Case Study • 2023 / 2024
Shakespeare.ai AI Ad Operating System.
Designing a centralized AI-powered platform for campaign automation, optimization, recommendations, and multi-platform ad management.
Designing a centralized AI-powered platform for campaign automation, optimization, recommendations, and multi-platform ad management.
Shakespeare.ai unified campaign creation, AI optimization, recommendations, performance monitoring, and automation into a centralized operational workspace.
Businesses managing campaigns across Google and Meta struggled with fragmented analytics, disconnected workflows, repetitive optimization tasks, and operational overload.
Campaign managers constantly switched between platforms, manually adjusted budgets, monitored performance separately, and struggled to maintain visibility at scale.
The challenge wasn’t just automation. It was making AI operationally understandable.
Recommendations required transparency, confidence indicators, and predicted outcomes.
Users needed approval workflows before applying AI-generated actions.
Large campaign systems required scalable, understandable workflows.
Google + Meta integration
AI creates creatives and headlines
Users review before publishing
AI continuously improves campaigns
Recommendations included performance analysis, confidence indicators, predicted outcomes, and actionable next steps.
Users previewed generated creatives and campaign outputs before launch.
Campaign performance, analytics, budgets, and AI actions were unified into one dashboard.
Users retained control through approvals, overrides, manual edits, and AI transparency.
Shakespeare.ai transformed fragmented ad management into a centralized AI-powered operational system capable of automating optimization, simplifying workflows, and improving campaign visibility.
AI products become successful when users understand what the system is doing and why recommendations exist.
Transparency, explainability, and visibility are as important as automation capability itself.
Operational systems require balancing power, scalability, and usability without overwhelming users.
Quick answers to questions a hiring manager might still have.
I led the end-to-end UX and product design process including research, workflows, IA, wireframes, UI systems, prototyping, testing, and developer collaboration.
I collaborated closely with founders, PMs, developers, marketers, and stakeholders while owning the UX direction and design execution.
Metrics were validated through platform analytics, funnel comparison, stakeholder reviews, and workflow performance observations.
The system supported large-scale campaign management workflows across multiple advertising platforms and automation layers.
Balancing AI automation with user trust, explainability, and operational clarity without overwhelming the interface.
AI systems become far more usable when users understand why the system is making decisions, not just what it recommends.