Lead UX/UI DesignerResponsive Marketing & Catalogue SiteIndustrial Cleaning Equipment

Billion Plus Website

BEURDEV CO., LTD. · Mar 2024 – May 2024
Billion Plus Service website — industrial floor-cleaning machine catalogue, specification tables and rental
Executive Summary & Impact
Real-world
Match between system and the real world
catalogue grouped by cleaning task, not model name
Recognition
Recognition rather than recall
spec tables size a machine against a known floor area
Prevention
Error prevention
rental route stated in the hero, before a buyer leaves

A catalogue site for an industrial floor-cleaning equipment supplier that sells, rents and repairs. It is designed for a facilities manager who knows their floor and their shift rather than the product range, so the catalogue is organised by task and the specification tables answer the sizing question directly.

01 / Discovery & Heuristic Gaps

Problem & Usability Gaps

A floor-cleaning machine is usually bought by a facilities or plant manager rather than an equipment specialist. Read against the heuristics, a catalogue organised by model name asks them to learn the supplier's vocabulary before choosing; the specification that decides a purchase, how much floor a machine clears per hour, needs to sit against the sizes on offer; and the rental option, often the better answer for a one-off clean, is easy to miss on a page shaped for sales.

Model-led
catalogue organised by product code, not cleaning task
Sizing unanswered
no way to size a machine against a known floor area
Rental hidden
the cheaper route easy to miss on a sales-shaped page
02 / Architecture & UX System

Design Decisions by Heuristic

01
Match between system and the real world
Catalogue Grouped by Cleaning Task
Machines sit in the classes a facilities manager already uses, from compact floor washers and single-disc machines to walk-behind and ride-on scrubbers, with a category menu that also reaches sweepers, vacuums, pressure washers and the chemicals that go with them. A buyer enters at the job, not the product code.
02
Recognition rather than recall
Specification Tables That Answer the Sizing Question
The rental page sets each machine's brush size against tank capacity, cleaning throughput per hour and rental term, in one table for each type of scrubber and sweeper. A manager who knows their floor area and shift length reads the right size off the table instead of describing the problem to a salesperson.
03
Error prevention
Sell, Rent and Repair Stated in the Hero
The three lines sit directly beneath the brand name, with the rental entry price on the same screen. A visitor for whom renting is the better answer finds it before leaving, rather than after buying the wrong way.
04
Consistency and standards
One Card for Every Machine
Every machine in the catalogue uses the same card, a photograph on white, the model name, a short description and a link to its details, under a class heading with a paragraph on what that class is for. Once a buyer has read one card they can scan the rest.
03 / Verification & Evidence

Before & After by Heuristic

HeuristicBeforeAfterChange
Real-worldModel number as the entry pointMachine class and cleaning taskRestructured
RecognitionAsk a salesperson to sizeThroughput set against size in a tableSelf-serve
PreventionRental behind an enquiryRental entry price in the heroSurfaced
ConsistencyA long list of modelsOne card per machine, grouped by classUniform

"A plant manager does not want a machine; they want the floor clean before the next shift. Publishing throughput against size turns the catalogue into a calculation they can run themselves."

— Design rationale · Billion Plus Website
04 / Retrospective

Design Learnings

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Buyers navigate by the constraint they own, floor area and shift length, not by the supplier's product codes, so the deciding specification belongs in the table.

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Stating every route in the hero is cheap error prevention: three words stop a rental customer leaving a page shaped for sales.

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A class heading with a short explanation helps a non-specialist more than a filter does, because it tells them which group their job belongs to before they look at a single model.