Rate finder
Data-driven cost-option comparison tool for freight forwarders.
Domain
Freight forwarding
Client(s)
My role
Postgraduate, UX Designer
Project duration
3 months
Team (1)
Stefan van Brummelen
Design challenge
How can an adaptive interface enhance pricing decision-making efficiency in cost estimation for companies?
Problem statement - improve decision-making effiency
Companies struggle with inefficient pricing decision-making in cost estimation due to rigid interfaces that fail to adapt to dynamic business needs, integrate diverse data sources, or align with strategic and stakeholder priorities.
Rate finder - comparing shipping options
A data-driven tool that compares cost options adaptively—prioritizing choices based on past user decisions to improve efficiency and decision quality.
Freight forwarder workflow
Enhancing decision-making efficiency
Accurate and efficient cost estimation is crucial for strategic planning and informed
decisions, particularly within business sectors such as transportation.
This case study focuses on enhancing the decision-making efficiency of freight forwarders when choosing cost options for B2B shipments
B2B context
Cost estimation from location A to B
Accurate and efficient cost estimation is crucial for strategic planning and informed
decisions, particularly within business sectors such as transportation.
Freight forwarders act as intermediaries responsible for estimating and arranging transportation services to move goods from one location to another
This case study focuses on enhancing the decision-making efficiency of freight forwarders when choosing cost options for B2B shipments
(2)
search for cost options (A > B)
(4)
decision-making and
cost option evaluation
(5)
deciding for a cost option
(make booking)
(3)
view cost option overview
(A > B)
(1)
Business request / cost estimation request
(shipment A > B)
Flight rate API
Flight schedule API
(6)
cost entry
notification
(after booking)
(7)
price input
(to update cost database)
Freight forwarder
cost database
Acquiring flight data
and data collection
Card sorting with SMEs & proof of concept
Card sorting with SMEs: Identified key data variables (route, cost, and service factors) to prioritize user decision-making in shipping option comparisons. Proof of concept: Acquired and merged flight cost data from 2 APIs, including data cleaning to ensure usability.
Hi-fi prototyping
for validating design decisions
Validated user needs through prototyping
Revealing key insights: "Future pricing trends and real-time updates would help me anticipate cost changes and make informed booking decisions." "Manually entering paid booking prices feels risky, I worry about errors affecting data reliability."
User testing
(ex) freight forwarders
Key takeaways
Data accuracy builds trust—automation is essential to minimize errors. Users prefer automated entry to avoid human errors and ensure reliable data. Designed expert-focused financial overviews and workflows based on user needs.
Personal reflection
Financial workflows & decision-making
The project has taught me:
To develop design-oriented feedback collection methods to understand the context of use, obstacles, needs, and pain points of expert users within a niche.
To address design uncertainty—stemming from not being an expert user or lacking domain expertise—by validating business scenarios through user and usability testing.
To gain a deeper understanding of decision-making efficiency for financially oriented business users in a niche domain.
To define decision-making variables for experts through design research methods and design-through-research practices.
