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Finning

A self-serve dealer portal and finance calculator for a major Caterpillar equipment dealer, turning multi-step sales conversations into a quote and repayment flow buyers can run themselves.

finning / equipment

Read time
~6 min read
Client
Finning
Timeline
2022
Role
Product designer
Team
Designer (me) 2 other designers 2 Back-end developers 1 Front-end developer 1 Project manager 1 Analyst

The brief

Finning is the world's largest Caterpillar dealer. Buying heavy equipment through them was, by tradition, a salesperson-mediated process: a customer expressed interest, a rep worked up a configuration, and a finance quote came back later after manual back-and-forth. It worked, but it was slow, opaque on price, and it tied up the sales team in early-stage questions that did not need a human yet.

The brief was a self-serve dealer portal: let customers browse the equipment catalogue, understand a machine, and generate a transparent finance and repayment estimate on their own, then request a quote or callback to hand off to sales exactly when they were ready. My role was product discovery and UX across the catalogue, product detail, the finance calculator and the quote handoff. Engineering built against the flows that came out of the design work.

Self-serve
Quote and repayment estimate, no sales call required to start
<1 min
From machine to an indicative monthly repayment
Catalogue
Equipment, specs and finance in one portal
Job-site ready
Designed to work on a phone, not just a desk
Problem

Buying a machine meant waiting on a person to tell you what it would cost.

Four problems tangled into one slow start. The core issue was not the catalogue, it was that the most important answer, what will this cost me per month, lived inside a sales conversation.

Where it hurt

Getting a price and a repayment estimate required back-and-forth with a sales rep. The single thing most buyers wanted first was the thing the existing journey made them wait longest for.

Who felt it

Contractors and buyers who wanted to compare and budget before talking to anyone, and a sales team spending its time on early-stage questions instead of closing.

The trap

Equipment finance is genuinely complex, term, deposit, balloon, APR. Oversimplify it and the number is wrong; expose all of it and you overwhelm a buyer who just wants a ballpark.

The hardest case

An enterprise catalogue of machines, specs and variants that still had to be usable on a phone, often by someone standing on a job site, not sitting at a desk.

A dated Finning enquiry form promising a sales advisor will call back within two working days, with no pricing
The way you used to get a price, a form and a callback, no numbers
A Finning equipment listing where every machine shows price on application and a contact-us button
No way to self-qualify, every machine just said 'contact us'
Research

Understand what a buyer needs to know before they are ready to talk to sales.

A focused discovery loop: map the current sales-led journey, then learn which questions buyers want answered themselves and which finance variables actually drive the decision.

Q1

What does a buyer want to know on their own, before they are willing to start a conversation with a sales rep?

Q2

Which finance variables genuinely change the decision, and which can be sensible defaults so the calculator stays simple?

Q3

How much of this journey happens on a phone, and what has to survive being used on a job site?

What the journey told us

Mapping the sales-led process, the friction was front-loaded. Buyers stalled at the very start because they could not self-qualify, they had no way to see whether a machine was even in budget without booking a conversation. The finance question was not a late-stage detail; it was the gate to everything else. Make the repayment estimate self-serve, and the rest of the journey opens up.

"I don't want a sales pitch yet. I want to know roughly what it lands at per month, then I'll pick up the phone."Buyer interview

That set the design principle: answer the money question first, hand off to a human second. The calculator does the qualifying; the callback request is the bridge to sales, placed exactly where intent is highest.

01 · Business brief & audience

Who's actually walking onto the lot?

The client brought a business brief: update the site, give desktop and mobile users more to work with, and make the platform an integrated lead engine for Caterpillar. A lead engine is only as good as its read on who it's selling to, so the first method was audience segmentation, straight from the brief.

brief
OBJ

The platform's one job

An integrated solution for Caterpillar to generate leads through digital marketing.

Everything downstream gets measured against that line. A prettier site that doesn't move leads is a fail. So I held two questions over every later decision: does this help a real buyer get to a real enquiry faster, and does it qualify them on the way?

AUD

Audience segmentation

The brief named the audiences. I split them into primary (the buyers the platform is built around) and secondary (real, but they convert differently). This is the frame personas and stories get built on top of.

Primary · 01

Construction

Firms buying or hiring earthmoving and site kit. Spec-led, deadline-driven.

Primary · 02

Industrial

Power systems and engines for plants and facilities. Uptime is the whole game.

Primary · 03

Agriculture

Seasonal, weather-bound buyers. Need the right machine before the window shuts.

Secondary · 04

Rental services

Buying to rent out. Watching residual value and total cost, not just sticker price.

Secondary · 05

Freelance

Owner-operators and non-customers. Price-sensitive, can't buy outright, easily lost.

Primary groups buy on spec and availability; secondary groups buy on access and affordability. Same catalogue, two different jobs to design for.
Open question carried into research: the secondary groups, especially freelance, are where the platform leaks. Can financing pull them across?
How I read the brief

A brief names the audience. It doesn't tell you where the money leaks.

The brief is the start, not the answer. It told me who Finning sells to. It didn't tell me where those buyers quietly give up and ring a competitor instead. That's what the next three methods are for, competitor analysis to find the missing capability, personas to get inside the buyer, A/B testing to prove the fix.

My read: the win here isn't a redesign for its own sake. It's closing the specific gaps that send a ready buyer somewhere else.

Method order

01  BRIEF → AUDIENCE SEGMENTS
02  COMPETITORS → FIND THE GAP
03  PERSONAS → THE BUYER'S QUESTIONS
04  STORIES → WHAT TO BUILD
05  A/B → PROVE IT MOVES LEADS

02 · Competitor analysis

JCB had one thing Finning didn't.

I benchmarked Finning against its main rivals, John Deere, JCB and Hyundai Construction Equipment. All three run a credible online presence with their kit on show. The analysis wasn't about copying them. It was about finding the one capability whose absence was actively costing leads.

benchmark
MTX

Capability matrix

Dealer Product catalogue Used equipment Request a quote Financing on platform
Finningbefore this project Yes Yes Call only Missing
JCB Yes Yes Yes Yes
John Deere Yes Yes Yes Partial
Hyundai CE Yes Limited Yes No
THE
GAP
Single biggest finding

JCB let you finance a machine on the site. Finning made you phone in for it.

That's the strength JCB held over Finning, a financing function in the interface. Every other box was roughly level. This one wasn't, and it sits right on top of the platform's one job: generating leads. A buyer who can't see the monthly cost picks up the phone to ask, or doesn't, and goes to the dealer who already showed them.

STR

Where Finning is strong

Largest CAT dealer globally. The brand and the catalogue depth are real advantages, not marketing lines.
New and used CAT plus non-CAT in one place. Genuine range for mixed fleets.
Service and parts network behind the sale. Competitors can't easily match the support footprint.
WK

Where it was leaking

No on-platform financing. The buyer's first money question had no answer on the page.
Quotes meant a phone call. Friction sits exactly where intent is highest.
Weak visual hierarchy buried spec and price, the two things buyers actually scan for.
The bet

Move the money conversation onto the page.

If a buyer can model a monthly payment before they ever speak to a human, the call they make is no longer "how much would this cost me?" It's "I want this one." That reframes the lead from a cold enquiry into a warm, qualified intent. That's the bet, and it's what the user stories in section 04 are built to deliver.

One competitor finding, sitting on the platform's one job. That's the thread the rest of the work pulls on.

Benchmarked against

▸  JOHN DEERE
▸  JCB  // the finance gap
▸  HYUNDAI CONSTRUCTION EQ.

All three maintain a product-led web platform. JCB was the only one whose interface answered the financing question before the call.

03 · Personas

Two buyers. Same catalogue, different fear.

Personas turn an audience segment into a person with needs, behaviour and motivation, so a screen has someone specific to answer to. I built two from the segmentation: the freelance owner-operator (the segment that leaks) and the fleet & procurement buyer (the segment that spends). Both end on the questions they actually ask.

2 personas
DK
Persona 01 · Freelance / owner-operator

Dele, the
self-employed operator

18–50EntrepreneurIndependent
Who they are
Runs solo or with a small crew. Driven, hard-working, fiercely independent.
Every job carries extra responsibility; the machine is the business.
Finds information across laptop, mobile and email, via search engines, industry blogs, social groups and direct marketing.
What they want
To secure machinery in a few steps, not a fortnight of back-and-forth.
To view and compare multiple machines side by side.
To contact the business with any further questions, on their terms.
Pain points
Securing machinery is slow; too much back-and-forth before it arrives.
Buying outright is expensive; cash flow is the constant constraint.
No clear way to know the monthly cost without committing to a conversation.
Motivation
Being financially independent and building a strong network of clients.
"Can I finance it, and how long until it's on site? If I can't answer that fast, I'm onto the next dealer."
RM
Persona 02 · Construction / fleet buyer

Rita, the fleet &
procurement manager

35–55Mid-size contractorAccountable
Who they are
Owns equipment decisions for a construction firm running multiple sites.
Answerable for total cost and uptime, not just the purchase price.
Researches on desktop in detail, shortlists, then talks to a named account contact.
What they want
To compare full specifications and configure parts, attachments and CVAs.
To see how financing options change the monthly picture across a fleet.
A fast, accurate quote that procurement can sign off without chasing.
Pain points
Spec and price are hard to scan; comparison means juggling tabs and PDFs.
Quotes take days of phone and email before a number lands.
No single view of how customisations move the cost.
Motivation
Keeping sites running and decisions defensible to the people above her.
"Show me the spec, the monthly cost with our config, and a quote I can take to finance. Then we'll talk."
Q

The questions both buyers walk in with

Personas earn their keep when they hand you a checklist. Here's the one this pair produced. Every later screen had to answer these, and the finance calculator answers the two that were costing the most leads.

How can I see the machinery specification?
Can I order used equipment, not just new?
Can I finance the machine on the platform?
How long will it take to arrive?
Can I get a quote first, before committing?
Can I contact the business for more detail?
Two of these six, "can I finance it" and "can I get a quote first", are pure money questions. Both were unanswered on the page. Both became the finance-calculator brief.
Discovery

From a sales-gated quote to a self-serve estimate, with the rep brought in at the right moment.

User stories turned the research into a build order, then A/B testing proved which version of the finance journey actually converted.

04 · User stories

The finance calculator, written as requirements.

The competitor gap and the persona questions both pointed at one build: an on-platform finance calculator. Before any UI, I wrote it as user stories, so what we shipped traced back to a real need. The bet is simple. The calculator replaces the call where a buyer asks for a quote, so by the time they do call, it's to complete the hire or purchase.

build spec
US-01Customer

As a customer I want to know what term options are available so I can match repayment to my cash flow.

Acceptance criteria
Available terms shown as selectable options, in months
Monthly figure updates the moment a term is changed
US-02Customer

As a customer I want to know my monthly price after down payment and interest so there are no surprises later.

Acceptance criteria
Down payment is an editable input
Monthly price recalculates from cash price, deposit, term and rate
US-03Customer

As a customer I want to see how payment changes with customisations (attachments, parts, CVAs) so I'm pricing the machine I'll actually run.

Acceptance criteria
Add-ons adjust cash price and the monthly figure live
Each add-on's cost is itemised, not hidden in a total
US-04Customer

As a customer I want the terms and conditions of financing visible so I can trust the number I'm looking at.

Acceptance criteria
Legal disclaimer present alongside the result
Representative rate and basis of calculation stated
BR-01Business requirement

As a business we need to surface cash price, monthly price, monthly term(s), a down-payment input and a legal disclaimer on the calculator.

Why it's mandatory
These five are the minimum to make a payment figure honest and compliant
Finance calculator · wireframe
Machine
CAT 320 Excavator used
Cash price [US-02]
£128,400 ex VAT
Down payment [input]
£25,680 20%
Term [US-01]
24
36
48
60
Customisations [US-03]
+ Hydraulic thumb £3,200
+ CVA · 3yr £6,900
Cash price£138,500
Term36 mo
Monthly price
£3,140
per month · after deposit + interest
Request this quote
[US-04] Representative example. Finance subject to status and a credit agreement. Figures are indicative and not a binding offer. Full terms apply.
Every input on this wireframe traces to a story. No control exists without a need behind it.
The CTA isn't "buy", it's "request this quote". The calculator qualifies the lead; a human still closes it.
Why stories, not a wishlist

A control with no story is just decoration.

Writing the calculator as stories did two things. It kept the build honest, every field answers a stated need, and it gave the client a shared definition of done before a pixel moved. When a "nice to have" came up later, the test was easy: which story does it serve? If none, it didn't ship.

The reframe that matters: the calculator doesn't sell the machine, it qualifies the buyer. It turns a cold "what would this cost" call into a warm "I want this one" enquiry. That's the lead the brief asked for.

Five mandatory elements

01  CASH PRICE
02  MONTHLY PRICE
03  MONTHLY TERM(S)
04  DOWN-PAYMENT INPUT
05  LEGAL DISCLAIMER

05 · Usability & A/B testing

Twelve designs, built to be measured.

The client handed over unmoderated usability data: real users completing tasks with their screens recorded, showing the clicks and journeys they preferred. I read that as a map of where intent stalled, and turned it into 12 designs across desktop and mobile for A/B testing, each one a hypothesis with a metric attached.

12 variants
DATA

What the unmoderated data told me

Clicks
logged

Where users tapped, and where they hesitated. Hesitation is a design smell.

Journeys
traced

The routes users actually preferred, not the ones the IA assumed they'd take.

Tasks
recorded

Screen recordings of real attempts. You see the stall before they rage-quit.

A/B

Test matrix

Experiment Desktop Mobile Hypothesis Measured by
Search functionalityfind a machine fast D M Buyers with a model in mind want search, not menus. Make it the default path. clicks to result
Nav bar redesignget oriented D M Clearer categories cut dead-ends for buyers who browse without a target. task completion
Product spotlightsurface the right kit D M A focused spotlight lifts engagement over a flat grid of everything. click-through
Reserve producthold it now D M Mobile buyers want to reserve in the moment. Capture intent before it cools. reservations
Finance calculatoranswer the money question D M On-platform financing converts a "how much" call into a qualified lead. qualified leads
Request a call backreach a human D M A cleaner call-back ask lowers the bar to a high-intent enquiry. enquiries
DSK

Desktop track

Desktop is where the fleet buyer researches in detail. Variants leaned into spec comparison, the calculator and clear call-back.
Search-first and the finance calculator are the two I'd back hardest to win, both sit on the highest-intent moments.
MOB

Mobile track

Mobile is where the freelance operator moves between sites. Variants prioritised speed: search, reserve, one-tap call-back.
Reserve is desktop-optional, mobile-essential. The data showed mobile users wanting to act in the moment.

Every method fed the next one.

The brief named the audience. Competitor analysis found the gap. Personas turned the gap into a buyer with questions. User stories turned the questions into a build. A/B testing is how that build earns its place in production instead of someone's opinion winning the room.

My read on this project: the leverage was never the visuals on their own. It was following one competitor finding all the way to a tested, qualified-lead machine. That's the work.

BRIEF
↓
COMPETITOR GAP
↓
PERSONAS
↓
USER STORIES
↓
A/B TESTING

Product

The screens that let a buyer qualify a machine on their own.

Catalogue, product detail, and a finance calculator that answers the money question first, designed to work on the desk and on the job site.

Impact

A buyer can now qualify a machine before sales ever picks up.

Self-serve
Quote and repayment without a sales call to start
<1 min
From machine to an indicative monthly repayment

The intended shift was where qualification happens: move the money question to the front of the journey so buyers self-qualify, and let the sales team spend its time on warm, ready conversations instead of cold early-stage ones.

OUT

Expected outcomes

↑
Qualified leads

The calculator filters out price-shopping calls and warms the ones that come through.

↑
Customer satisfaction

Buyers self-serve the answers they used to chase, on the surface they prefer.

↑
Accessibility

Cleaner hierarchy and mobile-first journeys widen who can actually use the platform.

These are the outcomes the A/B program was built to prove, not claimed results. Each variant carried the metric that would confirm or kill it.

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