Ecolens

Rate finder

Data-driven cost-option comparison tool for freight forwarders.

Domain

Freight forwarding

Client(s)

Cargoguide International

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.

Problem statement

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.

Solution

A data-driven tool that compares cost options adaptively—prioritizing choices based on past user decisions to improve efficiency and decision quality.

1. Doing a search query based on route (A>B) and shipment details

2. Compare cost options of different carriers and associated services

3. Viewing the detailed breakdown of a cost option

4. Review route and product information to decide and book a cost option.

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

Case study paper

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

(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.

Card sorting & proof of concept

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."

Validated user needs

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.

Key takeaways

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.