Methodology Registry

Operator Frameworks

A registry of the named diagnostic frameworks used across this site. Each framework identifies a recurring pattern in paid media performance that benchmark comparisons alone cannot surface.

Sourced data

Benchmark numbers drawn from published reports: WordStream/LocaliQ, platform documentation (Meta, Google, LinkedIn), IAB standards, and publicly available industry studies. Cited inline on each page.

Derived interpretation

Frameworks and diagnostic logic derived from sourced data combined with structural analysis of how paid media attribution and auction mechanics work. These are models, not measurements.

Operator observation

Pattern recognition drawn from 10+ years of AdTech and programmatic practice across agency and brand accounts. Not statistically representative. Used for pattern naming and diagnostic framing, not benchmark ranges.

Named Frameworks — v72, June 2026
False Efficiency Trap
Demand · Attribution
ROAS improves. Growth slows. The metric and the business outcome move in opposite directions.
Problem it identifies
An account concentrates spend on high-probability conversions — branded search, warm retargeting, existing customers — producing excellent reported ROAS while generating zero incremental demand. The dashboard signals success while the customer pipeline contracts.
When to apply it
ROAS is at or above target. New customer acquisition rate is flat or declining. Conversion volume holds up only because retargeting and branded search sustain the aggregate.
Primary reference
What Is a Good ROAS?
Why Your ROAS Dropped
What Is a Good CPA?
Diagnosis: A ROAS above target is not evidence of efficiency. It is only evidence of margin survival — and sometimes, not even that.
CPM Quality Illusion
Media Cost · Audience
Media costs fall. Conversion quality falls faster. The two move in opposite directions, and the dashboard only shows one of them.
Problem it identifies
Lower CPM is treated as improved efficiency. The actual mechanism is that cheaper inventory delivers lower viewability, lower ICP match rate, and lower purchase intent. The media becomes cheaper. The attention becomes less valuable.
When to apply it
Average CPM is falling while CPA is rising, or lead quality metrics are deteriorating. Teams expanding into open-exchange programmatic or broader placements are most exposed.
Primary reference
Average CPM by Platform
Diagnosis: CPM measures the price of attention. It does not measure the price of the right attention.
Demand Harvesting Plateau
Scale · Audience Saturation
ROAS stabilizes at a high level. Conversion volume stops growing. The account has reached the limit of the demand it can efficiently harvest.
Problem it identifies
A mature account captures existing demand efficiently — branded search, retargeting, known audiences — but this pool is finite. Incremental budget produces diminishing returns. Growth requires demand creation, not demand capture.
When to apply it
Budget scaling produces declining ROAS without changes in creative or CVR. Impression Share Lost to Budget is near zero. Average CPC is rising as the account moves into lower-intent inventory.
Primary reference
Why Your ROAS Dropped
Diagnosis: When ROAS declines without a change in creative or conversion rate, the question is not what deteriorated — it is what ran out.
Platform CPA vs Real CAC Gap
Attribution · Measurement
Platform CPA falls. Blended acquisition cost rises. The platform measures what it can observe. The business pays for everything it cannot.
Problem it identifies
Each platform attributes conversions using its own model. A buyer touched by three channels appears as three attributed conversions. The aggregate platform CPA is structurally lower than real CAC. Budget decisions made on platform CPA systematically under-price acquisition cost.
When to apply it
Running three or more paid channels simultaneously. Platform-reported blended CPA looks healthy but backend revenue growth is not matching spend growth. Cutting a channel causes unexplained performance drops in other channels.
Primary reference
What Is a Good CPA?
Diagnosis: CPA measures the cost of a transaction. It does not measure the cost of a customer.
Audience Temperature Model
Funnel · Intent
Audiences differ not just by demographics but by proximity to purchase. CPM, CTR, and CVR benchmarks are only meaningful when the audience temperature is held constant.
Problem it identifies
Benchmark comparisons between channels, campaigns, or time periods conflate audiences at different funnel stages. A cold prospecting campaign compared against a warm retargeting campaign using the same ROAS or CPA benchmark is not a valid comparison.
When to apply it
Cross-channel performance comparisons. Campaign audits where one channel appears dramatically more or less efficient than another. ROAS or CPA targets set without segmenting new vs returning customers.
Primary reference
Average CPM by Platform
What Is a Good ROAS?
Diagnosis: The benchmark is not wrong. The comparison is wrong. Audience temperature determines what any given metric means.
Attribution Distortion Layer
Attribution · Measurement
Every attribution model is a simplification. The distortion it introduces is not random — it systematically favors certain channels, certain campaign types, and certain time windows.
Problem it identifies
Last-click attribution over-credits conversion-stage campaigns and under-credits awareness and consideration channels. View-through attribution inflates social channel performance. Cross-platform overlap produces conversion double-counting. The distortion accumulates with each additional channel.
When to apply it
Evaluating multi-channel media mix. Comparing platform-reported ROAS to backend revenue. Diagnosing why cutting a supposedly inefficient channel causes performance drops elsewhere.
Primary reference
What Is a Good CPA?
Why Your ROAS Dropped
Diagnosis: Attribution does not reveal what worked. It reveals what the measurement model was designed to credit.
Benchmark data — source classification

Benchmark numbers used across this site fall into three categories. This table clarifies which claims are directly sourced, which are derived from sourced data, and which reflect operator interpretation.

Metric / claim type Primary sources Classification
Google Ads CPC, CPA, CTR ranges WordStream / LocaliQ 2025–2026 benchmark reports Sourced
Meta CPM, CTR ranges Meta Ads Manager documentation; WordStream industry breakdowns Sourced
LinkedIn CPC, CPM ranges LinkedIn Marketing Solutions documentation; B2B benchmark studies Sourced
Break-even ROAS formula (1 ÷ gross margin) Standard margin accounting; derived from cost structure logic Derived
Cost-per-qualified-impression methodology Derived from ICP match rate × CPM; no standard published source Derived
Platform CPA vs Real CAC gap magnitude (1.5–3×) Practitioner observation across multi-channel accounts; directionally consistent with published attribution studies Operator observation
Named framework patterns (False Efficiency Trap, etc.) Pattern recognition from AdTech practice; not statistically measured Operator observation
Update log
VersionDateChange
v72 June 2026 Operator case studies added to four flagship pages. This registry page created.
v71 May 2026 Operator Pattern callouts standardized across flagship pages. Visual distinction introduced: Named Framework (orange border) vs Operator Pattern (black border, grey background).
v70 May 2026 Homepage repositioned around interpretation hierarchy. Primary CTA updated.
v68 April 2026 average-cpm-by-platform fully rewritten around CPM Quality Illusion thesis.
v64 March 2026 what-is-a-good-roas and why-your-roas-dropped rewritten with Named Frameworks.