If your team already does SEO well, you're closer than you think.
In most cases, the gap comes down to execution: no clear AI baseline, weak off-site trust signals, and slow iteration cycles.
This 30-day playbook is for teams that already rank on Google and want stronger recommendation visibility in ChatGPT, Perplexity, Claude, Gemini, and Grok.
Days 1-7: Build your baseline
Start by building a clean baseline.
- Choose 20-30 high-intent prompts. Include category terms, use-case queries, competitor comparisons, and buyer-stage questions.
- Track current visibility by model. Measure mention rate, average position, and sentiment for each prompt.
- Map the top recurring competitors. Your AI competitors may not match your SEO competitors.
- Log cited sources. If AI keeps citing the same domains, that is where authority is being assigned.
Without this baseline, it is hard to tell whether any change actually moved the needle.
Days 8-15: Fix trust and consistency gaps
AI recommendations are strongly influenced by external credibility signals.
Prioritize:
- Review quality and recency on sites like G2, Capterra, Trustpilot
- Consistent positioning across your website, social profiles, and third-party listings
- Clear category language so models can confidently place your brand
- Negative narrative cleanup on high-visibility pages AI is likely to reference
For many teams, this work drives faster gains than publishing another batch of blog posts.
Days 16-23: Publish citable assets
Now create content AI can confidently cite.
Focus on 2-3 assets:
- One original data piece with specific numbers
- One direct comparison page (balanced, not sales-only)
- One "best for" page for your highest-value use case
Write for citation and decision support:
- Answer the core question in the first paragraph
- Use specific, verifiable claims
- Keep structure scannable with question-based headings
If you need deeper guidance on content format, this complements our piece on how to create content AI recommends.
Days 24-30: Run a weekly optimization loop
From this point on, treat SEO for AI as a system:
- Review visibility and ranking changes by prompt and platform
- Identify biggest weekly drops and gains
- Compare what winning competitors improved
- Ship one focused update (content, reviews, PR, or positioning)
- Re-measure and repeat
Run this loop weekly. AI recommendation patterns can shift quickly.
The 5 metrics that actually matter
Track these weekly:
- Mention rate - How often your brand appears
- Average position - Where you rank when mentioned
- AI share of voice - Your presence vs. competitors
- Sentiment score - Whether mentions help or hurt consideration
- Citation quality - Which sources AI trusts when discussing your category
Together, these five metrics give you an operating dashboard you can act on.
Keep SEO and AI connected
SEO still matters, and ranking well helps. It just does not guarantee recommendation visibility.
Use SEO to capture demand, then use SEO for AI to increase the odds that your brand is the one recommended.
If you want a conceptual breakdown first, read SEO for AI: What's Changed and What Hasn't. If you want execution, run this 30-day cycle and iterate every week.
OakData gives you the full loop in one place: prompt tracking, multi-model visibility, competitor benchmarking, sentiment, citations, and alerts.