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Research

Demand research that blends real search data with a language model into about 32 candidate prompts, plus a Search Console striking-distance block.

You can only track the questions you thought of. Research finds the rest. It mixes real search-demand data with a language model into about 32 new questions worth tracking: at least 80% unbranded, grouped into 6 to 8 themes, dropped into your suggestion queue for review. It also shows your striking-distance pages, the searches where you rank just off the first screen and a small push could break you through.

What it does

It finds trackable questions you have not thought of, grounded in real demand rather than guesswork. It also points you at searches where you are close to breaking through.

How to use it

Open Research:

  • Generate candidates. Send them to the suggestion queue, or straight to tracking.
  • Read the striking-distance list. These are queries ranked 8 to 20 in Search Console with impressions above zero. You see the top 12 by impressions.

How it's computed

A fail-open relevance filter trims off-topic candidates. If it cannot run, it keeps them rather than dropping good ideas in silence.

Per-prompt volumes use a long-tail decay model and read as about asks/month, never as an exact figure. AI-search demand cannot be measured to the unit. See data honesty.

The striking-distance tile has no sparkline. It is defined over a 28-day aggregate, and there is no honest daily series to draw.

Limits

Striking distance needs a connected Search Console. Volume estimates need DataForSEO credentials. Without them, volumes fall back to honest bands instead of invented numbers.

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