Performance analytics for content teams: The Content Technologist Measurement Model
How to measure your content's performance, regardless of the business model
industry standards
72 posts from industry standards
A guide to content analytics: Why content professionals should care about their metrics
ke it or not, it's up to us, the people who enjoy making things, to advocate for what we value and to value what we create. We must, on a base level, understand our numbers.
Making impressions a thing of the past: Grounding your content performance data in reality
Everyone else's numbers are inflated, but your own data is your gold. Learn to trust your owned data and make decisions with verifiable performance metrics.
Should I let Perplexity crawl my content? Pitting legacy media intellectual property standards against AI discoverability
Should I, as a website publisher, be angry that an AI summary engine includes my content in its index? Or should I not be so precious about my intellectual property? Here's how I'm making that data-driven decision.
What is content distribution? Navigating the necessary evils of algorithms
Instead of trucks and newsstands, in 2024 we have web- and social network-based aggregator systems that pipe content directly to consumers via software. Navigating algorithmic distribution is a necessary challenge. Here are some tips.
From engineered content to informed editorial: Blazing new trails in digital publishing
With data science and algorithms being panned into binary, good-versus-bad narratives, where can we find clarity and room to experiment?
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