AI-POWERED SCHEDULING
IOS App - Faßter
Faßter is a native mobile app through which users can order a portable beer bar on a bike to any desired location with their preferred beer choice and an optional bartender service.
In a team of 3 designers, we followed design thinking framework and UX tools to work on a MVP of the app and create a smooth and easy user journey.
Project Requirement
Conduct user research to understand user needs and incorporate findings in the design to make the app flexible and easy to navigate.
Deliverables:
MVP of the app
User research
Mid-fidelity Prototype
Usability testing
Hi-fidelity and interactive Prototype
More features can be added in the app in the future.
Background
Faßter is a native mobile app through which users can order a portable beer bar on a bike to any desired location with their preferred beer choice and an optional bartender service.
The app offers a variety of drink options which are in the portable barrels mounted with a bike, it also offers the human connection with the bike rider, showing their interests and recommendations.
In a team of 3 designers, we followed design thinking framework and UX tools to work on a MVP of the app.
With an intuitive interface and personalized recommendations, Fasster makes incorporating sustainable way of consumptions into your social life effortless and enjoyable.
This category details the step-by-step approach taken during the project, including research, planning, design, development, testing, and optimization phases.
Research & Planning
Conducted market research to identify existing scheduling challenges and user preferences. Defined target audience segments and outlined key features based on user needs and market trends.
Design & Prototyping
Collaborated with designers to create intuitive user interfaces and interactive prototypes. Iteratively refined designs based on user feedback to enhance usability and visual appeal.
Implementation
Leveraged agile development methodologies to build the scheduling app from the ground up. Prioritized feature development based on user feedback and technical feasibility. Implemented AI algorithms to analyze user behavior and optimize scheduling recommendations.
Testing & Optimization
Conducted rigorous testing across various devices and platforms to ensure compatibility and performance. Gathered user feedback through beta testing and iteratively optimized the app based on usability metrics and user satisfaction.
User Research
This category details the step-by-step approach taken during the project, including research, planning, design, development, testing, and optimization phases.
Lean Survey Canvas &
Empathy map
We started by brainstorming using
Lean Canvas Survey, to clarify:
What we needed to learn?
Who the users are?
What information is available?
& how to reach the users?
User Survey
After gaining some insights from lean survey canvas and got familiar with what we needed to learn from the users, we have started to prepare and conduct user surveys to collect the quantitative data. To understand the behaviour of users, we asked the questions in our survey, some of which were:
• Which type of Beer do they prefer
• If they order beer online
• if they buy large quantities of beer
• how often do they consume beer
• if they order big beer kegs for an outdoors party of theirs if that option is availabe
On the right are the key insights that were collected through the user survey.
We used this information when we designed the MVP version of the app.
User Interview
Through our surveys and interviews we learned for example that they would prefer to book both spontaneously and in advance, so we incorporated the possibility into the app.
We primarily focused on learning the current behaviour of users and what they would expect to see in such an app
HMW Statement
How might we design a platform that creates a connection with the user, and assists them in fulfilling their needs with a very smooth and clear path?
Moscow Method
To find out what feature or choices to provide to the user as per their needs, we followed the Moscow method.
Through this method, we categorised the features as per 4 section.
The most important features added to "Must have" and
next important features added to "Should have" and "Could have"
and lastly, the features that were not considered in the current design in "Won't have"
Prototype
The resulting AI-powered scheduling app offers a seamless user experience, allowing individuals and businesses to effortlessly manage their schedules.
Lo-fi Prototype
Based on the MVP of the product, we brainstormed on lo-fi ideas on paper.
The goal was to check and test the functionality of the app without concentrating so much on the visual part on this stage.
User flow
Based on the user research and business model, we envisioned various user flows and choose the most straightforward and logical path that the user would take to reach their goal.
In this user flow, the user goes through a happy path to order the product with a slight dip in the path with the sign in screen, which is a necessary part of the journey.
Mid-fi Prototype
To visualise the user flow, we created mid-fi wireframes. The wireframes views the path that the user will take to order the beer bike at their preferred location.
Mid-fi Usability Testing
To test the prototype, we used Maze.
To see what path the users would take, we assigned tasks and let the user complete the task as they understood the design.
Most of the results were positive, with only a few exceptions.
As this was the MVP version of the app and a Mid-fi prototype, not everything was clickable and that was one of the cause of confusion for users. We realised that after testing and made some changes in Hi-fi prototype.
Two of the tasks can be viewed below with the test results:
Through the time of the project, I worked with another designer and I collected some insights for myself:
The MVP idea also included the B2B side as well.
As a designer, I understand the need to know your users. The same app can have different set of users and completely different needs.
Images and Icons plays a big role in the finger-friendly tap targets.
Listening to the team and reflecting on their ideas is important, not only to be a good team player but also a user experience designer.
Asking for feedbacks can help in refining the designs and making it user friendly.
Know your users
Users report significant time savings and improved productivity through optimized scheduling recommendations.
Finger friendly tap targets
High user satisfaction ratings and positive reviews highlight the app's intuitive interface and powerful AI capabilities.
Asking Feedback
The app quickly gained traction among individuals and businesses worldwide, with a steady increase in user adoption and engagement.