How to Review an AI-Generated Marketing Strategy

Review an AI-generated marketing strategy as a decision draft. Verify company and product facts, trace material claims to sources, separate observations from inferences, check competitors and customer assumptions, test feasibility against capacity, define metrics and guardrails, and require an accountable owner. Fluent language is not evidence.

What you need

• the generated strategy;
• the corrected Alesta company and product context;
• source evidence and availability states;
• a validated competitor set;
• current business goals and metric definitions;
• product, sales, customer, and engineering reviewers where relevant;
• one final decision owner.

If these inputs are unavailable, the strategy can still generate questions. It should not be presented as an approved plan.

Step 1: Read the strategy without editing it

On the first pass, highlight:

• company and product facts;
• customer and market claims;
• competitor claims;
• quantitative statements;
• proposed priorities;
• assumed resources and dependencies;
• promised outcomes;
• missing limitations;
• actions that affect customers, budget, data, or public claims.

Do not begin by polishing wording. A well-edited false premise becomes harder to notice.

Step 2: Verify identity and scope

Confirm:

• canonical company and product name;
• priority audience and market;
• current product capabilities;
• plan, region, role, integration, and feature-flag limits;
• time horizon;
• decision owner;
• public and private evidence available.

Reject or rewrite any section that depends on roadmap behavior presented as current.

For Alesta specifically, do not assume the live free baseline includes backlink inventory, observed AI mentions, private analytics, social analytics, product analytics, growth analytics, campaign generation, or continuous monitoring.

Step 3: Label every material statement

Use:

Label	Meaning
Observed	Direct public, provider, user, or first-party evidence exists
Calculated	A transparent deterministic rule produced the value
Inferred	A model or analyst interpreted evidence
Asserted	A stakeholder stated it without sufficient corroboration
Unavailable	A required source could not provide a valid value
Not measured	The workflow did not attempt the measurement
Contradicted	Reliable evidence conflicts with the statement

No material recommendation should rely on an unlabeled premise.

Step 4: Trace evidence

For every important claim, record:

Claim:
Label:
Source:
Scope and population:
Date or period:
Method:
Confidence:
Limitation:
Reviewer:

Pay special attention to:

• "customers want";
• "the market is growing";
• "competitors do not offer";
• "the site is slow";
• "SEO is weak";
• "this channel will deliver";
• "AI visibility is low";
• "the product saves time";
• any percentage, ranking, or revenue forecast.

If the source cannot support the statement, change it into a research question or remove it.

Step 5: Check missing data and false zero

Search for values that may be defaults:

• zero field performance data;
• zero backlinks;
• zero AI mentions;
• zero search demand;
• zero conversions;
• absent competitor evidence;
• missing market share.

Ask whether the source measured the scope and returned zero, or whether it was unavailable, skipped, filtered, sampled, or failed. Correct the state before any score or priority calculation.

Step 6: Validate customers and competitors

Customer assumptions

Check whether the strategy uses direct research, a defined first-party sample, or only public copy. Public website language is not customer research.

Competitor assumptions

Confirm direct rivals, adjacent products, substitutes, status quo, search rivals, and aspirational peers. Remove candidates that belong only because of keyword or visual similarity.

Use the competitor validation guide before accepting comparative recommendations.

Step 7: Test strategic coherence

The strategy should connect:

Business outcome or learning goal
  -> priority audience and situation
  -> constraint or opportunity
  -> strategic choice
  -> action portfolio
  -> measurement and review

Red flags include:

• many channels with no shared constraint;
• several priority audiences;
• tactics that do not support the stated goal;
• a positioning choice with no real alternative;
• content topics disconnected from customer or search evidence;
• a technical backlog with no page or business scope;
• growth targets without baselines or economics.

Step 8: Review claim safety

For public messaging, check:

• objective claim has a reasonable evidence basis;
• implied meaning matches the evidence;
• qualification is near the claim and does not contradict it;
• comparative claim is current and scoped;
• customer evidence has permission and context;
• case-study result is not generalized;
• AI-generated claim has human approval;
• regulated examples receive appropriate review.

The FTC's substantiation principle applies before the claim is made, not after a challenge.

Step 9: Test feasibility

For each proposed priority, identify:

• accountable owner;
• required skills and capacity;
• product, engineering, legal, analytics, or creative dependency;
• budget;
• data access;
• release or market timing;
• risk and reversibility;
• work the team will stop or defer.

A strategy that assumes unlimited capacity is a wish list.

Step 10: Validate metrics

Every metric needs:

Name and definition:
Source:
Entity and scope:
Baseline period:
Target or decision threshold:
Attribution model where relevant:
Guardrail:
Review date:
Owner:
Known limitation:

Separate:

• implementation acceptance;
• leading behavior;
• business outcome;
• causal evidence.

Search Console clicks and analytics sessions will not match exactly. Attribution allocates credit under a model; incrementality asks what happened because of the intervention.

Step 11: Convert recommendations into decision cards

Use:

Decision:
Evidence and scope:
Inference and confidence:
Alternatives considered:
Unknowns:
Chosen response:
Owner:
Dependency:
Expected outcome or learning:
Acceptance evidence:
Business measure:
Guardrail:
Review date:
Stop or revise condition:

The audit action-plan article provides worked examples.

Step 12: Approve in layers

Do not use one generic approval for every consequence.

Suggested approvals:

• Context: company and product owners approve facts.
• Evidence: source owners or analysts approve measurement interpretation.
• Claims: marketing and legal reviewers approve public assertions where needed.
• Strategy: accountable leadership approves tradeoffs and budget.
• Delivery: implementation owners approve scope and feasibility.
• Measurement: analytics owner approves definitions and review design.

Retain rejected and revised recommendations with reasons.

Review scorecard

Use coverage, not a blended quality score:

Area	Complete	Partial	Blocked	Owner
Identity and product truth
Source traceability
Customer evidence
Competitor validation
Claims substantiation
Strategic coherence
Capacity and dependencies
Metrics and guardrails
Decision ownership

Blocked areas should remain visible. Do not turn them into zero or quietly drop them.

Example revision

Generated recommendation:

Launch 20 SEO articles and an AI visibility campaign next month to increase qualified pipeline by 30 percent.

Review findings:

• no qualified-pipeline baseline or causal model;
• no query or customer-question map;
• no observed AI visibility data in the free baseline;
• limited editorial capacity;
• competitor and audience context not yet approved;
• outcome claim unsupported.

Decision-card revision:

Validate the priority audience and ten recurring buyer questions using sales, customer, and Search Console evidence. Publish one pillar and two supporting assets with named owners and original evidence. Establish indexing, query, referral, and qualified-event baselines. Run a separate controlled AI visibility observation protocol. Review before expanding the cluster.

The revision removes the guarantee and turns volume into a learning sequence.

Common review failures

• editing prose before checking facts;
• trusting citations without opening them;
• accepting a score with missing inputs;
• treating public website data as customer truth;
• using roadmap capabilities as current;
• allowing strategy to list every channel;
• approving outcome claims without evidence;
• assigning teams instead of owners;
• measuring activity only;
• skipping stop conditions;
• publishing before product and claim review.

What to do next

Approve the smallest evidence-backed portfolio and schedule the first review. Use the AI marketing audit guide if major evidence layers are absent or the fractional CMO scenario when the strategy needs a wider first-month process.