2022/2023
In April 2022, I was working at Sellics when it was acquired by the Ascential Group. The team merged with their existing advertising product called Perpetua, and the Sellics tool was discontinued.
Prior to the merger, the Perpetua business team had noticed that large clients were migrating to other tools that provided competitive intelligence using estimated sales of products on Amazon. As a result, part of the Sellics team was tasked with developing a solution to address this market need.
As the designer responsible for this new project, I started working with the product manager and the general manager to research the current tools in the market and map their value proposition, offers, strengths, and weaknesses.
We identified three main tools:
Market research main takeaways:
In parallel to the market research, we interviewed 15 people from different backgrounds, such as sellers, agencies, and aggregators who were using or have used similar tools. The goal was to understand their current workflow, needs, and pain points. At this step of the process, we wanted to collect as much information as possible so we had open conversations where the main goal was to discover:
Main discovered use cases:
To define which exact problems to be tackled, we decided to focus on agencies since they were already the biggest user base from Perpetua. Inside the agencies, our main actors were the data strategists and account managers.
User interview main takeaways:
Agencies had to rely only on their client's historical data to come up with a strategy to grow their revenue on Amazon. With many transformations and the marketplace becoming more aggressive over the years, players need market data to project more realistic scenarios and understand external factors that are impacting their performance.
Prism is a market intelligence tool that uses estimated sales data from products on Amazon to model consumer trends in the marketplace. It allows advertisers to define market segments and track their share so they see a more realistic scenario to find opportunities to grow, discover who they are directly competing against, and the seasonality factors that impact advertising performance. This tool allows agencies to have discussions with their clients using data as a reference point.
Based on the collected information, we prototyped the version of the ideal product with some of our main ideas. Instead of wireframes, I used the existing Perpetua design system in the prototype because it contained solid components. Nonetheless, I didn’t spend too much time refining screens and using the exact same patterns.
We went back to some of the agencies we interviewed and pitched them three versions to discover which ideas resonated more with them. We also presented the project to the tech team to review feasibility. Based on the feedback we kept the most valuable features, adjusted what was necessary, and prioritized how we could release the product in phases.
Based on the user feedback and technical feasibility we split the releases based on features:
MVP - Closed Beta (October 2022)
The first thing we wanted to validate was the quality of the data. As the first release for the closed beta, we launched Explorer, which gave access to users to compare their brands with the estimates and then analyze competitor brands.
Version 2 - Closed Beta
We allowed users to use the main filters to create markets and save the reporting.
Version 3 - Open Beta (February 2023)
Improved the filters to create markets and reporting by adding more types of data visualization.
Version 4 - General Availability (March 2023)
We allowed users to dig deeper on the product level so they could see how specific products were performing and which keywords they were ranking for. We combined this data with the advertising data of the user to show which keywords they were already bidding on and which were not. They could then bid more aggressively if they want to outrank a certain competitor.
After release, we could gather real usage data to validate how the tool was being used and talk to users.