
I explain why proprietary first-party data can become a powerful AI citation asset, and why structure determines whether search and AI systems can actually extract and cite it.

I used Google Ads predefined audiences as a targeting filter to reduce invalid clicks by 50% after standard click-fraud defenses failed.

I remember Bruce Clay through our final conversations about SEO, AI, content structure, and the enduring craft behind ranking well.

I explain how Google Ads campaign structure affects Smart Bidding, Performance Max, conversion signals, budget allocation, and long-term PPC performance.

I break down how ChatGPT Thinking mode changes brand citations, with only 25.6% source overlap between minimal and high reasoning across 100 prompts and 20 buyer journeys, according to Semrush and Kevin Indig.

Google Search now sends users directly to publisher-hosted AMP pages instead of cached AMP viewer pages, while rankings remain unchanged and AMPhtml support continues.

I’m seeing Google’s new Channel Diagnostics for Performance Max give advertisers a clearer way to find missing or disapproved assets that may limit campaign delivery.

I can now add previous time period comparisons in Google Trends, making it easier to spot seasonal shifts, momentum, and useful search interest patterns.

I explain how GraphRAG shifts AI search from isolated text chunks to connected entity knowledge, and why that changes how brands should approach AI SEO, structured data, attribution, and visibility.