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MS4
Based on the feedback received for MS3, the following improvements were made:
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Empathy Maps: Reorganized entries in Empathy Map 5 to correctly assign information across quadrants (Thinks, Feels, Perceives, Does). Reclassified misplaced entries and added additional content to balance all sections.
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Brainstorming Process: Enhanced documentation to provide more in-depth explanation of the brainstorming methodology, session structure, and how ideas were organized and prioritized for the final solution.
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Solution Description: Expanded the "how" section with detailed implementation details explaining how each feature works and how the solution addresses the core pain points identified in the personas, particularly Paola's concern about doing activities alone.
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Personas: Refined persona definitions (for Paola) to ensure core pain points align with the proposed solution. Updated Needs & Expectations to include social and group discovery features. Clarified Desires & Motivations to emphasize companion-based activities and social connection. Refined pain points to be more specific and solution-oriented (e.g., "struggles to find suitable companions" rather than generic concerns). Enhanced technical environment sections to reflect willingness to use social features in apps.
People often fall into a routine and struggle to find interesting activities to do near them. When they want to do something different, they usually have to search across multiple platforms (social media, review sites, word of mouth) and manually compare options, which takes time and effort. Because of this friction, many people end up doing nothing or repeating the same activities instead of discovering new plans nearby.
The solution is an application that helps people discover popular activities to do in nearby places. It uses the user's location to identify available activities and shows them in a simple, accessible way, so users can choose an option based on their interests and location without having to search through multiple platforms or decide on an activity from scratch.
| # | Problem | Alternative | Solution |
|---|---|---|---|
| 1 | People fall into a routine and struggle to find new things to do. | Searching Instagram or Facebook for plans and ideas. | A personalized feed that recommends plans based on the user's interests. |
| 2 | Small businesses that offer plans and experiences have no easy way to reach new customers. | Paying for ads on social media. | Sponsored plans and quests featured inside the app. |
| 3 | People often miss interesting activities because they do not know what is happening near them at the right time. | Checking different social media accounts or asking friends about plans. | A location-based activity feed that shows available and popular activities happening nearby. |
| 4 | People new to Bogotá have difficulty discovering activities that fit their interests, location, and schedule. | Searching across Instagram, TikTok, and Google for different plans. | An activity calendar that recommends nearby events based on the user's interests and availability. |
| 5 | Users struggle to maintain consistency in trying new activities and lose motivation over time. | Relying on willpower or friend reminders. | A gamified system with activity streaks, achievements, and progress tracking to encourage habit formation. |
| 6 | Users feel uncertain about trying unfamiliar activities without social proof or reviews. | Asking friends for recommendations or reading reviews on multiple platforms. | Built-in ratings, reviews, and user feedback directly on each activity to build trust and confidence. |
| 7 | People struggle to find activities that fit into their limited free time. | Searching manually for activities during weekends or after work. | A schedule-based recommendation system that suggests activities that fit the user's available time. |
| 8 | Users feel overwhelmed when there are too many possible activities to choose from. | Looking through different platforms to compare all available activities. | A short list of a few suitable options with a simple comparison to make the decision easier. |
| 9 | People avoid activities they would enjoy when they cannot find someone to join them. | Waiting for friends schedules to align or posting invitations in group chats. | Buddy and group quest features that show interested friends or participants and let users invite others to join. |
| 10 | Users have difficulty finding activities that fit their budget because prices are often unclear or scattered across different sources. | Opening several venue pages or contacting organizers to compare prices. | Price filters and clear cost information on each quest, including a category for free activities. |
| 11 | Users become discouraged when a suggested activity is too far away or requires too much travel time. | Checking each location manually in a separate maps application before deciding. | A map-based discovery view with distance filters that prioritizes quests within the user's preferred radius. |
| 12 | Users have no simple way to record and share the new experiences they complete. | Saving photos in their gallery or posting each activity separately on social media. | A quest history with optional photo verification that records completed activities and displays them on the user's evolving profile. |
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During the last 30 days, what has been our average response time for quest recommendations?
- Justification: Monitors app performance and stability over time for developers to check.
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What activities near me match my interests and energy level (1-5 scale: low to very high) right now?
- Justification: Delivers personalized recommendations directly in the app by using explicit user input (Likert scale 1-5) combined with location data. Data sources: user input + GPS location + activity database. Privacy/Ethics: Energy level is strictly first-party user data with no third-party sharing required.
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How is my activity streak trending compared to previous weeks?
- Justification: Shows user engagement trends to encourage habit formation.
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What quest should be recommended to me next, based on my past activity?
- Justification: Provides personalized quest suggestions based on user behavior.
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Which of my favorite places or activities (bookmarked or visited >2 times) are near me right now (within 5km radius)?
- Justification: Displays relevant locations in real-time to improve discovery and engagement.
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Which activity categories are being selected less than 3 times a week?
- Justification: Identifies underused features to inform decisions on improvement or removal.
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At which step do users most often abandon a quest without finishing it?
- Justification: A step is a phase in the quest flow (e.g., view details → accept → navigate → complete). Identifying drop-off points helps optimize UX.
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What characteristics do users who haven't opened the app in the last 2 weeks have in common (demographics, activity history, notification preferences)?
- Justification: Identifies common traits of inactive users to target re-engagement campaigns.
- Which neighborhoods (defined by geographical zones in Bogotá) have the most quest activity, so we can offer partnerships to local businesses there?
- Justification: Identifies high-activity areas for possible business partnerships and monetization strategies. Data source: aggregated quest completion data by location.
- What characteristics do users classified as "highly active" (defined as: ≥5 completed quests per month) have if they haven't tried a sponsored quest yet, and how should we notify them (email, in-app, push notification)?
- Justification: Combines UX improvement (strategic notification delivery) with data monetization (sponsored quests targeting). Privacy/Ethics: Sponsored content targeting uses only aggregated behavioral data; users can opt out of sponsored content notifications. No third-party data sharing occurs, all data remains within the app.
Must display all 14 business questions and their data sources. Sources must be obtainable through the designed solution or must be publicly available.
