Case Study:

Personalized Traveling App

The Problem.

Travelers are overwhelmed with traveling advice and recommendations regarding everything: where to visit, where to eat, where to sleep etc. 

The problem with the recommendations they read is that they are not customized to your specific traveling needs. 

I wanted to create a smarter, customized and simple traveling experience for travelers globally. 

The Research.

My research focused on the analysis of social media chatter and traveling apps benchmarking. 

I gathered social media chatter in various traveling groups, and observed the main talk themes among users. 

As part of my own travels in South East Asia, I conducted conversations with fellow travelers to understand their most acute needs and current gaps when making a decision during the trip.


The Insights. 

The research led me to several conclusions about the user, that will lead me on in the design process:

Insight #1: Travelers need immediate guidance at hand, whether they are “in advance” planners or “go with the flow” type of travelers.

Insight #2: Travelers prefer to trust personal recommendations rather than “generic” tips such as lonely planet guides, trip advisor etc. 

Insight #3: Not all recommendations suits the same traveler. parameters like age, social -economic level and marital status affect the traveling preferences dramatically

I created two personas that reflect the spectrum of needs that can occur when traveling.

Insight #1

Based on the first insight I chose mobile as the best suitable platform, as it is usually used by travelers before and during their travel. 

Travelers need the most relevant travel information to be clusters upon “one layer” – that is immediate and simple. I designed a map feature that will include all saved travel recommendations on a visual layer – that will be easily approachable from any place within he app. 

Save a recommended item 

Filter all items in destination by category

See all saves items in one layer

Insight #2

Travelers will trust a personal recommendation rather than a “generic” one

I wanted to create a personalized “look and feel” across the app – and for that I used match percentage figures integrated in the user’s personal feed and when searching for a specific destination.




Find personal recommendations for travel destinations

preview of the top matches within a destination

see personal recommendations from travelers similar to you

Insight #3

Not all recommendations suit the same user

Different users will look for different activities in the same recommended location – and destination preferences need to be customized to the user’s characteristics. 

I understood that the mobile app needs to include a more lengthy on boarding process – that will help the app the get the know the user – who is he? how old is he? who are his traveling companions? what traveling style does he prefer? 

As the onboarding process is quite longer than usual, I wanted to create a more interactive experience for this stage, similar to other leisure apps such as apple music.



The user logs in his characteristics and traveling preferences

He marks the saying that describe him best – for “character based” recommendations

After onboarding process – the app is all set to personalize the user’s travel. 

User Flow.

“Uffala”  is a mobile app that creates a personalized arsenal of recommendations to fit the traveler’s needs and preferences: her age, her travel companion, her travelling taste and style in addition to her values and beliefs

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