Designing a better IA for sellers on Amazon.


Amazon Marketplace is an e-commerce platform built by Amazon to give third-party sellers a way to sell their products to Amazon's customer base.

Our team at Proximity Germany was tasked to redesign the Amazon Marketplace website, a first point of entry for prospective sellers. The goal: to increase both the quality of sellers entering the registration funnel, and the conversion rate.

After a deep dive into the data and reviews from potential sellers what started off as a purely visual task turned out to be a much broader architectural and content challenge.

Being a data-driven company, Amazon focused on optimising the website exclusively for conversions as easily quantifiable results. Without clearly addressing or showing understanding of seller needs it bombarded users with registration CTAs creating a confusing and generic experience.

Applying a user-centric approach, we established user research practices for the Amazon Marketplace team helping them understand seller needs and painpoints. We turned a structure that focused on describing specific services into one that caters to sellers at different stages of the journey and introduced a number of quick improvements along the way.

My role

I worked alongside the customer experience lead and a data strategist to research customer needs through user interviews, identify seller types, their pain-points and areas of friction. Our team of three then worked to develop the strategy for evolving the customer value proposition, website's purpose, language, information architecture and design principles.

We rebuilt the architecture, killed the noise and rewrote necessary content to ensure that sellers in the UK, Spain, France, Italy and Germany are now supported when they decide to sell on Amazon.
By bringing user-centric practices to the team at Amazon we helped switch the mentality from designing for conversion to designing for solving pinpoints.
Read on for a full case study
Unpacking the challenge

We started this project with a very broad task of redesigning the experience. To gather first insights on what issues potential sellers might be having with the existing website we jumped into research.

Due to certain business restrictions our ability to talk to users was extremely limited, so we had to get creative.

We paired a deep dive into client supplied quantitative data with a guerilla usability testing that helped us translate data patterns into actionable insights rooted in user behavior. We then validated these insights through social listening and by actively posing questions in existing seller communities online. This research was complemented by a formal heuristics analysis to identify design flaws, inconsistencies and areas where user error is likely.

As a result we identified five core areas of pain points in the existing seller experience:


Although Amazon Marketplace has two distinct types of sellers it caters to, the website is not addressing either of them distinctly leaving both audiences lost.


Potential sellers are hearing negative comments about selling on Amazon that are not acknowledged or addressed on the website in any way.


The website is not relevant to the user’s decision making journey with the content being both too generic and too jargon-heavy.


The users are not engaged and are not being guided through by the website to help them find the right information for their needs.


The site is organized around services rather than solutions for user needs making it hard for potential sellers to see the value for their business.

Defining the users

With a clearer challenge at hand we kicked off the discovery phase by going through all the  data to design personas that would represent the audience for the experience and ensure we keep our approach to design user-centric.

Data gathered at the previous step helped us flesh out each persona using empathy mapping. While diving deeper into what each of our potential users was thinking, feeling, seeing and doing, we discovered there was one more persona on top of the two types of audience Amazon was already aware of.

How do we break up the needs of these users across the website over time?
Mapping the journeys

We needed to understand how the three types of sellers go through the decision making process for joining Amazon Marketplace to define what role the website plays at each stage, what are the main pain points and how the website can help sellers overcome the barriers so they can move along the  funnel.

For this we built customer journey maps for each of the personas along an Amazon Marketplace specific funnel.

How do we cater to the needs of all our users if we can't identify them on the website?
Overcoming the barriers

Having gone deep into the detail of actions and pain points of each specific customer journey we had three existing experiences we were now aiming to bring into one that helped overcome barriers for all three types of users. For this we had to go away from specific journeys and back to an abstract level of thinking.

To figure out what our customers had in common we used thematic clustering to identify common groups of barriers.

We then mapped those barriers against the decision making funnel to visualize the points with the most issues and get clarity on what these issues were.

Taking care of future decisions

At this point we found ourselves facing a challenge of needing to make decisions regarding the specific solutions, tone of voice and design language. Without the chance to validate our decisions with the audience or existing guidelines it was getting harder and harder to establish a rationale for one decision or the other.

To streamline the process and set us up for success when selling work to the client we agreed on a set of design principles that would guide the way we approach the experience and help us better argue our decisions.

Bringing it all together

With design principles and our vision for Amazon's role defined we were ready to map the ideal journey the future experience would take sellers on.

Moving through the decision making funnel we defined how Amazon can fulfill each of the seller needs while addressing the barriers at every stage.

Finding solutions

From there we brainstormed solutions varying from widgets to pieces of content that would tackle specific customer issues and needs. These were then clustered together through a card sorting workshop.

The resulting information architecture was delivered to Amazon in the format of a site map. After going through rigorous rounds of feedback the team was able to gain enough buy-in from all stakeholders. The website was relaunched with the new architecture first in the UK at followed up by Italy, Spain, Germany and France in 2021.

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