Marketing Compass

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---
name: articulate-marketing-problem
description: "Turn scattered marketing or business symptoms, metrics, stakeholder statements, disagreements, and vague concerns into an evidence-bounded, testable problem definition before structural diagnosis or solution design. Use when a user says the issue is unclear, teams describe different problems, observations exist only as disconnected points, a request already jumps to ads/CRM/MA/reorganization, metrics conflict, definitions may have changed, or source data and interviews must be gathered to create an analysis-ready brief. Separate facts, measurements, interpretations, emotions, hypotheses, requests, and proposed solutions; connect points without inventing causality; identify competing explanations; and specify or perform the minimum evidence acquisition that can change the decision."
---

# Articulate Marketing Problem

Create the problem before solving it. Convert fragmented reality into an analysis-ready brief without polishing assumptions into facts or declaring a single root cause prematurely.

Read [references/problem-formation.md](references/problem-formation.md) for every substantive problem-definition task. Read [references/evidence-acquisition.md](references/evidence-acquisition.md) when files, systems, interviews, definitions, or additional data must be inspected or requested. Read [references/output-contract.md](references/output-contract.md) before returning a full brief.

## Establish the decision context

Identify:

- Who must decide what, and by when
- What triggered the concern
- What outcome, customer state, or operating condition is at risk
- What action is already being proposed, by whom, and on what premise
- What evidence is available now and what access is actually authorized

Ask at most three initial questions that materially change the scope or evidence plan. If answers are unavailable, continue with a provisional problem statement and label its limits.

Do not accept the requested solution as the problem. Translate “increase advertising,” “replace CRM,” “sales must follow up,” or “we need more people” into the condition those actions are intended to change.

## Phase A — Collect and classify the points

Extract atomic statements from conversation, documents, dashboards, spreadsheets, meeting notes, interviews, and system exports. Preserve source and wording when material.

Classify every consequential point as one of:

- Confirmed event or directly observed fact
- Measurement, including definition, denominator, population, period, and source
- Stakeholder report or lived observation
- Interpretation or causal story
- Emotion, concern, incentive, or desired outcome
- Hypothesis
- Unknown
- Proposed action or solution

Do not collapse stakeholder reports into system facts. Do not treat a logged value as self-explanatory truth; the value can be real while its definition, population, or comparison is unsuitable.

## Phase B — Connect points into candidate structures

Connect points only through an explicit relationship:

- Same population or cohort
- Temporal sequence
- Stage or process dependency
- Shared constraint or common cause
- Feedback loop or delay
- Contradiction or definition mismatch
- Stakeholder perspectives on the same event

Mark each connection as `confirmed`, `supported`, `plausible`, or `unknown`. Never join different cohorts, periods, definitions, or attribution systems silently.

Generate at least two competing explanations when the decision is consequential. State what observation would distinguish them. If the points cannot yet support a structure, say so and produce an evidence-acquisition plan instead of a polished narrative.

## Phase C — Form the problem statement

Write the narrowest useful problem definition that states:

1. Scope: population, process, market, cohort, and period
2. Observed condition or change
3. Why it matters to the pending decision
4. Candidate mechanism, explicitly labeled by evidence status
5. Material co

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---
name: assess-ma-crm-ltv
description: "Assess whether marketing automation, CRM, lifecycle messaging, customer success, retention programs, or LTV initiatives fit the business and what must be fixed first. Use when a user asks whether to introduce or strengthen MA, why CRM is not increasing revenue, how to separate strategic CRM, operational CRM, MA, and CS, why retention or renewal is weak, how to improve LTV, how to design lifecycle journeys or automation, or how to distinguish accounting LTV, acquisition economics, and the strategic lifetime of customer choice."
---

# Assess MA, CRM, and LTV

Diagnose the relationship and value structure before automating contact. Treat MA as an execution device, CRM as both a relationship strategy and an operating function, CS as value-realization intervention, and LTV as both an accounting result and a strategic formation problem.

Read [references/role-and-readiness.md](references/role-and-readiness.md) for every substantive diagnosis. Read [references/ltv-model.md](references/ltv-model.md) when calculating or diagnosing LTV. Read [references/output-contract.md](references/output-contract.md) before returning a complete recommendation.

## Establish the decision

Identify:

- Who must decide what and by when
- The business model, buying cycle, and repeat or continuation mechanism
- The customer population and cohort in scope
- The current customer state and observed problem
- The proposed MA, CRM, CS, or retention intervention
- Available behavioral, transactional, attitudinal, and service data
- Capacity, permission, customer risk, and acceptable loss

If the request begins with a tool or campaign, restate the underlying decision. Ask at most three questions that can change the readiness decision, then continue provisionally when possible.

## Test critical prerequisites

Check the three major blockers before using a scorecard:

1. Does relevant base or recognized demand exist?
2. Is the ICP or target customer state defined?
3. Does the customer reach and experience the promised value?

If any major blocker is absent, default to `Hold` or `Adverse` for additional automation. Do not let a majority of weaker positive conditions overrule a structural failure.

Then assess:

- Demand repeats or a meaningful future decision recurs
- A reason to choose already exists
- Timing or friction can change the outcome
- Customer states can be observed or responsibly inferred
- Contact permission and channel suitability exist
- The organization can act on signals
- Human intervention is available where ambiguity is high

Treat any `3/5` or `2/5` rule as a rough prompt, not a formal threshold.

## Separate responsibilities

Use these roles:

- **Strategic CRM:** design customer states, relationship meaning, value timing, contact logic, and LTV structure.
- **Operational CRM:** prevent leakage, restore recall, support return, adjust timing, and reduce selection friction.
- **MA:** automate contact, routing, timing, reminders, and known friction.
- **CS:** help customers reach value, succeed, adapt, and form a reason to continue.

Do not reduce CRM to message delivery, CS to support tickets, or MA to a revenue engine. MA does not create base demand, ICP, product value, or competitive advantage.

## Map the customer-state system

Use the smallest relevant path:

```text
Need recurrence
  → recall or return trigger
  → re-selection
  → access and friction
  → use and value realization
  → continuation, repurchase, expansion, or advocacy
```

For subscription or SaaS, include acquisition, activation, first value, habit, renewal, expansion, and recovery where relevant.

For each state, separate:

- Confirmed facts
- Proxy signals
- Hypotheses
- Unknowns
- Customer risk
- Appropriate automated and human response

Select one primary bottleneck. Do not launch a full lifecycle program to solve every stage simultaneously.

## Diagnose value realization and expectation

Check:

- What value the customer expect

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---
name: audit-marketing-reasoning
description: Audit marketing proposals, analyses, reports, dashboards, case studies, and frameworks for causal validity, evidence quality, reproducibility, context transfer, information freshness, ethical risk, and real-world implementability. Use when evaluating whether correlation supports causation, whether a successful case generalizes, whether metrics or models justify a decision, why a theoretically sound proposal may fail in practice, or how to rewrite a marketing claim into a falsifiable and operational form. Route measurement-system design and metric calculations primarily to design-marketing-measurement; route broad growth diagnosis primarily to diagnose-marketing-structure.
---

# Marketing Reasoning Audit

Audit consequential claims without turning the review into fault-finding. Preserve the useful core, expose uncertainty, and convert criticism into a safer decision or a small validation step.

## Operating principles

- Treat frameworks as subordinate to observed reality.
- Separate business outcomes from the proposed marketing mechanism.
- Distinguish fact, interpretation, hypothesis, unknown, and recommendation.
- Do not convert correlation, model output, or a successful case into causation by wording alone.
- Treat missing information as a reason to condition a decision, not automatically to stop it.
- Describe incentive, political, or operational risks as hypotheses unless directly evidenced.
- Protect customer trust; weak signals do not create strong permission to sell.
- Date unstable assumptions and verify current facts when the decision depends on them.

## Workflow

### 1. Define the audit object

Identify:

- the decision the material is meant to support;
- the material claims that could change that decision;
- the population, market, channel, product, period, and organization in scope;
- the cost of being wrong and the reversibility of the action.

If scope is unclear, state a provisional scope and ask only for information that could materially change the verdict.

### 2. Build a claim map

For each material claim, trace:

`evidence -> inference -> conclusion -> proposed action`

Label every element as fact, interpretation, hypothesis, unknown, or recommendation. Flag any skipped link, undefined term, proxy presented as an outcome, or meaning formula presented as a calculation formula.

Read [reasoning-audit.md](references/reasoning-audit.md) when auditing a report, case study, model, or causal claim in detail.

### 3. Audit evidence and causality

Check at minimum:

- denominator, distribution, comparison group, and time window;
- time order and a credible counterfactual;
- common causes, reverse causality, selection bias, and survivorship bias;
- measurement error, aggregation, collinearity, seasonality, and repeated testing;
- whether the evidence measures behavior, attitude, recall, revenue, or only a proxy;
- whether alternative explanations remain plausible.

Use four evidence levels:

- **A — causal:** credible experiment or strong quasi-experimental design.
- **B — triangulated:** multiple independent methods support the same direction.
- **C — observational:** association or model estimate with unresolved alternatives.
- **D — hypothesis:** expert judgment, anecdote, analogy, or untested mechanism.

Do not treat MMM as automatic causal proof. Use it primarily for hypotheses, anomaly detection, model and data audit, broad ranges, and directional risk. Pair it with experiments, Geo tests, surveys, or other evidence when the decision needs incrementality.

### 4. Audit transfer and reproducibility

Test whether the reasoning survives changes in:

- customer and buying situation;
- product category and price;
- competitive structure and distribution;
- channel, creative, and timing;
- operating capacity, incentives, and approval process.

Look for failed, neutral, and excluded cases—not only winners. A single high-CTR campaign, viral post, or successful company 

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---
name: design-btob-growth
description: "Diagnose and design B2B growth across ICP and demand triggers, contact and recall, first meetings, problem resolution, comparison, buying committees, internal approval, procurement, implementation, value realization, and continuing relationships. Use when a user asks why B2B leads, meetings, opportunities, proposals, or wins are not growing; how to improve discovery or first sales meetings; why deals stall; how to follow up content downloads; how to create ROI, comparison, approval, or internal-selling materials; or how to separate automation from human intervention."
---

# Design B2B Growth

Treat B2B growth as a multi-person decision and implementation system, not a lead-volume funnel. Diagnose how the customer's organization decides, explains, funds, approves, adopts, and realizes value.

Read [references/btob-structure.md](references/btob-structure.md) for every substantive diagnosis. Read [references/meeting-and-deal-design.md](references/meeting-and-deal-design.md) when designing meetings, reviving stalled deals, or creating internal-selling assets. Read [references/output-contract.md](references/output-contract.md) before returning a complete design.

## Establish the commercial decision

Identify:

- Who on the seller side must decide what and by when
- The product, contract form, sales cycle, and implementation burden
- The target account and excluded account conditions
- The customer's need event or decision trigger
- The current stage and observed stop point
- The acceptable acquisition cost, sales capacity, and delivery capacity
- What evidence exists beyond lead or activity counts

If the target account, need trigger, or value realization is undefined, do not begin by scripting outreach or automating nurture. Ask at most three questions that can change the diagnosis, then continue provisionally if possible.

## Map the B2B decision system

Use:

```text
Demand-bearing account / ICP
  → contact and recall
  → problem resolution, comparison, and sales value
  → internal approval and consensus
  → procurement and implementation
  → value realization
  → continuing relationship
```

For each stage, separate:

- Confirmed facts
- Seller interpretation
- Buyer-side hypothesis
- Unknowns
- Observable signal and missing evidence

Select one primary bottleneck. Do not treat all stages as equal priorities.

## Define ICP and demand trigger

Specify ICP through conditions that affect value and buying ability:

- Problem and use case
- Need event or change trigger
- Operating scale and economic impact
- Current workaround and dissatisfaction
- Decision authority and budget path
- Implementation readiness and constraints
- Timing and urgency
- Exclusion conditions

Do not define ICP only by industry, company size, or job title. Distinguish an account that fits the product from an account that is ready to decide now.

## Map the buying committee

Identify roles rather than assuming one buyer:

- Problem owner
- User or operator
- Champion
- Economic buyer
- Technical, legal, security, procurement, or finance reviewer
- Executive sponsor
- Blocker or status-quo beneficiary

For each relevant role, record success criteria, perceived risk, proof required, approval power, and the language they need to explain the decision internally.

Do not mistake a friendly contact for decision authority or consensus.

## Diagnose the stop structure

Classify the primary stop point:

- No real need or wrong ICP
- Need exists but is not articulated or urgent
- Contact exists but recall or trust is weak
- Problem is understood but the proposed value is generic
- Comparison criteria are missing or unfavorable
- Economic case or budget path is absent
- Internal consensus or approval format is missing
- Procurement, security, legal, or implementation risk blocks progress
- Expected value is unclear after purchase
- The next step has no owner, date, or deliverable

Do not explain a stalled deal as buyer hesi

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---
name: design-marketing-communications
description: "Design marketing communications from a defined customer-state transition, meaning, recall, trust, comparison, expectation, and action path rather than from channels. Use when a user asks for a communications strategy, brand message, awareness or recall plan, PESO or touchpoint roles, TV/PR/SNS/Web/store integration, a functional-versus-emotional message decision, expectation and UX alignment, word-of-mouth or buzz design, or a route from paid contact into owned assets, search, sales, store, product, or customer success."
---

# Design Marketing Communications

Design the customer-state transition before selecting media or producing messages. Communication is one intervention within marketing; do not use it to replace product value, availability, price, implementation, or experience.

Read [references/state-and-meaning.md](references/state-and-meaning.md) for every substantive design. Read [references/touchpoint-and-transmission.md](references/touchpoint-and-transmission.md) when assigning PESO, real/digital roles, or word-of-mouth. Read [references/output-contract.md](references/output-contract.md) before returning a complete strategy.

## Establish the decision

Identify:

- Who must decide what and by when
- The customer, buying situation, and demand state
- The current customer state
- The single next state communication should create
- The behavior or downstream path that state should enable
- Product, price, distribution, experience, sales, or operational constraints
- The acceptable cost, trust risk, and review horizon

If the primary bottleneck is product value, availability, adoption, or continuation, do not recommend communication as the primary solution. Ask at most three questions that can change the state transition, then proceed provisionally when possible.

## Define one state transition

Use the smallest relevant path:

```text
Latent or unrecognized need
  → recognition or category entry
  → awareness and memory
  → recall in the buying situation
  → understanding and meaning
  → trust, preference, or consideration
  → comparison and choice
  → intended action
  → expectation and experience
  → re-recall, re-selection, or advocacy
```

Name:

- Current state
- Desired next state
- Barrier to transition
- Customer evidence that the transition occurred
- Downstream owner after communication

Do not attempt to move every state in one execution. Recall and trust may support multiple stages, but still define the primary transition.

## Diagnose the buying condition

Classify only what changes the design:

- Convenience versus specialty purchase
- Low versus high involvement
- Impulse versus planned purchase
- Individual versus organizational decision
- Immediate demand versus future demand
- Search-led, shelf-led, relationship-led, or habit-led choice

Treat these as contextual dimensions, not fixed product categories. The same offer may require different communication by use case.

## Design the meaning

Use:

```text
Product → meaning → customer context → choice
```

Define:

- The customer as subject, not the brand
- The situation in which the message should be recalled
- One meaning the customer should reconstruct
- The choice reason that meaning supports
- Proof or experience that makes it credible
- What should not be remembered or overpromised

Measure success by what was reconstructed, not what was transmitted. Reduce information before adding more. Do not use brand jargon that requires the sender to explain it.

## Balance function, story, emotion, and logic

Assign roles rather than choosing a universal winner:

- Function creates understanding and practical credibility.
- Story creates context, empathy, and motivation.
- Emotion starts or accelerates attention and action.
- Logic removes uncertainty, perceived risk, and braking forces.

Match the mix to involvement, decision risk, prior knowledge, and channel context. Do not frame function versus sto

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---
name: design-marketing-measurement
description: "Design or audit marketing measurement systems, KPI trees, effect measurement, experiments, MMM interpretation, and continuation or withdrawal rules. Use when a user asks what to measure, how to connect a marketing objective to KGI and KPI, whether sales or ROAS is an appropriate success metric, how to choose among A/B tests, Geo tests, surveys, logs, MMM, or proxy signals, how much causal confidence a result supports, or how to define Baseline, Desired Signal, Counter-signal, Guardrail, review window, and action thresholds."
---

# Design Marketing Measurement

Design measurement for a decision, not a dashboard. Start from what the organization must decide and what return the intervention is meant to create. Do not begin with available metrics.

Read [references/measurement-principles.md](references/measurement-principles.md) for every substantive design. Read [references/method-selection.md](references/method-selection.md) when selecting evidence or auditing MMM and experiments. Read [references/output-contract.md](references/output-contract.md) before returning a complete specification.

## Establish the decision and return

Identify:

- Who will decide what, and by when
- The intervention and population in scope
- The single primary return `R`
- The expected time horizon
- The acceptable loss or downside
- The action that a result will trigger

Define `R` as the customer or business state the intervention is supposed to change: recall, understanding, preference, trust, qualified demand, purchase, activation, continuation, profit, or another explicit state.

If the marketing structure or primary bottleneck is still unknown, do not create a company-wide KPI tree. Return to structural diagnosis or produce only a provisional measurement discovery plan.

## Separate responsibility levels

Distinguish:

1. **Business KGI:** the organization-level result, such as profit, revenue, customers, or continuation.
2. **Intervention KGI:** the customer state or result the specific intervention can reasonably own.
3. **KPI:** an intermediate variable hypothesized to move the intervention KGI.
4. **Operational metric:** delivery, quality, or execution health.

Do not assign sales as the direct KGI of one communication intervention unless a defensible counterfactual and control of material product, price, distribution, competitive, seasonal, and sales effects exist.

Do not call reach, clicks, downloads, or open rates business outcomes. They can be delivery metrics, proxies, or weak signals depending on the decision.

## Build the smallest useful causal chain

Use:

```text
Intervention → customer-state change → behavior → business outcome
```

For every arrow, record:

- The causal hypothesis
- Population and period
- Known confounders
- Observable measure or proxy
- What evidence would weaken the link

Classify each expression as a meaning equation, accounting equation, probability equation, or hypothesis tree. Do not calculate a meaning equation or uncalibrated hypothesis tree.

Select a small number of decision-relevant measures. Do not reward a KPI merely because it is easy to collect.

## Choose the evidence method

Select methods by the claim required, intervention level, feasibility, lag, and risk.

- Use logs for observed behavior and delivery.
- Use surveys for recognition, recall, understanding, preference, trust, and intent.
- Use user-level A/B tests for treatment differences within a controllable interface or message.
- Use Geo or comparable market tests for macro incremental effects when spillover and region comparability can be managed.
- Use MMM for historical fit, hypotheses, anomalies, audits, and rough ranges—not causal truth or exact allocation.
- Use multiple independent signals when no single method can identify the effect.

Read `method-selection.md` for method constraints. State what the design can and cannot establish.

## Define the decision boundary

Every conse

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---
name: diagnose-marketing-structure
description: "Diagnose ambiguous marketing, growth, revenue, acquisition, retention, brand, channel, or go-to-market problems before recommending tactics. Use when a user asks why sales are not growing, what marketing should prioritize, whether to invest in ads/SEO/SNS/CRM/MA, how to choose among competing initiatives, or needs the business and customer-decision structure decomposed into demand, recall/acquisition, choice/value realization, availability, continuation, and relationship. Identify the maximum bottleneck, evidence gaps, what not to do, and whether a specialist measurement, advertising, B2B, CRM/LTV, communications, or reasoning audit is needed."
---

# Diagnose Marketing Structure

Treat this skill as the entry point to Marketing Compass. Diagnose the constraint before generating tactics. Do not assume the channel named by the user is the actual problem.

Read [references/core-principles.md](references/core-principles.md) for every substantive diagnosis. Read [references/diagnostic-model.md](references/diagnostic-model.md) when mapping the business, selecting equations, or comparing bottlenecks. Read [references/output-contract.md](references/output-contract.md) before returning a full diagnosis or requesting missing information.

## Establish the decision

Identify:

- Who must decide what
- The decision deadline
- Available budget or capacity
- Tolerable loss and irreversible risks
- What is outside the decision scope

If critical context is missing, ask at most three questions that could change the decision. Do not demand exhaustive discovery. When useful, continue with an explicitly provisional diagnosis.

Do not ask for a metric merely because it is conventionally available. Ask only when it distinguishes competing bottleneck hypotheses.

## Classify the demand problem

Distinguish:

1. **Base demand occurrence:** the need state or event exists independently of marketing.
2. **Demand recognition:** the customer has the problem but has not recognized or articulated it.
3. **Demand acceleration:** marketing can bring a future decision forward.
4. **Context or category creation:** marketing can create a new meaning, use case, or comparison frame, with high uncertainty.

Do not say simply that marketing can or cannot create demand. Name which of the four is in scope.

## Build the smallest useful structure

Choose the model that matches the decision. Do not fill every framework.

- Revenue accounting: trial revenue plus repeat revenue
- Measurable operating model: traffic × conversion × value × continuation
- Customer-decision model: demand → recall/acquisition → choice/value realization → continuation/relationship
- Availability model: mental availability × physical availability
- B2B model: demand-bearing account → contact/recall → problem resolution and comparison → internal approval → value realization → continuing relationship

Separate:

- Known values
- Proxy values
- Unknown values
- Meaning equations, accounting equations, probability equations, and hypothesis trees

Never calculate with a meaning equation or an uncalibrated hypothesis tree.

## Select the maximum bottleneck

Generate competing bottleneck hypotheses, then compare them using:

1. Expected effect on the total outcome
2. Proximity to zero or a hard constraint
3. Evidence strength
4. Ability to influence the variable
5. Time to learn
6. Reversibility and downside
7. Implementation and organizational feasibility

Select one primary bottleneck and, when needed, one secondary hypothesis. If evidence cannot distinguish them, recommend the smallest test that can.

Do not select a variable merely because it is easiest to measure. Do not list many equal priorities.

## Test the customer decision

Check only the dimensions relevant to the suspected bottleneck:

- Trigger or need state
- Recall and consideration set
- Choice criteria and preference
- Price, trust, proof, and perceived risk
- Physical and digital

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---
name: evaluate-ad-investment
description: "Evaluate whether an advertising plan, channel, budget, brand campaign, performance campaign, TV campaign, or media reduction qualifies as an investment and under what conditions. Use when a user asks whether advertising is worth it, how to compare brand and performance advertising, whether to cut or increase media, what return and time horizon to use, how to classify current-value, non-current-value, or organizational advertising, or how to define incremental return, residual value, safe floors, signals, guardrails, and withdrawal rules."
---

# Evaluate Advertising Investment

Judge the investment role before judging media efficiency. Treat advertising as an intervention in the timing or probability of purchase, recall, consideration, trust, or selection. Do not assume that all advertising has the same return period or can be compared by one metric.

Read [references/investment-model.md](references/investment-model.md) for every substantive evaluation. Read [references/decision-branches.md](references/decision-branches.md) when distinguishing optimization from threshold defense or selecting tests. Read [references/output-contract.md](references/output-contract.md) before returning a complete recommendation.

## Establish the decision

Identify:

- Who must decide what and by when
- The product, market, customer, and buying situation
- The budget change under consideration
- The probability or timing the advertising is intended to change
- The evaluation period and expected lag
- The acceptable loss, recovery time, and irreversible risk
- Product, price, distribution, sales, experience, or demand constraints outside advertising

If the underlying sales problem or primary bottleneck is unknown, do not approve a large advertising change. Return to structural diagnosis or limit the answer to a provisional test.

Ask no more than three questions that can change the classification or decision. Continue with labeled assumptions when appropriate.

## Name the intended probability

Choose the primary intervention target:

- Bring forward an already-likely purchase
- Enter or strengthen recall at a future category-entry moment
- Enter the consideration set
- Increase trust or reduce perceived risk
- Change meaning, comparison frame, or category context
- Maintain a baseline against forgetting or competitive pressure

Do not use “awareness” as a complete objective. State what awareness is expected to enable.

## Classify the advertising

Assign one primary class from `investment-model.md`:

1. **Current-value advertising:** buys time by accelerating existing demand through a known recovery path.
2. **Non-current-value advertising:** buys a future option or probability such as recall, trust, or consideration entry.
3. **Organizational advertising:** primarily buys internal reassurance, legitimacy, continuity, relationships, or institutional convenience while the market probability remains undefined.

Use `defensive / maintenance cost` only as an operating tag under non-current-value advertising; do not create a fourth class.

If one plan has materially different roles, split it into components rather than forcing a blended label.

## Test investment qualification

For current-value advertising, require:

- Existing or identifiable demand
- A defined conversion and profit path
- Incremental or marginal return logic
- Capacity, stock, sales, and value realization
- A limit where additional spend no longer qualifies
- Expected behavior when spend stops

For non-current-value advertising, require:

- A defined future customer-state change
- A plausible mechanism and relevant buying horizon
- Leading signals and counter-signals
- A theory of what persists after exposure
- A review period matched to lag
- A withdrawal or redesign rule

For organizational advertising, require transparent accounting as an organizational cost. Do not disguise it as market investment or assign invented ROI.

## Separa

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