Long-tail phrasings of one keyword
keyword_suggestions is a $0.20 GET request on the Wuthering AI API. Find the longer, more specific phrases built around a single term. It answers complete JSON, and a call that fails is not charged.
Endpoint
GET /v1/keyword_suggestions
Price per successful call
$0.20
Failed calls
Not charged
curl 'https://wutheringai.com/v1/keyword_suggestions?keyword=…&token=YOUR_TOKEN'
What does keyword_suggestions return, and when should you call it?
Take one keyword and return longer search phrases that contain it, with volume and competition for each.
This is full-text expansion of ONE term, so every result contains your keyword. It is narrower than wuthering_keyword_ideas, which returns semantically related terms that may share no words with the seed.
Returns: keyword, search_volume, cpc, competition_level, keyword_difficulty.
Use when a head term is too broad and you need the specific questions underneath it. Don't use to explore a category from scratch.
What parameters does keyword_suggestions take?
keyword_suggestions accepts 5 parameters, of which 1 is required. Array values are comma-separated on the query string.
| Parameter | Type | Required | Description |
|---|---|---|---|
| keyword | string | yes | The single seed keyword to expand. |
| location_code | number | no | Numeric location code to scope results to. Defaults to 2840 (United States). Search volume and competition vary sharply by country, so set this when the question is about a specific market.Defaults to 2840 |
| language_code | string | no | ISO language code for results, for example 'en' or 'de'. Defaults to 'en'.Defaults to en |
| limit | number | no | Maximum rows to return (1 to 1000, default 100). Ask for the fewest that answer the question: every row is billed and spends the caller's context.Defaults to 100 |
| offset | number | no | Rows to skip before returning results. Use with limit to page through a large set.Defaults to 0 |
Which playbooks call keyword_suggestions?
4 of the research playbooks name keyword_suggestions in their method. Each is free to read and says where in the sequence the call belongs.
- Is there real demand for this?Test an idea against the cheapest evidence that could kill it — search demand, sustained ad spend, posted salaries, and the words buyers use — and return a verdict with the number that decides it.
- What do we charge, and does the money work?Anchor price against what competitors actually charge and meter on, size willingness to pay from what the problem costs today, then run CAC, LTV and payback across three scenarios.
- What should we build next?Gather the language of people switching into and out of this category, code every quote to the force that drives it, size each theme against real search demand, and return a 50/50 roadmap.
- What would prove us wrong?Turn a belief the plan depends on into an explanation that cannot be bent to fit any result, name the rival explanations that would produce the same evidence, and pay only for the observations that would come out differently under each.
Reference for keyword_suggestions · last updated · published by Wuthering AI