Author: Ava Patterson
Ava Patterson
Ava is a San Francisco-based marketing tech writer with a decade of hands-on experience covering the latest in martech, automation, and AI-powered strategies for global brands. She previously led content at a SaaS startup and holds a degree in Computer Science from UCLA. When she's not writing about the latest AI trends and platforms, she's obsessed about automating her own life. She collects vintage tech gadgets and starts every morning with cold brew and three browser windows open.
Why brands must build approval workflows and content provenance controls before scaling AI marketing automation, not after.
GA4, Adobe, and Amplitude handle AI-referred traffic differently — here’s which platform actually attributes generative search revenue correctly.
Stale role, company, and device data quietly wrecks AI targeting. Here’s how to set data freshness metrics that keep signals decision-grade.
AI adoption in marketing has nearly doubled, but trust in output quality is flat. Here’s the root-cause diagnostic behind the gap.
Unified revenue data layers built on knowledge graphs are what make autonomous AI marketing agents trustworthy instead of dangerous.
A practical scorecard for auditing identity resolution and CDP vendors before renewal, so match-rate claims survive real scrutiny.
Autonomous AI agents fail without a shared data contract standard across CRM, MAP, and analytics — here’s how to build one before scaling.
Set up the GA4 AI Assistant Referrer Report correctly, so ChatGPT and Gemini traffic stops hiding inside your organic search numbers.
HaloIndex maps sales back to AI search citations, giving brands a way to prove ROI from zero-click discovery.
Zig.ai bets that embedded engineers, not more software, will finally fix B2B revenue data fragmentation. Here’s what brands should verify first.