1. The problem with keyword-first SEO

Traditional SEO workflows start with a spreadsheet full of keywords, volumes and difficulty scores. Teams then assign articles or landing pages to those keywords and hope that traffic equals revenue.

The issue is simple: buyers don’t think in exact-match phrases. They think in messy, contextual language – especially in AI, SaaS, and compliance categories where solutions are not obvious.

2. Thinking in intents, not phrases

Intent is what the user is trying to achieve when they type, tap or speak a query. “AI product search that understands natural language” and “retail semantic search engine” are different strings, but the underlying intent is almost identical.

  • Problem intent – “why”, “how”, “what is” style queries.
  • Solution intent – comparisons, alternatives, use-cases.
  • Execution intent – templates, checklists, implementation details.

3. Designing an intent map for your product

Start from your product’s value pillars, then map intents to each pillar. For GenAIEmbed, for example, one pillar is semantic discovery. Intents around that include:

  • “How do I make my ecommerce search understand natural language?”
  • “Examples of AI search for fashion catalogues”.
  • “Product discovery vs search in retail”.

Each of these should map to a small cluster of assets: one flagship article, one supporting how-to, one product-centred explainer, and ideally a case study.

4. How AI models help – and where they don’t

Embedding models are excellent at clustering queries into intent buckets. They allow you to see that “winter office jacket” and “cozy blazer for cold AC” are part of the same need.

What models cannot do for you is decide which intents matter to your business and how to shape your product narrative around them. That still requires humans who understand the market, pricing, and sales motion.

5. What this changes for your roadmap

When you shift from keyword lists to intent maps, content stops being random blog posts and starts behaving like product surface area. You can answer real jobs-to-be-done, link those answers to product capabilities, and measure impact in pipeline – not just visitors.

The practical next step: audit your current content by intent, not by topic, and notice where your best intents have zero deep assets. That’s where the next sprint lives.