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Reinventing the Bottle Service Experience in Toronto's Bars and Nightclubs

Timeline: 3 days/40h | Role: Solo Product Designer

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Solution
Group bookings with split payments

Development of a new feature for the iBar app enabling:

  • Pre-booking of alcoholic bottles for groups

  • Split costs among friends

  • Group order management

  • Seamless integration with existing drink service

Problem

Deliver shared reservations while maintaining the simplicity of the app's core functionality

iBar gained popularity in Toronto's nightlife by allowing drinks to be ordered without waiting in lines. Now, they wanted to enhance the experience further by offering bottle reservations, but this presented new challenges such as:

  • Expanding from individual orders to group bookings

  • Implementing cost-sharing flow

  • Staying aligned with Canadian nightlife culture and alcohol consumption laws

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Benchmarking and Interviews

Canada's Bar Culture: A Different Approach to Drink Management

Although the client provided initial research for the new feature implementation, interviews with locals helped map out key restrictions that needed to be considered in the new user flow and journey.

 

While benchmarking helped understand cost-sharing systems in similar apps, the interviews were crucial in revealing:

  • Alcohol consumption limits in bars and clubs

  • Legal liability of establishments for alcohol consumers even after they leave

  • Common profiles and behavior patterns of bottle service customers

User Journey

Merging Familiar Flow Patterns with Cultural Aspects

By analyzing purchase, sale, and reservation flows from popular apps like SkipTheDishes, DoorDash, and UberEats, I identified common patterns used in shared bookings among multiple users. Combining these functional aspects with research insights, I created a User Journey Map for the feature to guide the screen design process.

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Usability Test

Clear feedback cues can make the difference between success and failure

After mapping touchpoints, I sketched key screens that evolved into wireframes for testing with 5 users. The tests revealed understanding gaps in feedback during the bottle reservation flow. These pain points were addressed in the development of the high-fidelity prototype.

Final Result

Delivered Solution

Conclusions and Lessons Learned

Research method selection can bias an otherwise good solution

Everyone knows research is fundamental, but even how you conduct it can greatly impact the final product. In this project, it became clear that quality would have been significantly compromised if I had relied solely on the company's provided research without conducting interviews.Being from a different culture, simply reading research, even if conducted by locals, would never have allowed me to fully grasp the nuances of local drinking culture. Only through conversations could I understand what was obvious to them but completely new to me.

Key Considerations:

  • As a new feature, close post-launch monitoring is essential. Although it shares the context of individual drink orders, bottle service requires more attention points since it involves groups rather than individuals, especially regarding personal alcohol consumption limits. Flow adjustments are expected to optimize both venue and user experience.

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