Jack Brugger - Qogita Case Study

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Also credits to design team — Alicia Bello, Daniel Bedoya, and Polly Leeman

Overview

Role — Product Design Lead

Discovery & Research

Vision & Strategy

Product Design

Qogita is Europe's leading health and beauty wholesale marketplace. Retail buyers can source premium brands and high margin products from a combined catalog of 500+ suppliers.

I partnered with senior leadership, two engineering squads, and the design team to shape predictive AI and allocation models. These systems dynamically match buyer demand with supplier liquidity to maximize fulfillment and margin. I translated buyer behavior into product requirements to make these decisions transparent, explainable, and trustworthy.

Key results

+30% more checkouts from first-time buyers

From 1 to 2.2 monthly returning order frequency

1.5x - 2× GMV growth per month

50% reduction in reported buyer confusion

Discovery

To understand the mindset of wholesale buyers, I led strategic research combining interviews, surveys, and behavioral analysis. We found that buyers are heavily shaped by supply scarcity, risk management, and margin optimization, operating with a trader-like mentality.

Importantly, we identified key differences between marketplace buyers and brick and mortar retail store owners: marketplace buyers are opportunistic and data-driven, often chasing deals based on scarcity and competition, while retailers value consistency, stable pricing, and supplier relationships. These insights shaped a product experience built to reflect the distinct logic of each buyer type.

Learnings

Buyers think like commodities traders. Marketplace buyers are supply-driven, Retailers are demand-driven

Marketplace buyers fear products being delisted from Amazon due to counterfeit or unregistered B-stock products

Retailers feel protected by stable prices and stock, whereas marketplace buyers feel protected by volume scarcity

Retailers avoid participation in the gray market due to fears of perception about their business practices

Marketplace buyers have a deep set of tools and methods for understanding technical indicators like price and risk

Retailers stick to products they know. Marketplace buyers are flexible and diverse

Marketplace buyers have various strategies like buying out major discounts and scooping up deals based on factors like scarcity, minimal availability, and low competition

100s of other fundamental learnings

Problem

Buyers on Qogita were assembling high-value orders, sometimes worth €1,000–€100,000, yet were frequently frustrated by opaque changes to prices and availability, due to Qogita's predictive AI order algorithm. This revealed broader systemic gaps in transparency, trust, and control across the wholesale buying journey.

To improve Qogita’s procurement experience, I collaborated with engineers and PMs to design solutions that gave buyers greater control, clarity, and confidence. We focused on three core goals:

1. Enhancing navigation tools to help buyers discover the best deals
2. Streamlining the checkout experience for greater efficiency
3. Boosting re-engagement through more powerful and useful watchlist features

Insights

10–15% of cart items couldn’t be checked out due to invisible supplier constraints

Qogita's AI: A lack of clarity on why changes occurred, causing frustration and cart abandonment

Buyers were perplexed by the order process, seeing it as a very opaque and intransparent system

Buyers struggled to find key categories like Vitamins & Supplements due to poor catalog visibility and confusing sidebar navigation

Buyers struggled to understand the breadth of brands available on Qogita and the depth of each brand's catalog

Retailers were scared off by a few poorly priced products when browsing the catalog

Solution

We executed 100+ releases across the product lifecycle, building a simpler, clearer experience that gave buyers more control and reduced confusion.

The design was tailored to support different buyer profiles: new buyers experienced a smooth, mobile-friendly flow for placing remote test orders, while returning power users benefited from advanced tools like grouped supplier views and minimum order value (MOV) tracking to manage larger, more complex purchases efficiently.

Key features

Price history graph: Gives buyers a snapshot of price volatility in the last 90 days

Advanced filtering: Allows buyers to filter specific categories, brands, and attributes like availability, performance, price momentum and more

Fixed Pricing. A control that prevents the algorithm from changing prices during cart allocation

Supplier Grouping. Group items in the cart by supplier with clear MOV targets, and allow buyers to adjust, remove, or add products

Supplier Inventory. A browsable selection of products easily addable to a locked-in portion of the cart

Price and quantity alerts: Buyers receive an alert whenever a product hits a specified target

Visit Qogita

Takeaways

Frame the fundamental purpose of who you are designing for before process, pixels and money

Designing software is strategy. Especially when building systems that relieve human control to machines

Be extra vigilant on achieving quality with the previous two statements, but stay lean so you move quickly

Jack Roland Brugger

Qogita

Creating a smoother wholesale trading experience for first-time and returning customers, boosting GMV and retention.

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