Why Your B2B PPC Metrics May Be Lying to You
Search Engine Land on B2B paid-search (PPC) measurement — the paid leg of search-marketing. Thesis: marketers optimize toward vanity metrics; “more conversions and higher ROAS don’t always translate to more pipeline or revenue.”
Problems
- Quadruple-counting — all conversion actions set as primary inflates totals across funnel stages.
- False ROAS — adding conversion values to multiple actions masks real incremental gain.
- Average vs marginal CPA — average CPA hides the true cost of the next conversion at higher spend.
Fixes
- Relative conversion values (e.g. MQL worth 1000× a video view) to steer the bidding algorithm.
- Campaign-specific down-funnel goals; measure marginal CPA + incremental revenue; marketing-mix modeling / incrementality testing.
Why it’s here
Paid-search measurement, the counterpart to organic seo-commissioning-workflow and seo-affiliate-alignment in search-marketing. Its incrementality problem (you can’t see the true marginal effect) is the paid-side cousin of the AI-search opacity problem (google-io-business-visibility) — measurement is the cross-cutting hard part on both the traditional and AI sides. (AI minimal here — only bidding algorithms.) Audience: B2B PPC managers.
The automation stress-test
groas is this page’s problem in sharpest form: an autonomous AI optimizer sold on maximizing ROAS and conversions — the exact metrics flagged here as potentially “lying.” Handing bidding to a model trained to maximize reported ROAS scales whatever that metric mis-counts (quadruple-counted conversions, false ROAS) faster than a human would. The fixes above (relative conversion values, marginal-CPA/incrementality goals) become the guardrails you’d have to set before trusting any autonomous bidder.
Related
search-marketing · groas · seo-commissioning-workflow · seo-affiliate-alignment · google-io-business-visibility