Designing a Database for
Faster & Smarter Customer Searches
Designing a Database for
Faster & Smarter Customer Searches
THE CONTEXT
THE CONTEXT
What's this about?
What's this about?
Kensington Tours is a luxury travel company that creates tailor-made itineraries for travelers. They manage extensive customer records across multiple systems and access points, requiring quick and accurate data retrieval.
Consolidate complex, multi-system customer data into a single interface.
Prioritize and display the most relevant information based on user role and search context.
Streamline search workflows to improve speed, accuracy, and ease of use for internal teams.
Kensington Tours is a luxury travel company that creates tailor-made itineraries for travelers. They manage extensive customer records across multiple systems and access points, requiring quick and accurate data retrieval.
Consolidate complex, multi-system customer data into a single interface.
Prioritize and display the most relevant information based on user role and search context.
Streamline search workflows to improve speed, accuracy, and ease of use for internal teams.
Timeline:
2 weeks
Role:
UI/UX Design
Timeline:
2 weeks
Role:
UI/UX Design
THE CURRENT
THE CURRENT
The database needs structure.
The database needs structure.
Kensington Tours’ client data was scattered across multiple disconnected profiling systems like TMTx Client, Traveler, etc.
Kensington Tours’ client data was scattered across multiple disconnected profiling systems like TMTx Client, Traveler, etc.
Staff had to sift through excessive, non-prioritized details, slowing searches and increasing the risk of missing critical client information.
Staff had to sift through excessive, non-prioritized details, slowing searches and increasing the risk of missing critical client information.
THE CHALLENGE
THE CHALLENGE
Design a database interface that shows the most relevant client data efficiently.
Design a database interface that shows the most relevant client data efficiently.
ITERATIONS
ITERATIONS
Design systems and user flow.
Design systems and user flow.
˖ ᡣ𐭩 ⊹ ࣪ ౨ৎ˚₊
˖ ᡣ𐭩 ⊹ ࣪ ౨ৎ˚₊
The design evolved through multiple iterations, refining both the system’s visual structure and the user flow.
Early versions focused on decluttering the interface, while later iterations optimized search paths, reorganized data hierarchy, and introduced role-based views.
The design evolved through multiple iterations, refining both the system’s visual structure and the user flow.
Early versions focused on decluttering the interface, while later iterations optimized search paths, reorganized data hierarchy, and introduced role-based views.
This leads to faster and more intuitive paths to access key client information.
The design evolved through multiple iterations, refining both the system’s visual structure and the user flow.
Early versions focused on decluttering the interface, while later iterations optimized search paths, reorganized data hierarchy, and introduced role-based views. This leads to faster and more intuitive paths to access key client information.
Rather than trying to display all the important information on one page, I decided to transform this page to be more of a summary of the specifics, which provided more context. However, all details were still accessible through dropdowns and popups.
Rather than trying to display all the important information on one page, I decided to transform this page to be more of a summary of the specifics, which provided more context. However, all details were still accessible through dropdowns and popups.
REFLECTIONS
REFLECTIONS
REFLECTIONS
What did we learn?
What did we learn?
Designing for Role-Based Efficiency
Designing for Role-Based Efficiency
I learned the value of tailoring the interface to specific user roles, ensuring each team sees the data most relevant to their workflow. This minimized cognitive load and accelerated information retrieval across departments.
Simplifying Complex Data Structures
I learned the value of tailoring the interface to specific user roles, ensuring each team sees the data most relevant to their workflow. This minimized cognitive load and accelerated information retrieval across departments.
Simplifying Complex Data Structures
Transforming multiple disconnected systems into a unified, easy-to-navigate design required distilling large datasets into clear, prioritized views. Progressive disclosure allowed advanced details to remain accessible without overwhelming the main interface.
Optimizing Search Flows for Speed
Transforming multiple disconnected systems into a unified, easy-to-navigate design required distilling large datasets into clear, prioritized views. Progressive disclosure allowed advanced details to remain accessible without overwhelming the main interface.
Optimizing Search Flows for Speed
By refining the search path and reducing unnecessary steps, I improved the team’s ability to find key client information instantly. This reinforced the impact of clear interaction patterns and thoughtful default states on performance.
By refining the search path and reducing unnecessary steps, I improved the team’s ability to find key client information instantly. This reinforced the impact of clear interaction patterns and thoughtful default states on performance.
