Brand Lift Report

Overview

I was working on the Lift team within Measurement under the Ads org at Facebook. I led the design effort in redesigning the Brand Lift report, working closely with PM, UX Research, and a Content Strategist. In parallel, I collaborated with a peer designer to develop a unified lift reporting framework extensible across measurement tools.

Brand Lift is one of the measurement solutions Facebook offers. We randomize a target audience into test and control groups, serve ads only to the test group, then poll both groups in News Feed with questions about the brand. By comparing favorable response rates between the two groups, we can measure whether the ads produced a lift.

At the time, only advertisers with a sufficient budget had access to account teams to help set up tests and interpret results. The existing Brand Lift reports were difficult to use independently — lacking metric clarity, a clear narrative, and actionable guidance. In order to empower more advertisers with Lift and enable self-serve access, we needed to redesign the report from the ground up.

Project goals:

• A new reporting experience that guides advertisers to interpret results correctly and make more informed business decisions.
• A new reporting framework that unifies Brand Lift and Conversion Lift, extensible to support Split Testing, Offline Sales, and other measurement tools.

My Role & Process

I started by auditing the existing report UI, compiling prior research findings, PMM inbound feedback, and evaluating the interface against design principles. Key problems identified: lack of a true summary page, content competing for attention, metrics that advertisers couldn't interpret without expert help, and natural language statements that conflated concepts.

To answer what report narrative makes sense and what helps ease understanding and promotes actionability, we conducted research with 10 advertisers and advertising agencies in London using participatory design. Participants were given cards — each with a description of information and a visual example — and asked to assemble their ideal report. I led the card design and worked closely with UX Research on planning and conducting the sessions.

Key learnings from participatory design:

• Ideal narrative: recap of test setup → results → recommendations
• Advertisers want more actionable data cuts tied to their business goals
• Reports should include more visual, collapsible, and downloadable content for internal share-outs

In parallel, a peer designer was working on the Conversion Lift report — which would be unified on the same platform. We ran a design sprint with cross-functional partners to establish a shared reporting framework, then built prototypes for each use case to validate it.

Working with UX Research, we tested the prototype with 16 advertisers and agencies across New York City and Chicago to evaluate whether the prototype achieved its goals.

Key findings from prototype testing:

• The Answer Page needed to contain all data necessary for determining overall campaign success
• Reports needed to communicate in advertisers' language, not measurement jargon
• Plain-language metric explanations and confidence level guidance were essential
• Facebook needed to take a clear stance on measurement definitions

A lot of the problems uncovered in research were about content. I worked in close collaboration with a Content Strategist to revise metric definitions, natural language statements, and test terminology. After content was finalized, I spec'd out the full design and worked with engineers on requirements and edge cases — including localization for long strings and right-to-left languages.

Results & Impact

The report was built and shipped together with the self-serve Brand Lift solution, making Lift accessible to a much broader set of advertisers for the first time. The project contributed to measured spend — our top-line metric — though I did not get to see the detailed analysis.

Learnings

• Content and design need to work together to tell a cohesive story. The most impactful improvements in this project came from revising language, not visual design.
• Communicating complex statistical concepts in plain terms — without introducing misunderstandings — is genuinely hard and requires close collaboration with content and research.
• Learned different research methodologies (participatory design, prototype testing) and how to partner effectively with UX Research across both.

Next Steps

The self-serve launch was the foundation. The natural next step is closing the feedback loop — giving advertisers clearer guidance on how to act on results across different confidence scenarios (low, medium, high), and surfacing recommendations that tie directly to their campaign objectives. Longer term, the unified reporting framework creates an opportunity to give advertisers a single, consistent view across all measurement solutions: Brand Lift, Conversion Lift, and Split Testing together.