Scalable brand safety optimization
Role
Product Design
(0→1 Concept)
Industry
AdTech
Team
Brand safety&Classification
3 PMs
Timeline
Dec 2024 - Mar 2025
Overview
ScaleMax (ABS 2.0) is a data-driven optimization platform designed to help advertisers maximize campaign reach while maintaining brand safety. ScaleMax introduces AI-assisted recommendations and scale-aware insights that help advertisers understand how their brand safety settings impact inventory availability, reach, and CPM performance.
ScaleMax is designed to help advertisers maximize reach, campaign impact, and budget efficiency by improving how ABS (Authentic Brand Suitability) settings are configured and optimized.
Discover
Through client interviews and research, we identified three major problems.
Between December 2024 and January 2025, team conducted seven client interviews with agencies and programmatic teams, including Directors of Media Operations, Programmatic Managers, Analysts, and Investment Strategy leaders from companies such as Best Buy, GM, Lowe’s, Southwest Airlines, Kroger Precision Marketing, Klick Health, and Spark Foundry. The interviews revealed a key challenge: while advertisers rely on brand suitability settings to protect their brands.
Lack of visibility into why inventory is blocked
"
If the platform could automatically flag domains with incident rates, it would save us a lot of manual work.
Difficulty balancing brand safety with campaign performance
"
We need to protect the brand, but we also need visibility into how those restrictions affect the scale.
Event-driven adjustments
"
Most adjustments happen after major events. We respond quickly, but it’s often reactive.
Need for proactive alerts
"
If the system could alert us to potential risks like Google Alerts, it would help us stay ahead.
Users need better visibility into how brand safety settings impact campaign scale, delivery, and performance
Solution Direction
Designing for transparent and scalable brand suitability optimization
Based on client interviews with agencies and advertisers, we identified three core challenges: advertisers lacked visibility into how brand safety settings affected campaign scale, teams often applied overly restrictive configurations that unintentionally limited reach, and optimization relied heavily on manual troubleshooting rather than actionable insights.
To address these issues, we focused on three solution directions: providing transparent visibility into the scale impact of suitability settings, introducing intelligent optimization recommendations to unlock safe inventory, and enabling proactive campaign optimization through AI-assisted insights and performance signals.
Sketch
Exploring actionable flows for scale optimization and guided setup for brand Safety configuration
Early sketches explored two key action points in the workflow: a guided setup to help users configure brand safety profiles with awareness of scale impact, and a scale optimizer that surfaces recommendations to adjust restrictive settings. Together, these flows help advertisers understand the impact of their configurations and quickly take action to improve campaign scale and performance.
Final Design
Vision Workflow
Scale Optimizer: AI-driven recommendations to safely unlock additional inventory through conversational exploration
The Scale Optimizer surfaces AI-generated recommendations that help advertisers identify and remove overly restrictive settings. Each recommendation clearly communicates its expected impact on key metrics such as scale, block rate, and CPM.
Users can review and validate these recommendations directly within a conversational interface, ask follow-up questions, and explore projected outcomes before taking action. This enables a more transparent and informed decision-making process, allowing users to confidently optimize campaign performance while maintaining brand safety.
Guided Setup: Understand how configuration choices impact performance during setup
The guided setup helps advertisers configure brand suitability profiles with clear visibility into how each decision affects campaign performance. Instead of navigating complex settings in isolation, users are presented with key metrics—such as avoidance rate, suitability rate, and profile restrictiveness—alongside AI-driven recommendations.
By connecting configuration choices directly to their projected impact on scale and delivery, users can make informed decisions from the start. This reduces trial-and-error and ensures campaigns are set up with an optimal balance between brand safety and reach.
Achievement & Takeaway
Translated complex client needs into a clear product direction through continuous alignment with PMs
Led an initiative project translating client interview insights into a focused solution for brand safety optimization. Through ongoing synthesis and twice-weekly check-ins with PMs, I iterated on concepts and refined the direction to ensure alignment with both user needs and business goals. The final concept was presented at an all-hands, gained stakeholder alignment, and was approved for integration into the live product.
This process reinforced the importance of collaboration and iterative alignment in shaping actionable solutions, especially when working with ambiguous problem spaces.
Next work
