Are you looking for a great restaurant in Toronto? a UX case…
I was trying to select a great option to celebrate my daughter, B-Day. I found that there is no easy way to combine restaurant ratings across different website searches. I did google, Yelp, Zomato, and open table, trip advisor, Expedia, etc.
It is a pain to look for a consolidated rating. For example, my friends have issues such as dietary constraints, foodies, oldies, etc.
We have so many ways to look for information. Which one is the best way for me as a user? The fragmented data across different platforms; is not us; from that point of view, I would say businesses and marketers don’t know how to communicate the multiple offers to their target market.
It is not our attention that is fragmented; what about if it is the service offering that is fragmented? Yes, creating a specific market solution that the rest of us live in the no-man land.
I decided to create a user journey as a hypothesis on how I think to elevate the experience, following a design-thinking framework.
Discovery: Understanding the user, why are they looking for information about restaurants? Let the customer wild without previous assumptions; maybe we want to have one place to compare all the restaurants' ratings, search for keywords, type of food, dietary restrictions, availability, location, and budget.
Analyze: Describe the user's point of view; why do they need one place to look for ratings? For example, I need to enter the restaurant, and what about if I don’t know the name, but I know the type of food or budget or location; the user journey change, most of the marketplace applications search filters are not flexible enough for the user to have the best experience. Most of the search engines are too narrow and not flexible enough. Their target user's definition reflects old research; in my humble opinion, user research is not a project is a program continuous improvement program.
Design: brainstorm possible solutions that could enhance the search platform, for example: allowing the user to start the search from different points, depending on the information that the user has about the place that they want to go.
Prototype: create a flexible solution that runs on AI recommendations that will provide answers to an unknown problem and learn how to adapt the filter options and actual customer queries.
Measurement: testing of the solution will be learning along the way, adding options and flexibility to the user search journey, and to keep adding new features and enhancements.
Conclusion
Users will want and always have their own opinions about restaurants and how they find the best option, filtering and ranking the restaurants based on their personal experience.
Things that can improve in adding and enhancing the search engine offerings, creating a consolidator app for users that want flexibility, and solving their bookings fast.
