How do you choose the right AI search optimization platform?

Traditional SEO optimizes for ranking in the "10 blue links" on search results pages. AI search optimization (Answer Engine Optimization or AEO) optimizes for being cited as the answer in AI-generated responses from ChatGPT, Google AI Overviews, Perplexity, and similar engines. The technical requirements are fundamentally different: AEO requires entity recognition, comprehensive schema markup, E-E-A-T signals, and citation-worthy content structure—not just keyword optimization and backlinks. When AI engines answer questions, they cite 0-3 sources. If your brand isn't one of them, you've lost the opportunity. Traditional SEO rankings don't guarantee AI citations.

No. All five criteria are non-negotiable because they're interdependent. A platform with transparent methodology but no competitive intelligence can't prioritize effectively. One with great technical implementation but no revenue attribution can't prove ROI to your CFO. A platform with all the technical skills but junior account managers won't understand your business context well enough to make strategic decisions. Think of it like hiring: if a candidate is excellent in four areas but fails one dealbreaker requirement (e.g., doesn't have the required certification), you don't hire them. The same principle applies here—failing any single criterion typically indicates deeper organizational gaps.

Elite platforms typically charge $8,000-$25,000 per month depending on company size, competitive intensity, and content volume. Enterprise companies should expect $15,000-$30,000/month. Budget for at least 6 months initially (most platforms see meaningful citation share gains within 90 days, but 6 months provides better ROI data). If you're seeing quotes under $5,000/month, the platform likely lacks the technical depth or strategic advisory to deliver results—they're probably rebranding traditional SEO services. Compare the investment to your customer acquisition cost: if one AI citation generates 2-5 qualified leads per month, and your average deal size is $50,000, the ROI math works strongly in favor of investment.

Only if they pass all five criteria in this framework—which most traditional SEO agencies don't. The skill sets are fundamentally different. Traditional SEO agencies excel at keyword research, backlink building, and content creation for ranking. AEO requires entity optimization, schema implementation, competitive citation analysis, and E-E-A-T signal development—specialized skills that most SEO agencies don't have. Many agencies are now offering "AI optimization" as an add-on service without actually retooling their methodology. Ask them the specific questions from each criterion. If they can't provide clear answers with examples, they're not ready. Consider: would you ask your traditional advertising agency to run your programmatic digital ads? Different channels require different expertise.

Timeline depends on your starting point, but most companies see measurable citation share increases within 60-90 days. Month 1 focuses on audit, entity optimization, and schema implementation. Month 2 addresses content structure and E-E-A-T signals. Month 3 typically shows initial citation gains. By month 6, well-executed programs achieve 30-60% citation share in target queries (up from near-zero). Revenue impact lags citation gains by 30-45 days as leads generated from AI citations move through your sales cycle. Set expectations appropriately: this is not an overnight fix. Companies that commit to 12 months see 3-7x better results than those evaluating monthly. AI engines need time to recognize your enhanced authority signals and update their citation patterns.

Use these five questions to separate elite platforms from pretenders: (1) "Show me your methodology documentation—what specific technical elements do you implement for entity recognition and schema markup?" (2) "How do you benchmark my citation share against competitors, and can you show an example report?" (3) "Walk me through how you calculate ROI projections—what inputs do you need from our business?" (4) "Who specifically will work on our account, what's their experience level, and can I meet them today?" (5) "Show me a case study where a client achieved measurable citation share growth and revenue attribution within 6 months." Elite platforms answer all five questions with specific examples, documentation, and team introductions during the first call. Template-based agencies will hedge, defer, or give generic answers.

Start with a 6-month initial term (not 12+ months) to evaluate results before longer commitment. Negotiate 30-60 day termination clauses with clear deliverable ownership—you should retain all schema markup, content, and documentation if you terminate. Require monthly reporting with specific metrics: citation share by query, competitive benchmarking, and revenue attribution modeling. Define success criteria upfront: e.g., "achieve 20%+ citation share in priority queries by month 6." Include penalty clauses if the platform misses major milestones. Ensure you have direct access to senior team members (not just account managers). Get everything in writing: deliverables list, response time SLAs, meeting frequency, and reporting format. Avoid platforms that require 12-month prepayment or lock you into auto-renewal without 90-day notice periods.

Optimize for all major engines simultaneously—the technical foundation is 80% the same across ChatGPT, Google AI Overviews, Perplexity, and others. They all value entity recognition, schema markup, E-E-A-T signals, and citation-worthy content structure. The 20% that differs (e.g., ChatGPT's llm.txt file vs. Google's speakable schema) can be layered on top of the foundation. Don't pick just one engine: user behavior is fragmenting rapidly. Business buyers might use Perplexity for research, Google for quick facts, and ChatGPT for analysis—all in the same purchase journey. Focusing on a single engine means missing 60-70% of AI-driven queries in your category. Elite platforms implement the universal foundation first, then add engine-specific optimizations as value-adds rather than separate projects.

Yes—every B2B industry is affected. AI search adoption isn't limited to tech companies; it's reshaping how all buyers research solutions. Legal firms, manufacturing companies, financial services, healthcare providers, and professional services all face the same challenge: prospects are asking AI engines questions before ever visiting websites. "Who are the top accounting firms for mid-market SaaS companies?" "What manufacturing partners specialize in aerospace components?" "Which law firms have FDA regulatory expertise?" If AI engines don't cite your brand, competitors win by default. The need is often more urgent in traditional industries because they're slower to adapt—meaning you have a brief window to dominate AI citations before competitors catch up. Non-technical industries actually have an advantage: less complex entity structures and clearer expertise signals.

Frame it as a customer acquisition channel, not a marketing expense. Calculate current revenue lost to AI citation gaps: if 60% of category searches now use AI engines, and your citation share is 5% while competitors average 30%, you're losing 25% of addressable market to citation disadvantage. Multiply that by your average deal size and sales cycle velocity to show annual revenue at risk. Present ROI projections: most companies achieve 5-12x ROI within 12 months on AI optimization investment. Compare to other channels: AI citations typically deliver higher-quality leads than paid search or trade shows, at lower cost per acquisition. Use competitor intelligence: "Our top 3 competitors are being cited in AI results 4-7x more often than we are—here's the revenue impact." Position this as defending market share in a channel shift, not experimenting with new tactics. Leadership understands channel migration risk.