In mid-2021 I joined the Facebook Ads Transparency team to continue expanding and improving the Facebook Ad Library and related transparency surfaces, including the Ad Library Report and Facebook Report Ad user experience. This team was conceived as a response to the Cambridge Analytica scandal of the 2016 US Election. Today, Meta is the leading VLOP (Very Large Online Platform, a designation from the EU) in the way of transparency over its advertising process. In 2022, the team went into overdrive in order to prepare for new regulations coming down from the EU, in the Digital Services Act (DSA). One massive change that we had to consider was the anticipated requirement to include all ads, active and archived, from all advertisers in the Ad Library. This would multiply the volume of ads in the library 100x and our current experience was not built to navigate this volume of results.
As previously stated, the need to expand the library to include all ads was on the horizon. We anticipated that this would be a requirement of the EU's Digital Services Act, and we wanted to get ahead of the curve. As lead designer on this initiative, I put together a thorough analysis of the existing product and identified opportunities to improve the experience for its future iteration.
The outcome of the first leg of this project was a presentation to the team. First, to paint a picture of where we are and where we’re going, I set context. What does the All Ads Archival entail? Why is it necessary and a priority? Then, I established a clear problem and the goals that we are focusing on with this project. Next, I brought the team up to speed on what has been do so far with the Ad Library and what we know about our users. The data points from this conversation were drawn from: the UX audit I performed; interviews with internal team members who had historical context on the project; historical and recent research provided by our UX research team; our data analyst’s end-to-end user journey with usage insights; and multiple team brainstorms and workshops we conducted on the topic.
These exercises ensured that I was taking in multiple perspectives and viewpoints – from long term and new team members, research, data, and our users. This was crucial in getting the team on board and to build a case for the changes I was to propose.
Before diving into my recommendations, I explored the risks of not pursuing this project. I looked at risks from multiple perspectives – Technical & Performance, User Experience, and Policy & Legal risks. Working in the Integrity space came with a lot of real world ramifications if we didn’t do it right, usually resulting in fines (from the US gov or other governments around the world) or even bad press that could hurt the company.
Next, I shared my findings from my comparative analysis exercise. I examined a wide variety of products from various industries. The common thread across these products was that they facilitate the browsing of large amounts of data. I looked at search tools, e-commerce, travel booking, social media, and cloud storage to name a few. I studied these products with the following questions in mind:
With the stage set, I then walked through my recommendations. I sorted these recommendations into 3 buckets: Interface, Usability, and Experience.
Interface recommendations focused on surface level changes to the UI, such as a wider, more responsive grid layout and enforcing a consistent height in the visuals of the ads (which would create a more stable, clean experience).
Usability included recommendations such as additional navigation methods and revamping the filter component in order to encourage more use of filters, based on the theory that filters will help users cut through the noise to find what they need.
Experience referred to broader, more ambiguous changes that would spin off into their own dedicated projects. This included projects like an improved Education & Onboarding experience, and a Low Bandwidth experience that would better serve users in areas with slower internet connections.
With each of the recommendations I proposed, I anchored the solution in a key user need, provided an estimate of the time required for design to complete their part of the project, and prioritized each solution based on a number of factors such as effort and the risk regarding the DSA. I also included low fidelity design mockups for each solution.
