How might we streamline the workflow of a trucking shipper when booking quotes?

Portex Web Application

Portex is a venture capital backed startup focused on streamlining the freight procurement process. I lead foundational research to uncovering key personas and critical user journeys to help the team build a simpler and more efficient workflow for a shipper’s quotation process. The work supported the launch of the Portex web platform and a $1.4M pre-seed investment raise (Susa Ventures, Base10, and angels).

Visit Portex

PROJECT DURATION

3 Months

MY ROLE

UX Researcher

Data Scientist

Product Manager

PRODUCT TEAM

UX Researcher

UX Designer

Lead Engineer

CEO

METHODS & TOOLS

User Interviews

Usability Testing

NLP with Python

Design & testing with Figma

THE PROBLEM

The global freight procurement process is very ‘old school’ and manual, with vital data points for quotations living in static Excel or PDF documents that are lost in tons of email threads. In addition to that, booking confirmations occur via email and on the phone.

RESEARCH OBJECTIVES

The Portex founding team and I set out to understand the current workflow of trucking shippers to identify their key pain points, goals and behaviours.

Understanding the Shipper workflow

I conducted user interviews with 20+ shippers from SME businesses and larger enterprises across the US, using the JTBD framework to understand :

  • Their supply chain

  • Their end-to-end workflows and tools used

  • The pains in these workflows

  • Their needs

 

Examples quotations that live in static emails, Excel and PDFs.

Thematic Analysis

A thematic analysis of all the feedback from user interview sessions helped me understand the key themes in the shipper’s current workflow and all their pain-points in this flow. 

Shipper’s Pain-points

The thematic analysis of user feedback gave me insights on the biggest pain points in the shippers workflow:

Shipper’s Workflow

An average shipper carries out this inefficient and manual quotation process at least 40x times a week!

  1. Manual data entry from Excel

  2. Multiple email threads to manage

  3. Manual data entry to Excel

  4. Inefficient comparison methods prone to human error

  5. Back and forth on email and phone calls, and inefficient document management

  6. Manual report creation

  7. No benchmarks for rate comparison

From the user interviews I built a clearer picture of the ‘shipper’ persona.

Using Data Science

I conducted NLP Analysis of customer reviews of competitor tools scraping data from G2, Google etc. to learn more about the pain points of users, and understand strengths and gaps of these tools.

Exploratory data analysis workflow using NLP

Competitor Freight Procurement Tools

I shortlisted my analysis to the following competitor tools:

  1. Flexport

  2. Freightos

  3. Shipa Freight

  4. UPS

  5. SAP Ariba

  6. Emerge

Word Clouds

From the most frequent terms in word clouds, I could see:

  • Change is highlighted in multiple word clouds and is used in the context of users wanting to change shipment information.

  • Delay appears highlighting the importance of transit time.

  • Terms such as Expensive and Cost appear showing how users are looking for cost effective solutions.

  • Customs and associated charge is a major problem for users of Freightos.

  • Need appears in the word clouds showing room for additional features or tools in these solutions.

  • Contact information needs to be highlighted.

  • Approval workflowis an important feature that large organizations require.

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DESIGN SOLUTIONS

Using my research findings, the product team designed & developed:

  • an Outlook Add-in that fits into the shippers existing workflow.

  • a Web Application that consolidates the shippers lane, quote rates, partner etc data in one dashboard.

  • These solutions have made the quoting process for shippers simpler and more efficient.

The problems in the shippers workflow were addressed in the following ways:

Problem 1 - Manual data entry from Excel

  • Templates: Shippers can create & save templates of frequented lanes on Portex Outlook Add-in. 

  • Contacts: Partners that shippers frequently do business with are stored on the Portex Outlook Add-in.

  • Automatic data capturing: Key data points e.g. lane rates, are automatically captured on the on the Portex Web App.

Problem 2 - Multiple email threads to manage

  • Consolidated Dashboard: Shippers can manage all quote requests to & from multiple partners on one dashboard on the Portex Web App.

Problem 3 - Inefficient comparison methods prone to human error

  • Comparison with Market Benchmarks: Real-time industry benchmarks are available on the Portex Web App for quick & accurate comparison.

Problem 4 - Back and forth on email and phone calls, and inefficient document management

  • Data storage in one place: Quotes can be sent out, booked and tracked all on the Portex Web App. 

Problem 5 - Manual report creation

  • Analytics & Reports: Automatic reports & analytics can be generated based on the data gathered on the Portex Web App.

Problem 6 - No benchmarking

  • Market Benchmark Data: Real-time industry benchmarks are available on the Portex Web App for quick & accurate comparison. 

Templates

Templates

Contacts

Contacts

Data Storage

Data Storage

Consolidated Dashboard

Consolidated Dashboard

Benchmarks

Benchmarks

Quote Comparison

Quote Comparison

Analytics & Insights

Analytics & Insights

CRITICAL REFLECTION

  • Used the JTBD framework to clearly define the Shipper persona: process, tools, key needs and pain-points

  • Using data science techniques to augment qual findings, expedite analysis and uncover other missing opportunities

  • Created a design partner programme to co-design with super users from different customer segments.