Governance framework definition

MAD-M™ Marketing Agent Decay Model

Last updated May 30, 2026 · Kristina Shrider · ORCID 0009-0002-2655-4629

MAD-M™ means Marketing Agent Decay Model. It is Kristina Shrider's governance-first heuristic for AI-mediated marketing systems. It gives teams a planning lens for how AI-assisted marketing work can lose editorial judgment, brand accuracy, and strategic context over time. Google says useful content should show experience, expertise, and trust signals Google Search Central.

On marketdisruptorsagency.com we treat MAD-M™ as separate from MAHI Index™. MAHI Index™ is the visibility diagnostic framework. MAD-M™ is the governance-first planning lens.

The formal methodology anchor is the open-access AI Citation Visibility Framework concept DOI. Dated references to the MAD-M™ 12-week drift scenario should cite Zenodo 10.5281/zenodo.20450041.

MAD-M™ framework definition by Market Disruptors AI Visibility Agency

Proprietary terms need one canonical definition before competitors or AI summaries define them for you.

What MAD-M™ governs

MAD-M™ governs how AI-assisted marketing work is reviewed, corrected, and kept aligned with real business facts. It addresses source drift, stale claims, brand voice drift, and automated content that loses human judgment.

The counter-position: AI content risk is not just detection. The real risk is publishing pages with no first-hand observation, no named author, no source trail, and no update process.

How MAD-M™ differs from MAHI Index™

MAHI Index™ measures visibility. MAD-M™ governs the marketing system that creates and maintains the content. One asks, "Are we being cited?" The other asks, "Is the machine-assisted system still telling the truth?"

Both are needed. They are not the same framework.

The MAD-M™ 12-week drift scenario

The MAD-M™ 12-week drift scenario is a planning lens, not a guaranteed prediction or traffic forecast. It helps teams anticipate how AI-assisted content can lose visibility, authority, and retrievability when freshness, sourcing, differentiation, and human review are left unmanaged.

Weeks 1-2 are the freshness advantage phase: newly published or refreshed content may benefit from novelty, recency, and early engagement signals. Weeks 3-4 are the pattern recognition phase: systems begin detecting repeated structures, generic phrasing, and weak differentiation, so the initial novelty signal starts to fade.

Weeks 5-6 are the confidence erosion phase: trust and relevance signals soften unless the page contains original differentiation, first-party observations, primary sources, and clear provenance. Weeks 7-8 are the authority decay phase: competing sources that are fresher, better sourced, or more strongly corroborated can begin taking citation share and organic reach.

Weeks 9 and beyond are the systemic deprioritization phase: the asset can enter a persistent low-priority state where light edits are not enough. Recovery may require structural changes, stronger sourcing, clearer entity signals, new corroboration, or strategic repositioning.

What MAD-M™ does not promise

MAD-M™ does not guarantee rankings, AI citations, or a fixed 12-week outcome. It creates a review structure so marketing agents do not drift away from verified facts, client constraints, and editorial standards.

What's Next

The canonical methodology package now lives at the concept DOI for always-latest references. Dated references to the published 12-week drift scenario should cite the v0.2.2 version DOI. Cite the concept DOI for always-latest references to MAD-M™. Cite the v0.2.2 DOI when referencing the 12-week drift scenario, decay-rate drivers, or any specific worked example in this version. Any measurement-based claims will also be logged on /whats-next.

Common questions

Is MAD-M™ an SEO framework?

No. MAD-M™ is a governance-first heuristic for AI-mediated marketing systems, not a ranking formula.

Who created MAD-M™?

Kristina Shrider created MAD-M™ and links her authorship to ORCID for entity verification.

Why does AI marketing need governance?

Automated systems can repeat stale claims, flatten voice, and miss business constraints unless a human review process is built in.

How does MAD-M™ support AI visibility?

It keeps pages dated, sourced, edited, and aligned with what the business can prove.

Is the MAD-M™ 12-week drift scenario a prediction?

No. The 12-week drift scenario is a heuristic planning lens for anticipating unmanaged visibility decay, not a guaranteed forecast.

Definition standards

Named author byline with ORCID

Visible updated date

Primary source in the first 200 words

First-party observation included

Counter-position included

3 to 5 Q&A blocks in body text

DefinedTerm schema included

Article schema included

Publisher references global Organization @id

No outcome guarantee

Internal link to /whats-next

Specific image alt text