Choosing relevant Search Terms
Last updated: April 2, 2026
This article helps you think strategically about which search terms to track and gives you concrete categories to work from.
Why It Matters
Every search term you add to a brand uses credits each time it is tracked across your selected AI engines. Choosing your search terms thoughtfully means you spend credits on the queries that actually reflect how your customers search - giving you actionable data rather than noise.
Think Like Your Customer
The best starting point is to ask: what would someone type into an AI search engine when they are looking for a product or service like yours? AI search queries tend to be more conversational and specific than traditional Google searches. Instead of "CRM software," a user might ask "What is the best CRM for small sales teams?"
Focus on the questions and phrases your ideal customers would actually use, not on internal terminology or product feature names.
Categories of Search Terms to Cover
A strong set of search terms typically includes a mix of the following categories:
Branded queries — Queries that mention your company or product by name. These help you understand how AI engines represent your brand when someone asks about you directly. Examples: "What is [Your Brand]?" or "[Your Brand] reviews."
Competitor queries — Queries that mention your competitors by name. Tracking these shows you whether your brand appears in responses about competitors and how you are positioned in comparison. Examples: "Best alternatives to [Competitor]" or "[Competitor] vs [Your Brand]."
Generic category queries — Broad queries about your product category or industry without mentioning any brand. These reveal whether AI engines recommend your brand when someone is exploring their options. Examples: "Best project management tools for remote teams" or "How do I choose an email marketing platform?"
Use-case and problem-based queries — Queries framed around a specific problem or goal rather than a category. These often reflect where a customer is early in their research. Examples: "How do I improve my team's productivity?" or "What tools help with customer retention?"
Comparison and listicle queries — Queries that ask for rankings, lists, or head-to-head comparisons. AI engines frequently generate structured responses for these. Examples: "Top 10 analytics platforms in 2026" or "Compare [Brand A] and [Brand B] for enterprise use."
Tip: Start Focused, Then Expand - You do not need to track every possible query from day one. Start with a focused set, around 10 to 20 search terms, that covers your most important branded, competitor, and category queries. Review the results after a few tracking cycles, then add more terms based on what you learn.
If you notice a category where your brand consistently does not appear, that is a signal worth investigating further with additional, more specific search terms.
Use Automated Suggestions as a Starting Point
RankScale can suggest search terms automatically based on your brand and industry. These suggestions are a helpful starting point, especially when you are setting up a new brand. You can review and add them selectively. For details on how to use this feature, see 📄 Finding Search Terms.
Best-Practices for writing effective Prompts
Keep your prompts natural and conversational, write them the way a real person would ask a question. Avoid keyword-stuffed or unnatural phrasing. A prompt like "What is the best tool for managing social media content?" will produce more realistic results than "best social media management tool top ranked."
Consider adding variations of the same question. AI engines can give different responses depending on how a query is phrased, so tracking both "Best CRM for startups" and "What CRM should a startup use?" can reveal differences in how your brand is surfaced.