small and fun challenges. Activities are presented as quests rather than obligations. Most of them are short and easy to start, so trying something new doesn't feel like a big commitment. For users who enjoy it, there can also be optional features such as streaks, progress, or an "Explorer" identity.
The app learns from you. Every time you complete, skip, or accept a quest, the app gets a better idea of what you like. Over time, the recommendations can become more relevant and, if the user wants, gradually suggest activities that are a little more challenging or social.

In short, the goal isn't to tell students to simply "be more spontaneous." Instead, the platform makes spontaneity easier by removing the things that usually get in the way: planning, too many choices, lack of time, and the uncertainty of trying something new. The user only needs to take one small first step.