AI Search Optimization Templates and Checklists

The Playbook lives or dies on whether the operating cadence actually gets executed. These templates exist so the cadence can start on Monday, not in two months when someone has built tooling from scratch. Copy them, paste them into Google Sheets, Notion, or wherever your team works, and adapt the columns to your category.

Each template includes context: when to use it, which strategy it supports, and what to do with the output.

1. AI Citation Audit Spreadsheet

When to use: Monthly, as the source dataset for the Monthly Dashboard. Also at program kickoff to establish baseline visibility.

Supports: Measurement Cadence and Expectations (Chapter 13), Narrative and Reputation Alignment (Chapter 14).

The AI Citation Audit is the spreadsheet behind every monthly report. It tracks the same set of prompts run across the same set of platforms, captures whether you were cited and how, and flags trends over time.

Column definitions

2. Weekly Monitoring Protocol

When to use: Every week, indefinitely, once the program is live.

Supports: Measurement Cadence and Expectations (Chapter 13). Light-touch operating rhythm.

Weekly monitoring is not a full audit. It is a quick scan to catch material changes between monthly audits and to spot reputation issues before they compound.

WEEKLY MONITORING PROTOCOL
Owner: AI Search Lead
Time required: 60 to 90 minutes per week, distributed
Cadence: Monday, Wednesday, Friday

MONDAY (30 minutes): Volatility Check
  [ ] Run top 5 priority prompts in ChatGPT, Perplexity, Google AI Overviews
  [ ] Compare citations to prior Monday baseline
  [ ] Flag any new omissions (you were cited, you are not now)
  [ ] Flag any new hallucinations or sentiment shifts
  [ ] Log results in weekly tracker

WEDNESDAY (30 minutes): Competitor and Mention Scan
  [ ] Review Alertmouse / Ahrefs Alerts digest for the week
  [ ] Check competitor citation positions for top 5 prompts
  [ ] Note any new third-party citations of your brand
  [ ] Note any new third-party citations of top 3 competitors
  [ ] Flag content opportunities surfaced by mentions

FRIDAY (30 minutes): Source Health and Refresh Triggers
  [ ] Check freshness of pages cited in this week's audits
  [ ] Identify any cited page over 12 months stale
  [ ] Add stale-page refresh tickets to next week's content queue
  [ ] Verify robots.txt and crawler access have not been changed
  [ ] Send weekly summary email to executive sponsor (5 bullets max)

3. Monthly Dashboard Structure

When to use: First week of each month, covering the prior month.

Supports: Measurement Cadence and Expectations (Chapter 13).

The Monthly Dashboard is what executive sponsors see. It must be readable in five minutes and tell a clear story. The structure below is the minimum viable layout.

MONTHLY DASHBOARD: AI SEARCH PROGRAM
Period: [Month YYYY]
Prepared by: [Name], [Date]

1. EXECUTIVE SUMMARY (3 to 5 bullets)
   - Headline result for the month (citation rate, share of voice)
   - One material change vs. prior month
   - One material change vs. prior quarter
   - Top risk or volatility flag
   - Next-month focus

2. CITATION RATES BY TOPIC
   - Table: Topic | Prompts Tracked | Citation Rate | Δ vs Prior Month
   - Highlight any topic with citation rate change >10 percentage points
   - Note: AI volatility is real; report 30-day moving averages, not week-to-week

3. SHARE OF VOICE
   - Table: Competitor | Citations | Share of Voice | Δ vs Prior Month
   - Stack bar chart: your brand vs. top 3 competitors over last 6 months
   - Flag any competitor gaining >5 share-of-voice points

4. TRAFFIC ATTRIBUTION
   - AI-attributed sessions in GA4 (chat.openai.com, perplexity.ai, gemini.google.com, copilot, etc.)
   - Conversion rate from AI traffic vs. traditional organic
   - Pipeline or revenue attributed (if attribution model in place)

5. VOLATILITY REPORT
   - Number of prompts with citation present in 100% of runs
   - Number of prompts with citation present in 50-99% of runs
   - Number of prompts with citation present in <50% of runs
   - Hallucinations or sentiment incidents this month
   - Reputation alignment status: any open training-baked vs. retrieval-baked items

6. ACTIONS COMPLETED THIS MONTH
   - Bullet list, tied to MERIT strategies
   - One sentence per action

7. ACTIONS QUEUED FOR NEXT MONTH
   - Top 5 priorities, tied to MERIT strategies
   - Owner and due date for each

4. Quarterly Strategic Review Agenda

When to use: Once per quarter, with executive sponsor and core program team.

Supports: Measurement Cadence and Expectations (Chapter 13), Organizational Evolution (Chapter 15).

Quarterly reviews are where strategy gets re-pointed. Monthly dashboards report progress; quarterly reviews ask whether the program is solving the right problem.

QUARTERLY STRATEGIC REVIEW
Duration: 90 minutes
Attendees: Executive sponsor, AI Search lead, content lead, technical SEO lead
Pre-read: Last 3 monthly dashboards plus Quarterly Trend Pack

AGENDA

1. Quarterly Trend Recap (15 minutes)
   - 90-day citation rate trajectory by topic
   - 90-day share-of-voice trajectory vs. top 3 competitors
   - 90-day AI-attributed traffic and conversion trend
   - Top wins and top losses

2. Strategy-Level Health Check (20 minutes)
   - Walk through each MERIT strategy in scope
   - Status: Green (on plan), Yellow (at risk), Red (blocked)
   - One sentence on what's driving the status
   - Specific blockers requiring executive support

3. Competitive Intelligence (15 minutes)
   - Significant competitor moves in the quarter
   - New entrants in tracked prompt set
   - Platform-level changes (new AI engine, new feature)

4. Reputation and Narrative Review (15 minutes)
   - Any reputation issues surfaced (training-baked vs. retrieval-baked)
   - Narrative drift in AI responses (Narrative and Reputation Alignment)
   - Open items from Narrative and Reputation Alignment (Chapter 14)

5. Resourcing and Capability (10 minutes)
   - Bandwidth: is the program staffed for next quarter's plan?
   - Capability gaps: skills, tools, content production
   - Vendor performance and cost review

6. Next-Quarter Bets (15 minutes)
   - Top 3 strategic priorities
   - Specific commitments and owners
   - What we will stop doing or de-prioritize

CLOSE: Single-page summary mailed within 48 hours.

5. Reddit Engagement Plan

When to use: At program inception for any team planning to engage on Reddit.

Supports: Community Mentions and Positive Sentiment (Chapter 2).

Reddit is the second most-cited source in AI responses (Profound, October 2025). It is also the platform where premature brand promotion gets accounts banned and hurts long-term visibility. The plan below is the minimum threshold for entering the platform without doing damage.

REDDIT ENGAGEMENT PLAN
Owner: [Name, real person, real account]
Account: [Reddit username]
Strategy: Build trust before promotion

PHASE 1: ACCOUNT BUILD (4 to 8 weeks, before any brand mention)
  Goal: 500+ karma, established posting history
  Activity:
    - Identify 3 to 5 subreddits relevant to your category
    - Read each subreddit's rules thoroughly
    - Comment thoughtfully on existing posts (5 to 10 per week)
    - Answer questions from your area of expertise
    - Do NOT mention your brand or product yet
    - Do NOT post links to your owned content yet

PHASE 2: VALUED CONTRIBUTOR (8 to 16 weeks)
  Goal: Recognized contributor in target subreddits
  Activity:
    - Post original analysis or perspective (1 to 2 per month)
    - Engage in comments on your own posts as well as others
    - Reference industry research and third-party sources
    - Begin occasional disclosure of role and expertise
    - Brand mention only when directly relevant and helpful
    - Apply 90/10 rule: 90% value, 10% promotion (max)

PHASE 3: ONGOING ENGAGEMENT (continuous)
  Goal: Sustained presence, AI co-citation
  Activity:
    - Monthly cadence of substantive contributions
    - Respond to direct questions about your category or brand
    - Cross-link to original source assets (Original Source Asset Development) where relevant
    - Track which posts get cited by Perplexity, ChatGPT
    - Adjust topic mix based on what AI systems pick up

GUARDRAILS (ALL PHASES)
  - Real account, real person, never a brand account
  - Disclose affiliation when discussing your own product
  - Never astroturf with multiple accounts
  - Never delete-and-repost to game timing
  - When in doubt, do not post

6. Original Source Asset Brief

When to use: Before commissioning any major content asset (research report, framework, opinion piece, dataset, tool).

Supports: Original Source Asset Development (Chapter 4), Third-Party Corroboration (Chapter 3).

The brief forces clarity on what is genuinely new (information gain) versus what is restating known territory. Score the draft against Information Gain Density (the 5-to-7 distinct-insight count) before it goes into production. If a brief cannot answer "what is the net-new claim," the asset should not be commissioned.

ORIGINAL SOURCE ASSET BRIEF

ASSET TYPE: [Framework / Original Research / Opinion / Dataset / Tool]
WORKING TITLE: [Concise, citable]
OWNER: [Name]
TARGET PUBLICATION DATE: [Date]

1. INFORMATION GAIN
   - What is the net-new claim, finding, or framework this asset contributes?
   - What does the model not already know about this topic?
   - In one sentence, why would AI prefer to cite this over existing sources?

2. METHODOLOGY (for research and data assets)
   - Data sources (with documentation links)
   - Sample size and selection method
   - Time period covered
   - Analytical approach (statistical methods, qualitative coding, etc.)
   - Limitations and known biases

3. KEY FINDINGS (placeholder before research; final after)
   - Headline finding 1
   - Headline finding 2
   - Headline finding 3
   - Counterintuitive or surprising finding
   - Quotable statistics with full context

4. SUPPORTING ENTITIES
   - Author(s) and credentials
   - Author schema and SameAs targets
   - Internal SMEs cited or quoted
   - External voices included (interviewed, quoted, peer reviewed)

5. STRUCTURAL DESIGN
   - How will the page be structured at the passage level for AI retrieval (retrieval systems internally segment content; this is sometimes called chunking)?
   - Self-contained sections, snippet-extractable findings
   - JSON-LD schema (Article + Organization + Person)
   - Internal cross-links to related assets

6. DISTRIBUTION PLAN
   - Owned channels: blog, newsletter, social
   - Earned channels: target publications, podcasts, panels
   - Paid amplification (if any): platform and budget
   - Outreach list: 25+ relevant journalists, podcasters, and SMEs
   - Co-citation strategy: who else should be referenced alongside this asset

7. EXPECTED CO-CITATIONS
   - List of authoritative sources the asset will reference
   - List of sources the asset hopes to be co-cited with
   - Plan for follow-up content that reinforces co-citation patterns

8. SUCCESS METRICS
   - Citation goal (number of AI-engine citations within 90 days)
   - Earned media goal (third-party references within 90 days)
   - Traffic goal and AI-attribution goal
   - Refresh cadence (when will it be updated; trigger conditions)

7. Reputation Alignment Audit Query Template

When to use: Quarterly, or anytime an executive flags AI describing the brand inaccurately.

Supports: Narrative and Reputation Alignment (Chapter 14).

Reputation Alignment audits test the same questions across multiple AI engines and document where each engine's answer is accurate, slightly off, materially wrong, or overtly misleading. Pair this with the anchor set methodology to define the stable set of authoritative pages the brand defends across surfaces. The output drives whether the corrective work is retrieval-baked (fixable now) or training-baked (fixable through corroborating signal over time).

REPUTATION ALIGNMENT AUDIT
Brand: [Brand Name]
Date: [Run Date]
Engines: ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews

QUERY SET (run each prompt in each engine)

A. IDENTITY AND POSITIONING
  1. What is [Brand Name]?
  2. Who founded [Brand Name] and when?
  3. Where is [Brand Name] headquartered?
  4. How big is [Brand Name]? (employees, revenue, customers)
  5. What does [Brand Name] sell?

B. PRODUCT AND POSITIONING
  6. What are [Brand Name]'s main products or services?
  7. Who is [Brand Name]'s target customer?
  8. What makes [Brand Name] different from competitors?
  9. What are [Brand Name]'s strengths?
  10. What are [Brand Name]'s weaknesses or limitations?

C. COMPETITIVE FRAMING
  11. Who are [Brand Name]'s main competitors?
  12. Compare [Brand Name] vs. [Top Competitor 1].
  13. Compare [Brand Name] vs. [Top Competitor 2].
  14. When should I choose [Brand Name] over [Top Competitor]?
  15. When should I choose [Top Competitor] over [Brand Name]?

D. PEOPLE
  16. Who is [CEO Name]?
  17. What is [CEO Name] known for?
  18. Where did [CEO Name] work before [Brand Name]?
  19. (For each named SME) Who is [SME Name]?

E. TRUST AND CONTROVERSY
  20. Has [Brand Name] been involved in any controversies?
  21. What do customers or reviewers say about [Brand Name]?
  22. What are common complaints about [Brand Name]?
  23. Is [Brand Name] reputable?

DOCUMENTATION

For every response, capture:
  - Verbatim AI response
  - Sources cited (URLs)
  - Errors flagged (factual, narrative, sentiment)
  - Severity: Minor (cosmetic) | Material (affects buyer decision) | Critical (legal/reputational risk)
  - Diagnosis: Training-baked (model has wrong info baked in) vs. Retrieval-baked (model is reading bad sources right now)

REMEDIATION
  - Retrieval-baked: identify the source, request correction, publish corrective content, monitor weekly
  - Training-baked: invest in third-party corroborating signal (Third-Party Corroboration and Original Source Asset Development), monitor monthly, expect slow change
  - Critical-severity issues: escalate to executive sponsor and legal/comms before public action