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Redesigning the Search experience

Intelligence is an AI-powered product developed to empower procurement and supply chain experts in making effective decisions when selecting suppliers. The tool makes it easy to find, compare, evaluate suppliers, gain insights, get an advantage in negotiations and make better strategic decisions. All supplier information such as financial, economic, certifications, diversity, sustainability, is consolidated in one place. 

In this case study: cross-functional workshops, problem definition, ideation, validating UX concepts in usability testing sessions, synthesising insights 

My role

Senior Product Designer


August 2022 - February 2023

The Problem

The team and I used the continuous product discovery framework to uncovered new insights and opportunities. One of such usability tests showed that the search experience was causing confusion. Search is the cenral part of the experience. It allows users to discover suppliers based on their location, certifications, EDG data and the products they make. In tests users expressed frustration around what search terms to use, how to filter and how to understand search results. 

The Goal

Redesign and improve the search experience:

  • create a simpple and intuitive search experience, 

  • tailor the filtering functionality to the varying needs of customers,

  • find a way to show results in a way that brings most value.


My Approach

To make sure we focused on the right problems, I conducted cross-functional workshops with key stakeholders, including the product manager, designers, developers, engineers, and data teams. This helped foster a common understanding of the problem space and brought focus into the ideation sessions. Next, I created a UX concept and ran usability testing sessions to validate it. Based on the learnings, I prioritised recommendations and the product manager added them to the roadmap. After implementation, we ran additional testing sessions, making sure the improved experience met user expectations.

Step 1: Problem definition

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Before jumping into prototyping or design, it’s crucial to understand what problem we are trying to solve. To make sure the problem was clear:

  • I synced with the Product Manager about how the redesign should bring value to the user and the business,

  • synced with the engineering team to understand what technology powered search at the moment and how it could be changed.

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Step 2: Research 

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Since this was not the first iteration on improving search, I needed to understand everything about the current implementation and how it got there, so the desk research included:

  • previous usability testing sessions,

  • user research, such as personas, user journeys, 

  • notes from previous brainstorming and ideation sessions, 

  • heuristic evaluations of the product, 

  • competitor analysis and benchmarking.

Portfolio & CV - Search Step 2 Illustration.jpg

Step 3: Synthesis

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I grouped all insights from the previous steps and arranged them into affinity groups: searching, filtering and sorting, search results. Then I framed How Might We…? questions. 

Portfolio & CV - Search Step 3 Illustration 1.jpg
Cargo Ship at Sea

Step 4: Cross-functional workshop with product team 

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It was time to bring the whole team in: product manager, designers, developers, engineering, data. The goal of the workshop was to kick off the discussion, foster a common understanding of the problem space, make sure we’re solving the right problems, and ideate potential solutions

During the workshop I introduced the problems and potential solutions, gave time for reflection on each topic, and facilitated the discussion.

Portfolio & CV - Search Step 4 Illustration.jpg

Step 5: Solutions and Prioritization

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After the workshop, together with the Product Manager and the engineers, I prioritized the potential solutions by confidence: solutions we're highly confident in, assumptions we’d test again, and deprioritized solutions. 

Portfolio & CV - Search Step 5 Illustration.jpg

Step 6: Usability Testing

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I ran around 7 usability test sessions, which consisted of two parts:

  • testing the existing solution on the live product, 

  • testing the future vision of the search experience using a Figma prototype. 

The script for the sessions included: 

  • the area being tested, 

  • testing goal or assumption, 

  • respective task/prompt or question.

Portfolio & CV - Search Step 6 Illustration.jpg

Step 7: Insights synthesis & prioritization

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In the 7 moderated sessions I would either facilitate or take notes. The notes that I took on post-its were colored based on sentiment, i.e.:

  • red (if it was a negative comment or a failed task), 

  • green (if the comment was positive or the task was easy) and 

  • amber (neutral comment or task completion with some setbacks).

After the sessions, I marked all the post-its with the participant’s tag (e.g. User 1, User 2). This way, I can still trace the response back to its author if necessary, but the absence of specific names helps avoid bias.

To get a feeling for the trend, I arranged the feedback into logical groups by sentiment, e.g. three or more similar responses with similar sentiment constitute a group.


For each group I came up with recommendations

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My approach to solving the problem involved running workshops with the product team and conducting usability testing with customers to help inform design decisions. By involving multiple stakeholders early in the process, focusing on the right problem and continuously validating ideas, I was able to create a solution that met the business needs and was user-centric at the same time. 

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