Asia's First Cross border B2B Liquidation Marketplace

Introduction

Pollen is Asia's first cross-border B2B liquidation marketplace. We work directly with FMCG manufacturers who have slow-moving or obsolete inventory sitting in warehouses. Instead of letting these products expire or be written off, we connect them with bulk buyers who purchase at steep discounts, sometimes up to 90 percent off. Because many deals happen across borders, Pollen also supports the full export and import process, from compliance paperwork to logistics. To date, the platform has managed more than 20 million USD worth of inventory that would otherwise go to waste.

My role was to design the marketplace experience end to end. On the buyer side, I created a flow where bulk buyers can browse SKUs, negotiate, and check out in a single screen. On the seller side, I designed tools for uploading product lists, setting floor prices, and reviewing offers. I built the company design system in Figma so engineers could ship faster with consistent components, and I led research with real manufacturers and buyers to refine flows. Working closely with product and data teams, I also designed an AI-powered pricing recommendation interface that guided negotiations, increased adoption, and reduced deal rejections.

🛒 Buyer Platform, Pollen Pass

Pollen Pass is the buyer facing side of the marketplace. It allows verified buyers to browse manufacturer catalogs, place bulk orders, and track shipments in one place. Discounts run deep, making it attractive for distributors, wholesalers, and retailers sourcing inventory at scale.

Pollen Pass Flowchart

I worked closely with the product and engineering teams to design how platform features connect to each other. The flowchart maps this out, buyers start from catalogs, drill into SKU details with filters and sorting, then move into offers. Each offer has a clear state, waiting for seller response, waiting for buyer response, proceeding to order, or rejected. Once accepted, the deal transitions into shipment tracking. Around these core flows, we added account settings, company profiles, notifications, and user profiles to complete the experience.

Pollen Pass, Make Offer

The Make Offer screen was designed directly from conversations with buyers. Many told us they were most comfortable working in an Excel style view where all details are visible at once. We built a table layout that lists every important field, SKU number, price per pallet, price per unit, expiry date, warehouse location, package type, total units, asking price, retail price, and more.

Pollen Pass, Offer Summary

To reduce back and forth, we added automatic calculations. Buyers can instantly see totals by weight, price, or volume as they adjust quantities and prices. This way, they can make decisions faster, submit precise offers, and avoid mistakes during negotiation.

🛍️ Seller Platform, Liquidation Management System, LMS

The seller platform was designed for FMCG manufacturers managing excess or near expiry stock. Sellers can upload product data, track inventory, and create catalogs that are instantly visible to buyers. We focused on making data migration easy so that large product lists can be imported without friction.

LMS, Product Management

LMS, Product Details

Sellers get a clear overview of their inventory in one dashboard. Each product entry shows batch information, expiry dates, warehouse locations, and package types. This helps sellers manage stock efficiently and know exactly what they have available for liquidation.

LMS, Flowchart

When a new offer comes in, sellers can choose to accept, reject, or counter with revised terms. The flowchart maps out every state of the process so sellers always know where a negotiation stands. This streamlined decision flow reduced time spent on back and forth communication.

LMS, Offer Detail

The Offer Detail screen displays all the information tied to an offer, including price, quantity, buyer information, and supporting documents. Sellers can review everything in one place before making a decision. This reduces errors and makes approvals faster.

LMS, AI Pricing Recommendation

One of the hardest problems for sellers is knowing how to price excess stock. Near expiry goods are often overpriced by sellers or lowballed by buyers. To address this, I worked with product and data to design an AI powered pricing recommendation. The system uses the Pollen SLOB Index, historical sales data, and expiry timelines to suggest fair price bands. By showing sellers a clear range and explaining the logic, adoption went up and pricing related deal rejections went down.