Get extra storage
when needed
Redesigning the warehouse capacity request workflow
ROLE
UX Designer
COMPANY
Amazon
DURATION
Jan - Dec 2024
How sellers manage Amazon warehouse storage capacity is a critical aspect of successful selling that directly impacts a seller's bottom line. When sellers can’t effectively manage their capacity, they risk revenue loss from stock-outs and increased costs from excess storage fees. Proper capacity management enables sellers to maintain optimal inventory levels for peak seasons, launch new products, and sustain a competitive advantage through consistent stock availability of high-selling products. These factors ultimately contribute to better cash flow and profitability.
Sellers struggle to request additional capacity using the current interface.
Amazon sets a monthly storage limit for Fulfillment by Amazon (FBA) sellers based on sales forecasts, taking into account their past sales performance. This limit determines the amount of inventory a seller can send and store. Additionally, sellers can request extra capacity if they are confident that they will have higher sales volume than what Amazon has forecasted. Requests are granted objectively through a bidding process, where the highest fee sellers are willing to pay per cubic foot are prioritized. This fee is called the capacity reservation fee. If sellers reach the sales volume for which they requested extra capacity, Amazon fully offsets their reservation fee. Currently, sellers find it difficult to request more FBA capacity through the existing interface.
My role
I redesigned the FBA capacity request creation workflow to improve discoverability and add signals that help sellers identify when they need more capacity. The new design also makes requesting additional capacity easier through a guided process. In my role as the main UX designer for this project, I worked closely with product managers, engineers, and UX writers to bring it to life.
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​​To comply with my non-disclosure agreement, I have omitted and obfuscated confidential information in this case study. All information in this case study is my own and does not necessarily reflect the views of Amazon.
How did we reach there?
Before this project, sellers used Excel to determine their reservation fees and estimate performance credits. The goal was to improve this calculator by developing a web page with additional features, such as suggesting the total capacity needed based on sales forecasts. The team believed that a better calculator would help sellers identify the capacity they require, making it easier to submit accurate requests. This new version would also automatically suggest the reservation fees they should bid and the expected performance credits. The team believed that this improved calculator would help resolve the current issues with creating capacity requests.
Should we create a better calculator or is one even needed?
When the team requested this calculator, I questioned its need and began to explore several questions.
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How do sellers determine the extra capacity they need, and what methods do they use to forecast it?
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When do they request additional capacity?
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What is their understanding of reservation fees?
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How do they set up these fees?
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What do they know about performance credit, and how do they currently estimate it?
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What happens if they don't find the calculator?
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What are sellers’ opinions on using this tool? What value does this calculator provide?
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How much effort do sellers need to put in to use it effectively?
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To answer these questions, I conducted a UX audit to identify ways to improve the capacity request process. I also interviewed six US-based FBA sellers, including both resellers and brand owners.
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The interviews uncovered key issues sellers face when requesting FBA capacity. Based on these findings, I identified the challenges sellers encounter within the current system and their process of requesting extra capacity.
Securing stakeholder consensus on a revised design:
After analyzing these findings, I realized we must overhaul the capacity request creation process. The problem lies with the entire process, and the calculator only made it more complicated. Interviews revealed that sellers often struggle to decide when to request more capacity and how much to ask for to stay profitable. We need to develop a user-friendly interface that guides sellers on when to request additional capacity. It should also enable them to quickly estimate their capacity needs and determine the appropriate reservation fee based on the expected offset. Gaining stakeholder approval was crucial because this approach significantly differs from our original plan.
Using customer feedback to find common ground:
Amazon promotes a data-driven and customer-focused approach. To gain stakeholder buy in, I gathered customer feedback on the new designs, which will help build their confidence in this strategy.
The concepts I created were centred around​​​​
A workflow that guides sellers through request creation, eliminating the need for a separate calculator.
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The capacity request creation workflow takes minimal inputs and suggest the optimal storage sellers should request, the reservation fee they should set to receive the maximum performance credit.
Rethinking the navigation to enhance discoverability
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Following sellers’ feedback about difficulty finding the capacity widget, I suggested adding ‘Manage Capacity’ to the L2 navigation menu.
I conducted 2 rounds of usability testing (Unmoderated + moderated) to evaluate whether sellers can accomplish certain tasks and dive deep into sellers sentiment around the new concepts and identify improvement opportunities.
The key objective include:
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Learn where do sellers expect to find the capacity. Uncover their thought process around their chosen path
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Evaluate how sellers are using the Manage capacity page?
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Evaluate the new workflow to request additional capacity.
Key insights I found​​
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All participants found the appropriate spot in navigation to feature capacity is within the inventory category. As they think capacity is only relevant to manage inventory.
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They wanted to prioritise the storage category that is relevant to them. As they don’t necessarily sell in all categories or not all categories need attention.
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Sellers highlighted that the shift to units in capacity aligns with their mental model​.
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Majority of the sellers were looking to assess opportunities to optimise capacity usage while reviewing capacity usage trend. They were mostly focused on the maximum and minimum levels of capacity usage and explored suggested strategies for maximising capacity usage, such as reducing slow moving items which are using high capacity.
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9 out of 9 participants could successfully request additional capacity and they preferred the ability to request for additional capacity without having to calculate the values. Majority of the participants suggested that sometimes they know how much extra capacity they need, and they just need to enter that value and submit the request without Amazon’s recommendation.​​​​
Going back to iteration and brainstorming with Product managers and tech team​​
Bringing all the insights together and creating the version shipped to develop
Impact of the launch
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The preliminary A/B testing results show: 1) Capacity request completion rates are higher (61.10%) for treatment group across all marketplaces vs the control group (53.94%)
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Among the successful request submission, granted rates are higher for treatment group.
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The initial observation seem to indicate the new workflow leads higher completion rate and more quality bids.
Reflection
During conflicts, quick usability testing with customers and sharing feedback with product and tech teams can speed progress.
I realised stakeholders have conflicting views. Many decisions focused on what tech can achieve for an on-time launch. I shifted focus to the seller’s perspective, using exploratory research and a seller journey map to identify struggles. I hosted ideation workshops with key stakeholders to explore touch points and opportunities, involving product managers in interview sessions. Despite chaos and different viewpoints, close collaboration with product and tech teams on usability studies helped me progress faster.
Achieving alignment through frequent design review sessions.
I regularly included my partner teams and design leadership in review sessions, where I presented multiple solutions along with their pros and cons.