Bar Explorer Application

​

This application was a major project for CPSC 444: Advanced Methods for Human Computer Interaction. When discussing this project, we were brainstorming several different ideas, and one thing common between us was our interest in breweries. So, we came up with the idea of identifying how people in Vancouver find and visit breweries, and we wanted to see if there was a space for an application that could help make finding and going to breweries more interesting. Our target customers were young adults (19-30 years old) living in a city like Vancouver that liked visiting bars.�After our initial field study, we found some interesting requirements from the users and brainstormed several, vastly unique designs.

​

​

Prototype

​

From our field study, we found that, for a new customer, the most persuasive quality that a brewery could have would be if a friend recommended it. Furthermore, all participants mentioned how important the social aspect of both planning and visiting breweries were. So, we crafted our medium-fidelity prototype with this in mind. We tested this med-fi prototype to estimate its usability, efficiency and user satisfaction against the current most commonly used method to find and visit breweries with friends, i.e., using Google Maps. We created a brand new feature called ‘Trips’, where you could plan trips to multiple breweries, invite friends and plan collaboratively, and our application would also generate a route to all of the breweries that you can follow.

​

​

A User-Centric Approach

​

Our approach and design was driven by the users. Our final prototype ended up being quite different from what we might’ve imagined when we first came up with the idea for this project. Initially, we imagined our application to be focused on breweries, and finding them efficiently. However, after conducting a field study (N=8) on how adults in Vancouver explore and choose to go to breweries, we discovered the importance of the social aspect in both planning and actually going to breweries. Users were really likely to visit a brewery if a friend had recommended it, and very few said that they would look for breweries online when making a plan. Furthermore, participants also expressed interest in going to bars and pubs. As we thought about our design, we focused on the users, and added an extensive social factor that, through our experiment, resulted in increased user satisfaction. We also expanded from only breweries to also have our application include bars and pubs.

​

The following presentation is from the final presentation for the CPSC 444 course, it gives a high-level overview of our entire project and design process.

​

I have also created a more in-depth report which I will link here: https://drive.google.com/file/d/1RT53ZlaOI6UKeSU82LoMGXM_gJs2eHbt/view?usp=sharing

​

​

bar explorer

Team SURE!

CPSC 444 Project Milestone IV

To understand how young adults in Vancouver discover, choose, and navigate to breweries, and the implications of these activities for designing a digital platform that effectively supports brewery discovery and social planning.

​

​

The users are between the age of 19-30 and fall into categories:

• Bar explorers
• Group planners
• Budget-constrained students
• Travellers trying to explore a new area

​

​

​

​

​

Project Direction

Process

Field Study

Generate Requirements

Lo-fi Prototype

Med-fi Prototype

Pilot Testing

Experiment

Requirements Process

• 8 participants
• Semi-structured interviews
• Observations
• Key insights:
• Reliance on friend recommendations
• Scattered information
• Google Maps being the popular workaround

​

Field Study

Prototyping

• Tools used
• Lo-fi wireframes
• Sketches
• Cognitive walkthrough
• Design iterations
• Med-fi interactive prototype on Figma

​

Iteration Processes

• 2 participants
• Ran through the entire experiment
• Determined flow and validity
• Key insights:
• Bugs within Figma
• Clarity of instructions given
• Timing
• Reinforced values of the tasks performed

​

Pilot Study

Experiment

• Conducted with 8 participants
• Observations
• Structured scenario performed for A/B comparison
• User guided exploration of novel and social features
• Semi-structured interview
• Questionnaire

• Social features
• In app messaging and notifications
• Friend recommendations
• Collaborate on planning a trip
• Trips
• Tracking history of trips
• Planning future trips
• Ability to generate a route from a trip
• Venue Cards
• Providing insights and details about a location
• Helps decison making
• Saved and Want to Go Lists
• Ability to save and view a list of bars with details visible

Goals:

• Efficency
• Learnability
• User Satisfaction

Prototype Features

Prototype Walkthrough

Experiment Plan

A/B Testing

• Perform a identical scenario with each application (Google Maps vs Prototype)
• Counterbalanced
• Within Group
• No coaching or guidance given.

Novelty

• 2 specific tasks on friend recommendations and trip planning
• Explore freely to see any features that they want to look through at their own pace
• Think aloud interactions with the features

Independent variables

• Tool used (2 levels)
• Google Maps (control)
• Prototype (experimental)

​

Dependent variables

• Self-reported satisfaction -> user experience
• Task completion time -> efficiency
• Error count -> learnability

​

Experimental Condition 1:

• Users complete tasks using Google Maps.

Experimental Condition 2:

• Users complete tasks using our prototype.

​

Experimental Design

Hypotheses

• H0 (null): User performance and satisfaction using the prototype are less than or equal to those in Google Maps.
• H1 (alternative): User performance and satisfaction using the prototype are higher than those in Google Maps.

Participant recruiting

• Convenience sampling
• Participants aged between 19-26 years old
• Included both expert and novice bar and brewery visitors

Each participant completed both conditions (within-subject) with order counterbalanced (AB/BA) to mitigate learning effects.

Results

Time Taken by Application

Errors by Application

Significant main effect

No significant effect

Novel and social features

Comparison to Google Maps

• Users valued:
• Seeing where friends had been
• Being able to share a full trip
• Integrated planning + social context
• Feedback:
• “This is actually sick.”
• “I love the friend's recommendation!!”

• User previously used Google Maps to perform this task - significant transfer effects
• Feedback:
• “I use Google Maps every day.” (P8)
• “Maps are for navigation; this is for planning.” (P3, P6, P8)

​

• Misunderstanding of buttons, lack of feedback reduced clarity
• Feeback
• “Add to trip could be clearer—maybe a plus sign with the word Trip.”
• “I thought tapping the person’s face would open it.”

​

Thematic Analysis

Signfiers, Feedback and Clarity

Workflow and Efficency

• Users performed faster on the prototype than in Google Maps
• Having all the information in one place was essential
• Feedback:
• “This is way faster: I can see everything here.” (P3)
• “All I had to do was click add.” (P7)
• “For planning a night out, this is better.” (P4)

​

Conclusion & Recommendations

• Users liked the novelty and specificity of the tool.
• Users completed tasks faster and felt more satisfied.
• The value of the Google Maps known mapping platform should be integrated rather than recreated.
• UI needs stronger affordance + labels - improvements would focus on learnability.