MCM Worldwide
my background of working at mcm
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MCM has been through many evolutions and big and small rebrandings over the past years.
My journey at the company has been as dynamic as the changes the brand itself has undergone since 2016.
Problem Solving Process
User Research and Problem Identification
To gain a deeper understanding of user behaviors and needs, I have conducted 30-minute interviews with 7 interviewees located around the world. The reason I chose interviewees from different cultures is that I wanted to receive a variety of insights from diverse perspectives and backgrounds. The one specific requirement was that the participant travels internationally more than once a year.
Affinity Map and Empathy Map
After transcribing the interviews, I reframed the data into structured categories to see what connections emerge. The affinity map below shows the sorted and clustered data derived from interviews. The top pink post-its are the themes for each column and below yellow post-its are some research quotes or pain points from the interviews. From this data, I was also able to create an empathy map to illustrate what my chosen audience says, thinks, does, and feels. The black text is positive or neutral and the red text is negative points.
Interesting Insights
Most participants claimed that they would like to experience at least one high-end restaurant on a trip:
The dining experience was a big part of a travel experience for most participants and even with covid, it seemed like some are still putting dining as a top priority.
Some participants refer to multiple different sources when retrieving recommendations about a destination:
Everyone wants to have the best experience while traveling but gathering numerous amount of information is time-consuming and exhausting.
Most participants believe that the location is one of the most important factors when deciding where to dine:
As much as the eatery is the foremost priority, where the restaurant is located at influenced the decision making.
Needs
Restaurant selection comes first then comes the destination.
Depending on the dining experience, users will be deciding on where they will be traveling to. This is a reverse way of determining a travel destination compared to the traditional way. For big “foodies,” this can be an interesting way of deciding a location.
A personalized restaurant curation.
Machine learning program can curate a list of restaurant recommendations based on the user’s digital footprint. Linking to social media apps or email accounts can provide users with the most precise results. No need to go through numerous website or travel apps only to be disappointed by the reality from the photos you saw.
Search and reserve in one go.
With the carefully selected options in a list, you can also make reservations for the international restaurants without any hassle of going through a 3rd party site.
Understanding the Persona
Based on the research materials, I created a persona that represents the interview respondents as a whole. Understanding of this persona will be useful to improve the user experience.
Say hi to Olivia!
Sketching
After understanding the problems and opportunities, I started sketching out different ideas for the possible solutions.
A Friendly Meet and Greet
Onboarding flow introduces the important functions of Savor that may be new to the users.
Really Getting to Know You
On top of the user data and footprint that the user provides, Savor offers optional questions for even more specific analysis to get to know the user in depth.
Easy Reservations Just for You
With the analyzed information, Savor recommends the carefully selected restaurants from all around the world that is perfect for the user’s taste and offers a straightforward and easy user interface to make reservations.
