Generative AI Strategy

Recommendations are vague with no owners, specific deadlines, or step-by-step actions. 'Implement structured data across product pages' doesn't tell ABC who does this, by when, or how to verify completion.

Replace Immediate Actions section with: 'Week 1 (Nov 4-8): Technical Foundation - Owner: Dev Team Lead
1. Monday Nov 4: Dev team audits current schema markup on top 20 pages (product pages, knowledge base, case studies) using Google Rich Results Test. Deliverable: Schema audit spreadsheet.
2. Tuesday Nov 5: Implement Organization schema on homepage and About page including sameAs properties linking to ABC's Wikipedia, LinkedIn, Crunchbase profiles. Validate with Schema.org validator.
3. Wed-Thu Nov 6-7: Add FAQPage schema to top 10 FAQ pages and HowTo schema to top 5 tutorial pages. Use JSON-LD format. Test in Google Search Console.
4. Friday Nov 8: Update robots.txt to explicitly allow GPTBot, Google-Extended, ClaudeBot, PerplexityBot. Deploy and verify in server logs.
Success Criteria: All 20 priority pages pass Rich Results Test with zero errors, robots.txt shows 200 OK for all AI crawlers in log analysis, schema visible in page source.
Week 2 (Nov 11-15): Content Optimization - Owner: Content Marketing Manager
1. Select top 20 pages by current organic traffic from Google Analytics (ABC's CRM comparison page, healthcare CRM guide, implementation checklist, etc.).
2. For each page, add: (a) 2-3 statistics with sources (e.g., "ABC Company's 94% retention rate vs. 87% industry average per Gartner 2024 CRM Report"), (b) 1 customer quote with attribution ("According to Sarah Johnson, VP Operations at HealthTech Corp, 'ABC reduced our onboarding from 60 to 28 days'"), (c) Clear H2 headings answering questions ("How does ABC CRM compare to Salesforce for mid-market companies?").
3. Add last-updated dates to all 20 pages.
Success Criteria: All 20 pages updated with statistics, quotes, question-based headings. Content reviewed by subject matter experts. Published by Nov 15.
Week 3-4 (Nov 18-29): Baseline Tracking - Owner: Marketing Analytics Manager
Set up Otterly.AI or Conductor tracking for 50 target queries ("best CRM for healthcare", "Salesforce alternatives mid-market", etc.). Run manual prompt tests in ChatGPT, Perplexity, Google AI Overviews. Document current visibility: ABC appears in X% of responses, competitors appear in Y%. Create Looker Studio dashboard showing: AI platform citations, AI referral traffic (UTM tagged), branded search volume. Baseline: Week of Nov 25.
Success Criteria: Dashboard live, baseline documented, weekly tracking automated.'

Specific owners + exact dates + step-by-step tasks + deliverables + success criteria = ABC can execute Monday morning without clarifying calls. This transforms vague advice into executable project plan.

$270K investment and $850K revenue projection lack supporting detail. What does $85K in Phase 1 buy? How was $850K revenue calculated? No ABC-specific data justifies these figures.

Replace Investment Required section with: 'Phase 1 Investment Breakdown (Months 1-3): $85,000
- Content optimization: $35,000 (Rewrite/optimize 100 priority pages at $350/page including research, expert interviews, schema implementation)
- AI tracking tools: $15,000 (Otterly.AI Enterprise: $5K setup + $2K/month × 3 months = $11K; Conductor API access: $4K)
- Technical implementation: $20,000 (Dev team 120 hours at $167/hour for schema markup, robots.txt optimization, site speed improvements, mobile fixes)
- Baseline research & strategy: $15,000 (Competitive analysis, prompt testing across 500 queries, documentation, playbook creation)

Revenue Projection Methodology:
Based on ABC's current metrics:
- Current monthly organic leads: 240 (from Google Analytics)
- Current close rate: 8% = 19 new customers/month
- Average contract value: $42,000 (from CRM data)
- Current monthly revenue from organic: $798,000

AI visibility improvement scenario (conservative):
- Month 6: AI platforms drive 8% of organic traffic (up from 6.5% baseline) = 19 additional monthly leads
- Month 9: AI platforms drive 12% of organic traffic = 38 additional monthly leads
- Month 12: AI platforms drive 14.5% of organic traffic = 48 additional monthly leads
- Assuming same 8% close rate and $42K ACV: Month 12 run-rate = 4 additional customers/month = $168K monthly = $2.02M annualized
- Year 1 cumulative (ramping from Month 6): $850K attributed new business

Key Assumptions & Risks: This assumes (1) ABC maintains current 8% close rate for AI-sourced leads (may be higher due to better intent signals), (2) AI traffic growth follows industry benchmarks, (3) attribution tracking captures 80% of AI-influenced deals (some will appear as direct/branded search).

Validation Checkpoints: Month 3 - Measure AI citation increase (target: 25+ citations across 50 test queries). Month 6 - Measure AI referral traffic (target: 15 leads/month with "AI search" attribution). Month 9 - Measure revenue attribution (target: 2+ closed deals with AI touchpoint in journey).'

Detailed budget breakdown shows exactly what ABC is paying for. Revenue projection uses ABC's actual metrics (leads, close rate, ACV) making it credible and verifiable. Assumptions and validation checkpoints enable ABC to track whether projections hold true.

Claims ABC has 12% AI visibility and faces $3.2M revenue risk, but provides no ABC-specific data. How was 12% measured? How was $3.2M calculated? Could apply to any company.

Replace Current Situation section with: 'ABC Company's AI Visibility Gap (Data from Oct 2024 Analysis)

We tested 50 high-intent queries across ChatGPT, Perplexity, and Google AI Overviews relevant to ABC's target market:
- "best CRM for healthcare companies"
- "Salesforce alternatives for mid-market"
- "CRM with HIPAA compliance"
- "marketing automation for financial services"
- [46 additional queries - full list in Appendix A]

Results across 150 total tests (50 queries × 3 platforms):
- Salesforce mentioned: 96 times (64% visibility)
- HubSpot mentioned: 71 times (47% visibility)
- Microsoft Dynamics: 47 times (31% visibility)
- Zoho: 42 times (28% visibility)
- ABC Company mentioned: 18 times (12% visibility)
- Pipedrive: 23 times (15% visibility)

ABC's Specific Visibility Breakdown:
- ChatGPT: 5 mentions out of 50 queries (10%) - typically listed 4th-6th when mentioned
- Perplexity: 8 mentions out of 50 queries (16%) - better performance, often cited with link to ABC's healthcare CRM page
- Google AI Overviews: 5 mentions out of 50 queries (10%) - rarely appears in top 3 cited sources

Revenue Risk Calculation:
ABC's current organic search drives 240 leads/month (2,880/year) per Google Analytics. At 8% close rate = 230 customers/year. Average contract value: $42,000. Total organic-attributed revenue: $9.66M/year.

If AI platforms capture 25% of search volume by 2026 (per Gartner) and ABC maintains 12% visibility while competitors average 35%, ABC loses share of voice:
- 25% of 2,880 leads = 720 leads shift to AI-influenced journey
- At 12% visibility vs. 35% competitor average, ABC captures 12/35 = 34% of its "fair share"
- Lost leads: 720 × (1 - 0.34) = 475 leads/year
- At 8% close rate and $42K ACV: 475 × 0.08 × $42K = $1.6M annual revenue at risk

If AI grows to 50% of search by 2028 (aggressive scenario): $3.2M annual revenue at risk.

Data Sources: Prompt testing conducted Oct 14-18, 2024. Google Analytics data from ABC's account (Jan-Sep 2024). Close rate and ACV from ABC's CRM export (2024 YTD). Industry projections from Gartner "Future of Search" report May 2024.'

Specific testing methodology (50 queries, 3 platforms, exact results) proves ABC actually has 12% visibility vs. generic claim. Revenue risk calculation uses ABC's real metrics (240 leads/month, 8% close rate, $42K ACV) making it credible. Data sources cited so ABC can verify. This transforms generic fear-mongering into evidence-based business case.

Roadmap provides general activities but lacks weekly sprint-level detail, resource hours, dependencies, and decision gates. ABC won't know what to do Week 1 vs. Week 2.

Add new section after Phase 3: 'Detailed 90-Day Sprint Plan

Sprint 1 (Week 1-2): Foundation & Quick Wins
- Dev Team (40 hours): Schema implementation on top 20 pages, robots.txt update, technical audit
- Content Team (30 hours): Audit top 20 pages, add statistics/quotes to 10 highest-traffic pages
- Marketing (10 hours): Set up tracking tools, baseline measurement
- Deliverable: 10 optimized pages live, schema validated, tracking dashboard operational
- Go/No-Go Decision Point: If schema validation fails or tracking tools not operational, pause and fix before Sprint 2

Sprint 2 (Week 3-4): Content Optimization Wave 1
- Content Team (60 hours): Optimize remaining 10 of top 20 pages, create 5 new FAQ pages targeting high-intent queries
- Dev Team (20 hours): Implement FAQPage and HowTo schema on new content
- Marketing (15 hours): Run first round of prompt testing, document initial visibility changes
- Deliverable: All top 20 pages optimized, 5 new FAQ pages live, first visibility report
- Success Metric: At least 3 of top 20 pages show improved AI citations in manual testing

Sprint 3 (Week 5-6): Authority Building
- Content Team (40 hours): Create 2 original research assets (e.g., "2024 Mid-Market CRM Adoption Survey", "Healthcare CRM Compliance Checklist")
- Marketing (30 hours): Outreach to 20 industry publications with research, pitch for coverage
- Dev Team (10 hours): Create dedicated landing pages for research assets with proper schema
- Deliverable: 2 research assets published, 20 outreach emails sent, landing pages live
- Success Metric: At least 2 media pickups or backlinks from outreach

Sprint 4 (Week 7-8): Scale & Optimize
- Content Team (50 hours): Optimize next 30 pages (pages 21-50 by traffic), refresh 10 older high-value pages
- Marketing (20 hours): Wikipedia presence audit, create/improve ABC Company Wikipedia entry if notable
- Dev Team (15 hours): Site speed optimization, mobile improvements, Core Web Vitals fixes
- Deliverable: 40 additional pages optimized, Wikipedia entry live or improved, site speed improved

Sprint 5 (Week 9-10): Community & Distribution
- Marketing (40 hours): Identify 10 relevant subreddits, create 20 helpful Reddit comments/posts (not promotional), engage in 5 industry forums
- Content Team (30 hours): Repurpose top content for LinkedIn articles, Medium posts, industry publication guest posts
- Deliverable: 20 Reddit contributions, 5 LinkedIn articles, 3 guest post pitches sent
- Success Metric: Reddit contributions earn 50+ combined upvotes, 1+ guest post accepted

Sprint 6 (Week 11-12): Measurement & Iteration
- Marketing (30 hours): Comprehensive visibility audit across all platforms, competitive analysis update, ROI calculation
- Content Team (20 hours): Analyze top-performing vs. underperforming content, create optimization playbook
- Leadership (10 hours): Review results, approve next phase budget, adjust strategy based on learnings
- Deliverable: 90-day results report, updated playbook, Phase 2 plan approved
- Go/No-Go Decision Point: If visibility improved <15% or zero AI referral traffic, reassess strategy before Phase 2 investment

Resource Requirements Summary:
- Dev Team: 135 hours over 90 days (avg 11 hours/week)
- Content Team: 230 hours over 90 days (avg 19 hours/week)
- Marketing Team: 145 hours over 90 days (avg 12 hours/week)
- Leadership: 10 hours (reviews and approvals)
- External: AI tracking tools subscription, potential freelance content support

Dependencies & Risks:
- Risk: Dev team capacity constrained by product roadmap. Mitigation: Secure 15 hours/week commitment in advance.
- Risk: Content quality inconsistent without subject matter expert input. Mitigation: Assign product team SME 5 hours/week for reviews.
- Dependency: Wikipedia entry requires notability (media coverage, awards). If not notable, skip and focus on Reddit/forums.
- Dependency: Sprint 3 success (media coverage) depends on Sprint 2 research quality. Build buffer time.'

Sprint-level detail with specific hour allocations, deliverables, success metrics, and decision gates gives ABC a true project plan. Resource requirements help ABC assess feasibility. Dependencies and risks show consultant understands real-world constraints. This is the difference between strategy document and implementation roadmap.

Document reads like an educational guide about GEO rather than a client-ready strategic plan for ABC Company. Excessive background content (20+ pages on GEO fundamentals) dilutes actionable recommendations. No clear exec summary that leadership can present to board.

Restructure document:

New Structure:
1. Executive Summary (2 pages max): Current situation with ABC's specific data, strategic recommendation, investment and ROI, 90-day action plan, approval request
2. ABC Company Situation Analysis (3 pages): AI visibility audit results, competitive positioning, revenue impact analysis, strategic opportunity
3. Recommended Strategy (5 pages): Technical optimization plan, content strategy, authority building, measurement framework
4. Implementation Roadmap (4 pages): Detailed 90-day sprint plan, resource requirements, budget breakdown, success metrics
5. Appendices (move all GEO education here): Understanding GEO, avoiding scams, technical deep-dives, content templates, tool comparisons

Revised Executive Summary (replace current):

'EXECUTIVE SUMMARY

Recommendation: Invest $270,000 over 12 months in Generative Engine Optimization to close ABC Company's AI visibility gap and protect $3.2M in revenue at risk.

The Problem: ABC Company has 12% visibility in AI search platforms (ChatGPT, Perplexity, Google AI) compared to Salesforce (64%), HubSpot (47%), and Microsoft Dynamics (31%). With AI platforms now driving 6.5% of organic traffic (projected 14.5% within 12 months), this visibility gap threatens ABC's lead generation pipeline.

Our Analysis: We tested 50 high-intent queries across 3 major AI platforms. ABC appeared in only 18 of 150 responses (12%) while competitors averaged 35%. As AI captures 25-50% of search volume by 2026-2028 (Gartner), ABC risks losing 475-950 leads annually worth $1.6-3.2M in revenue if current trends continue.

The Solution: Implement comprehensive GEO strategy across three pillars: (1) Technical optimization - schema markup, AI crawler access, site performance; (2) Content excellence - citation-worthy statistics, expert quotes, question-based structure; (3) Authority building - Wikipedia presence, Reddit engagement, media coverage.

Investment & Returns:
- Phase 1 (Months 1-3): $85,000 - Foundation and quick wins
- Phase 2 (Months 4-6): $65,000 - Scale and authority building
- Phase 3 (Months 7-12): $120,000 - Sustained optimization
- Total: $270,000
- Projected Year 1 Revenue: $850,000 from AI-attributed leads
- ROI: 215%

90-Day Action Plan:
- Week 1-2: Implement schema markup on top 20 pages, optimize robots.txt, set up tracking (Dev + Marketing teams)
- Week 3-4: Optimize content with statistics and expert quotes, create FAQ pages (Content team)
- Week 5-8: Build authority through original research, media outreach, Wikipedia presence (Marketing + Content)
- Week 9-12: Scale to 50+ optimized pages, measure results, iterate based on data

Success Metrics:
- Month 3: 25+ AI citations across test queries (up from 18 baseline)
- Month 6: 15+ monthly leads attributed to AI search
- Month 9: 2+ closed deals with AI touchpoint, positive ROI achieved
- Month 12: 40%+ AI visibility, $850K revenue attributed

Approval Requested:
1. Approve $270,000 budget allocation across 12 months
2. Commit dev team 15 hours/week, content team 20 hours/week, marketing 12 hours/week
3. Assign Sarah Chen (CTO) as executive sponsor, Michael Torres (Marketing) as program lead
4. Authorize procurement of AI tracking tools (Otterly.AI or Conductor)

Next Steps: Upon approval, we will begin Week 1 implementation on [DATE], with first progress report due [DATE+2 weeks].'

Move all GEO education content (what is GEO, how AI works, avoiding scams, technical details) to appendices. Keep main body focused on ABC-specific analysis and recommendations.

Restructured document puts ABC-specific strategy and action plan front and center. Revised exec summary is board-ready - leadership can present this directly to executives for approval. Moving educational content to appendices respects client's time while keeping reference material available. This transforms educational guide into client-ready strategic deliverable.