PROJECT OVERVIEW
In 2021, COVID-19 was starting to subside, and we knew people would be more willing to travel now more than ever. However, it would be troublesome to determine which place would be safe to visit or plan a trip according to the travel guidelines of that particular place. This problem was relatable, so we decided to develop a solution for it as part of our Innovative Product Development Course.
We designed a travel application that provides a destination recommendation system and customized itinerary planning while ensuring travelers’ safety during an emergency using the User-centred Design (UCD) process. Our goal was to understand the problems faced by the users, analyze the shortcomings of existing solutions, and eventually design a user-centered prototype of an application that helps them streamline the travel planning process.
After implementation, we evaluated the usability of the application using the User Experience Questionnaire (UEQ) method and identified the design shortcomings.
SURVEY
As a part of the preliminary research phase, an online survey was conducted through Google forms to understand the users’ travel necessities.
RESULTS
UNSTRUCTURED USER INTERVIEWS
We conducted informal online user interviews with 10 users to get more detailed insights. It consisted of travel-specific questions plus follow-ups asking them about their travel styles, opinion, thoughts, experience, problems faced while planning a trip, and general expectations from travel-related applications.
MAIN INSIGHTS
Initially, we were unsure what features to include and whether the solution would be a website or a mobile application. To get more clarity, we drew paper frames and decided on our main focus.
After understanding the user pain points and crafting user personas, we wanted to understand the relative strengths of other competing travel applications. Two important features lacking in these applications are feedback from other users on a particular itinerary and a mechanism to ensure the user's safety.
After creating these Low-Fidelity Wireframes, we realized we had technical constraints. For instance, the application had to be developed at the end of the course, which meant we had to remove certain functionalities like the expense tracker. The final features are described in the next section.
FINAL FEATURES
PROBLEM: Search for different locations is often for simple criteria such as main state or climate. It doesn’t precisely fit individual users.
SOLUTION
PROBLEM: Users need access to up-to-date information about the situation of each country.
SOLUTION
SOLUTION
PROBLEM: Customized itineraries and collaborating with other users to view or edit itineraries are uncommon.
SOLUTION
PROBLEM: Users often miss the must-have experience in the area and don't get feedback on itineraries they have created.
SOLUTION
We devised an information architecture to decide how to best organize and structure all the features and make it easier for further wireframing.
We tested the usability of the working model with 5 users and the User Experience Questionnaire was used to get a comprehensive impression of the usability in the following aspects: Attractiveness, Perspicuity, Efficiency, Dependability, Novelty, and Stimulation. This measure was selected since it has simple, fast data collection and can be compared with a benchmark. Along with that, we observed the flaws which hinder the use of our application.
Working on this project while collaborating with my teammates was really fun. More importantly, I was able to recognize three important things that are required in the design process, and we missed them.
Firstly, bias played a significant role in our design decisions. These biases about our own experiences with travel lead us to prioritize certain features based on our own preferences.
Secondly, we underestimated the importance of understanding and working within technical constraints. Our solution heavily relies on whether the amount of data about destination is present in a curated dataset. Furthermore, we did not have developers capable of creating such a complex recommendation system. We failed to consider the practical limitations imposed by technology, resources, and implementation capabilities.
Lastly, our approach to research lacked inclusivity. We relied too heavily on standard user research methods and failed to actively engage with diverse user groups. Inclusive research is essential for understanding the unique needs and challenges faced by different communities especially in terms of income and physical capabilities.