Tackling complex UX problems of international Shippers and Carriers by delivering a modern transportation software solution.
Role: Senior Product Designer
Team: Product Leader, Full-stack Engineers, Product Manager, and Carrier Ops
Addressing The Legacy in the room
Cross-Border Logistics is complex. It sounds simple at first: Shippers have materials (freight) that need to move across cities and Carriers help move that freight. However, there are several touch points through the lifecycle of a Load between negotiations, communications, dispatch, charges, invoices, and border paperwork. Forager connects these pieces. A critical piece of the equation includes capturing the “Capacity” of Carriers, which includes short-term and long term availability, service routes, and rate expectations. Capturing this data was often gathered and entered manually into different internal tools via conversations, a process including multiple phone calls, emails, texts, and What’sApp messages. This inefficiency slowed down users and the business and left lots of room for error.
The first iteration to solve for this problem included 2 separate workflows. This resulted in confused users, muddled data, and continuation of legacy communications to capture Capacity. To get more accurate data, automate and simplify the process, and support Carrier needs, the experience needed an upgrade.
Roadblocks of v1
Missing functionality for the business to segment rates by countries
Little insight into actual market rates
Low engagement and frustrated users
Inconsistent and inaccurate data collected
Confusing user experience for Carriers and Reps
Lack of flexibility to differentiate types of Carrier requirements for Capacity (short- or long-term)
No visibility around rates and conversions for Carriers
Brainstorm exercise revealing overlap in data types across different types of Capacity
Rerouting to a Solution
To revision the Capacity feature, the team interviewed Carriers to gain a clear understanding of pain points, process, and expectations during and after the Capacity data entry experience.
Reps wanted
a faster data entry process
to understand market costs to support their negotiations with Carriers
easier ways to capture the varying specifics of capacity requirements
to support the business in improving its unit economic price by understanding Carrier market prices better
Carriers wanted
less confusing tools in their day-to-day
to keep their businesses moving and need flexibility to enter rates in different formats
to communicate earning expectations before a freight opportunities reaches them
to be matched with freight opportunities instantly
visibility in to freight rate calculations
The Final Destination
Interviews revealed sharing Capacity data is a fluid but complex conversation between humans.
“Do you have trucks available?
Is this consistent?
You mentioned availability Monday, but I have this load on Tuesday, can you do that instead?”
How does this interaction translate to into a digital interface that removes direct conversation? What happens when you remove humans from the conversation? How are detailed requirements communicated and captured?
These are some of the questions that informed the solution for the new Capacity Inputs feature for Forager. The result was implementing these focus areas creating a new digital experience that mimicked a conversation between a Rep and Carrier.
For Reps
Simplicity
Progressive disclosure was utilized to display relevant content exactly when it was needed, eliminating previous clutter.
Efficiency
Carriers are selective with information released to Reps so validations and business requirements were revisited to eliminate friction to data entry.
Accuracy
An improved, more intuitive rates “calculator” was added to reduce manual efforts of converting rates, saving reps time.
For Carriers
Common Language
Logistics has highly specific vocabulary, but conversations are casual and direct so the new feature’s copy imitated this.
Voice and Tone
Reps and Carriers speak to each-other naturally, so data prompts were written as basic questions.
Familiarity
Content within the new feature was ordered similar to the construction of a call with a rep to avoid disorienting users.
The Outcome
Results on launch
18.35 Capacity entries collected per day; v1 averaged 1.33 per day
81% of entries captured were short-term, a Capacity type not supported in v1
1,156 entries of Capacity data collected in 63 days; 231 entries collected in 173 days with v1