Most B2B content teams measure AI ROI against draft costs. This post builds a concrete multi-touch attribution model that connects published articles to assisted pipeline at months 6, 12, and 18, and shows why the real question is whether your measurement infrastructure can capture the compounding returns at all.
AI Overviews are cutting top-ranking CTRs by up to 58%, and the standard content ROI model hasn't caught up. This post builds the exact breakeven comparison between traditional SEO articles and GEO-optimized ones for two-person B2B teams spending under $3,000 per month.
Most B2B content teams still measure publishing ROI on click-derived pipeline alone, but zero-click searches now represent 68% of Google queries. This post rebuilds the per-article economics model from scratch, showing exactly how much revenue your current measurement framework is undercounting and where the reallocation threshold actually sits.
Most B2B teams measure AI content ROI by what they saved on writing. The real budget drain is the operational layer after the draft: keyword validation, internal linking, metadata, and quality scoring. This post breaks down where per-article costs actually go and introduces a lifecycle efficiency score to benchmark your workflow against a fully automated baseline.
