Coolblue, a leading electronics retailer in the Netherlands and Belgium, is renowned for its exceptional customer service and playful marketing style. During my time there, the company was undergoing a significant transformation, modernizing its backend systems to streamline operations and enhance efficiency.

Problem

Why this project?

Our business analysts identified the slow and unreliable restocking process as a major obstacle to revenue growth. Frequent product unavailability hindered our ability to compete in the market and maximize sales.

Desired outcome

We had 3 overarching goals in mind:

1. Increase the frequency: Ensure products are replenished more frequently.
2. Reduce overstocking: Minimize excess inventory to optimize warehouse space.
3. Automate easy decisions: Streamline the process for routine restocking tasks.

Our team aimed to optimize the restocking process by increasing product availability, reducing excess inventory, and automating routine tasks. By creating a learning system that could handle common restocking decisions, we sought to free up buyers’ time for strategic initiatives like long-term planning and supplier negotiations. This would not only enhance efficiency but also mitigate the risks associated with human factors, such as memory lapses or turnover, which can negatively impact stock availability.
For example: making sure to secure a stock of barbecues in black, red and green in the winter so they can sell them in the summer of next year. This is an example of how the skills of a buyer can be better applied since it requires active communication with manufacturers, negotiation about price, signing of deals, etc.
Additionally, we wanted to lessen the burden in the memory of a buyer. People grow, move to other companies, get sick, forget things. All these circumstances hinder the performance of stock availability in a store.

Audience

For who are we building this?

While a well-stocked store directly benefits customers, this tool was primarily designed for Coolblue’s employees, specifically the buyers responsible for managing restocking orders. Each buyer was equipped with a standard desktop PC, complete with a monitor, mouse, and gamepad controller.

Roles and responsibilities

My responsibilities

As the first UX designer to delve into Coolblue’s back-office systems, I had a broad range of responsibilities. I had to gain a deep understanding of the business operations, partner dynamics, and the specific needs of restocking buyers. Additionally, I engaged with stakeholders to gather their perspectives and understand the factors influencing their decisions, including the significant influence of the CEO.

Scope and constraints

Limitations

Rather than A/B testing, we evaluated the product’s performance using key business metrics. Given the relatively small user base of 12-24 individuals, it was feasible to conduct qualitative / exploratory research, such as user interviews, with all users.

Process

Step by step description

This text reflects the state of the product during my time at Coolblue. I believe it has evolved significantly since then. For example, the original version was designed for Windows desktops, whereas Coolblue has transitioned to a web-app model.

1. User interviews

As a pioneer in UX design for Coolblue’s back-office systems, I initiated this project before a dedicated product owner was appointed. To gain a comprehensive understanding of the business processes, I conducted interviews and observations with various Coolblue employees. Through this research, I familiarized myself with the company’s internal logistics, customer experience goals, and the intricacies of the restocking processes.

Customer journey map

The image illustrates the complete customer journey, from initial consideration to purchase. This visual representation helps guide customers through the buying process, even before they actively engage with the product.

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2. Work as them

To gain a practical understanding of the process, I role-played as a buyer, using the existing tools to place orders. Through this hands-on experience, I gained valuable insights into the intricacies of the decision-making process, identifying three key factors that influence buyers’ choices.

1. Should I restock now?
   The software determined the need for restocking by identifying products with low stock levels. To assist buyers in making restocking decisions, the system presented relevant information.
2. If yes, how much should I restock?
   The optimal restocking quantity was influenced by factors such as available warehouse space and supplier stock levels, which were not always readily accessible. Some suppliers provided real-time stock information, while others did not. Additionally, contractual agreements and delivery lead times varied among suppliers.
3. Can I restock from my selected supplier?
   This depends on the points mentioned above, contracts, delivery time, stock transparency.

The feasibility of restocking from a specific supplier depended on these factors, including contract terms, delivery times, and stock transparency. To gain a better understanding of warehouse limitations and existing tools, the team conducted two on-site visits to the warehouses.

3. Ideation sessions

Through collaborative brainstorming sessions, facilitated by the product owner, we identified the potential to automate many of the restocking decisions while reserving complex tasks for buyers. These discussions also highlighted the critical role of the restocking process within Coolblue’s overall operations.

3.1. Mapping the old process

To effectively design the product, we focused on understanding the interactions between users and both physical and digital systems across different business areas. I created a visual sequence to illustrate the steps a buyer would take to decide whether to restock a particular product.

5. Guerilla testing

Testing with the end-users was straightforward in this case. Simply sharing a link to the InVision prototype allowed them to walk through the design. I carefully documented their feedback and presented it to the team for analysis.

6. Hi-fidelity prototyping

The tool was designed for simplicity, focusing on a single decision at a time. Our goal was to provide buyers with the most relevant information to facilitate quick and accurate restocking decisions.

The tool would automatically identify items needing restocking, and buyers would assess whether to restock, the quantity, and the preferred supplier (initially limited to one). After making a decision, the screen would update, and the process would continue until all restocking needs for the day were addressed.

7. Probing after release

Following each sprint, I conducted feedback sessions with buyers to gather insights for product improvement. After several iterations, we invited buyers to our team room for a demonstration of the application (Vanessa Purchandez). This hands-on session allowed buyers to interact with the app, share their experiences, and ask questions directly to the development team.

8. Demo

During each sprint, we held demos attended by buyers and other stakeholders. These sessions served two key purposes: to showcase new app features and discuss progress toward our key performance indicators.

Conclussion

Results

Learnings