Choosing Keywords

Keywords are the foundation of your GSEO analysis. They determine what questions EYE asks AI platforms about your brand and category. Choosing the right keywords is critical for getting actionable insights.

How Keywords Work

EYE takes your keywords and uses them to generate hundreds of prompts that simulate how real users query AI platforms. For example, the keyword "CRM for agencies" might generate prompts like:

• "What's the best CRM for a marketing agency?"
• "Compare CRM platforms for small teams"
• "Which CRM do agency owners recommend?"
• "Affordable CRM options for freelancers"
• "Is HubSpot better than Pipedrive for agencies?"

The same logic applies to any industry — "immune health supplements", "travel insurance", "sustainable clothing", "robo-advisors", and so on.

The more relevant your keywords, the more accurate your GSEO Score and competitive analysis will be.

Keyword Strategy

Category Keywords

Broad terms that describe your product category. These capture how AI platforms perceive the overall market.

Examples (SaaS): "CRM software", "project management tool", "HR software for small business"

Examples (Healthcare): "immune health supplements", "probiotic brands", "magnesium supplements"

Examples (Finance): "robo-advisor", "travel insurance", "high-yield savings account"

Feature Keywords

Specific features or benefits that differentiate your product. These reveal whether AI platforms associate your brand with key selling points.

Examples (SaaS): "CRM with built-in email automation", "AI-powered project management", "HR software with payroll integration"

Examples (Healthcare): "third-party tested supplements", "vegan protein powder", "sugar-free probiotics"

Use Case Keywords

How people describe their needs in your industry. These simulate real decision-intent queries.

Examples (SaaS): "CRM for remote marketing teams", "project management for agencies"

Examples (Retail): "sustainable activewear for women", "affordable luxury skincare"

Examples (Finance): "travel insurance for families", "robo-advisor for beginners"

Comparison Keywords

Terms that trigger head-to-head comparisons between brands.

Examples (SaaS): "HubSpot vs Pipedrive", "Notion vs Asana for teams", "Salesforce vs HubSpot for SMBs"

Examples (Healthcare): "Athletic Greens vs Ritual", "Hims vs Roman for hair loss"

Examples (Finance): "Betterment vs Wealthfront", "Navan vs Concur for corporate travel"

Problem Keywords

Terms describing problems your product solves. These capture high-intent queries.

Examples (SaaS): "how to manage client relationships at scale", "team productivity bottlenecks"

Examples (Healthcare): "low energy and fatigue supplements", "gut health issues remedies"

Examples (Retail): "clothes that last longer", "ethical fashion brands"

Best Practices

• Think like your customer — Use the language your customers use, not your internal jargon
• Mix broad and specific — Include both category-level and feature-level keywords
• Include competitor names — Keywords like "HubSpot vs Pipedrive" or "Athletic Greens vs Ritual" trigger comparison queries that reveal competitive positioning
• Cover the journey — Include awareness keywords ("what is..."), consideration keywords ("best..."), and decision keywords ("which...", "compare...", "price...")
• Use natural language — AI users tend to ask full questions, not type short keywords like in Google
• Localize — If you're analyzing a non-English market, use keywords in the target language

Keywords to Avoid

• Too generic — "software" alone is too broad; "CRM for agencies" is better
• Too niche — A specific SKU or internal product code is too specific for AI queries
• Internal terms — Avoid product codes, internal naming conventions, or jargon your customers don't use
• Irrelevant categories — Stay focused on your actual product category and buyer intent