Keyword Question Finder — AnswerThePublic Alternative

Find keyword questions and related searches using Google autocomplete. Submit seed phrases and research patterns, then export ordered suggestions with source queries, country, language, and collection time. For content researchers, each dataset record is a completed autocomplete source query with its ordered suggestions.

Workflow: put the results to work

Choose seed phrases and the question patterns your audience might use. Keep country and language aligned with the intended readers. Group the returned suggestions into research themes; autocomplete order is observed source data, not a search-volume or keyword-difficulty estimate.

Best fit and focused standalone workflow

Choose this Actor when you need current, machine-readable search-question discovery that can feed an editorial brief, content gap list, landing-page outline, or a downstream keyword-metrics workflow. It works well for a specific seed, locale, and research category when an API or dataset is more useful than a visual research interface.

This Actor is designed as a focused standalone workflow. A practical flow starts with a seed such as shopify seo, then expands it into selected Google autocomplete patterns, reviews the returned dataset, and passes the shortlist to a separate tool for search volume, CPC, SERP, or rank validation if those metrics are needed.

It deliberately does not replace a broader research suite's saved history, alerts, visual wheels, team workspace, content studio, search-volume, CPC, or trend-comparison features.

Quick start

{
  "seedKeywords": ["content marketing"],
  "researchTypes": ["questions", "comparisons", "prepositions", "alphabeticals", "numbers", "related"],
  "language": "en",
  "country": "US",
  "maxSourceQueries": 60,
  "maxSuggestionsPerQuery": 10
}

Use fewer categories or a lower maxSourceQueries value for a smaller, cheaper research pass. The full six-category plan creates up to 58 source queries for one seed; the cap always stops expansion predictably.

What the Actor does

Category	Lookup pattern	Why it is useful
Related	seed	Captures the current direct autocomplete context for the seed.
Questions	how seed, what seed, and similar forms	Finds question-led content and FAQ angles.
Comparisons	seed vs, seed or, seed and	Finds comparison and alternative-intent phrases.
Prepositions	seed for, seed with, and similar forms	Finds use-case and relationship modifiers.
Alphabeticals	seed a through seed z	Broadens long-tail discovery with a bounded A-Z plan.
Numbers	seed 0 through seed 9	Finds number-led modifiers when the live source offers them.

The source returns autocomplete predictions, not search-volume, CPC, keyword difficulty, rankings, traffic, conversion, or audience estimates.

Output contract

Each dataset item is one completed source-query snapshot. suggestions is an ordered, de-duplicated array from that one request; an empty array is a valid result and is recorded truthfully.

Field	Meaning
seedKeyword	The original phrase that started the research branch.
researchType and variant	The category and exact pattern used to build the source query.
query and queryOrder	The exact autocomplete phrase and its bounded plan position.
suggestions and suggestionCount	Ordered predictions retained for that one source query.
language and country	Source hints that scoped the request.
sourceUrl, sourceEndpoint, and collectedAt	Provenance for rechecking a live, changeable source.

{
  "runId": "abc123",
  "seedKeyword": "content marketing",
  "researchType": "questions",
  "variant": "how",
  "query": "how content marketing",
  "queryOrder": 2,
  "language": "en",
  "country": "US",
  "suggestions": ["how content marketing works", "how content marketing helps businesses"],
  "suggestionCount": 2,
  "provider": "Google Search autocomplete",
  "sourceEndpoint": "suggestqueries.google.com",
  "sourceUrl": "https://suggestqueries.google.com/complete/search?client=firefox&hl=en&gl=US&q=how+content+marketing",
  "collectedAt": "2026-09-07T10:00:00.000Z"
}

Every terminal run also writes OUTPUT and RUN_SUMMARY. Outcomes are COMPLETE, PARTIAL, VALID_EMPTY, INVALID_INPUT, UPSTREAM_FAILED, or CONFIG_ERROR; use the terminal record before continuing an automated workflow.

{
  "outcome": "COMPLETE",
  "sourceQueriesRequested": 58,
  "sourceQueriesCompleted": 58,
  "sourceQueriesFailed": 0,
  "itemsPushed": 58,
  "suggestionsReturned": 421,
  "warnings": []
}

API example

curl -X POST "https://api.apify.com/v2/acts/khadinakbar~answerthepublic-alternative/runs" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "seedKeywords": ["shopify seo"],
    "researchTypes": ["questions", "comparisons", "related"],
    "language": "en",
    "country": "US",
    "maxSourceQueries": 16,
    "maxSuggestionsPerQuery": 10
  }'

Read the run's default dataset for the snapshots, then read OUTPUT and RUN_SUMMARY from its default key-value store before using the results downstream.

How this workflow compares with AnswerThePublic

Decision	This Actor	AnswerThePublic
Scope and workflow	Covers a bounded Google-autocomplete discovery workflow across six explicit category patterns.	A broader research suite can cover dashboard-oriented workflows beyond this focused API dataset.
Input friction	Uses seed phrases, locale hints, selected categories, and query caps in a single run.	Use the incumbent when you prefer its broader product workflow and workspace experience.
Output contract	Returns one source-provenanced dataset row per completed query, plus terminal OUTPUT and RUN_SUMMARY records.	Use the incumbent when its product-specific visual or export workflow is a better fit.
Automation and integrations	Provides an Apify API run and dataset readback for this bounded workflow; no named client integration is claimed here.	Use the incumbent when its documented suite integrations or alert workflow are required.
Freshness and provenance	Each row includes the direct source URL and collection timestamp for a live, changing autocomplete response.	Choose the incumbent when its history, comparison-over-time, or reporting features are the deciding requirement.
Billing, cost, and effective efficiency	The Actor is Pay per event with an explicit source-query cap; a same-job cost or effective-efficiency comparison is not claimed without current, matched evidence.	The incumbent lists subscription plans and search allowances that should be checked against the exact workload.

The comparison is about this specific search-question discovery workflow, not a claim of full-suite parity or a universal recommendation.

Best-results guidance

Use a specific seed and country/language pair, then validate promising suggestions with your own demand, SERP, and business-context data before publishing content. Autocomplete is live and can change between runs; retain sourceUrl and collectedAt whenever decisions need a recheck.

If a run is PARTIAL, reuse the same bounded input after checking RUN_SUMMARY; the record lists the source queries that need another collection attempt. If a valid input finishes VALID_EMPTY, try a more natural seed phrase or a different locale to broaden the live autocomplete context.

AI agent and MCP handoff

An AI agent can use this Actor as a research step, provided it reads the terminal records rather than assuming a successful HTTP request means useful data.

Run the Actor for shopify seo in US English, extract the question and comparison suggestions from the dataset, confirm OUTPUT.outcome, then pass only source-provenanced phrases to the next validation step.

The Actor makes read-only autocomplete requests and produces a dataset plus terminal outcome records. It does not write to search engines, publish content, or change external accounts.

Builder's note

I built this Actor to make the useful part of question-led autocomplete research repeatable in a small, explicit API workflow: a seed, a bounded expansion plan, and an output that keeps the source and collection time beside the suggestions. My goal is to make it easy to inspect what was actually queried before a team treats a phrase as an SEO decision.

Responsible use

Use the Actor only for research you are authorized to perform and in compliance with applicable laws and site terms. Google autocomplete responses are a live public-source observation, not a license to infer private behavior or make claims about search demand.

Pricing and run costs

This Actor uses Pay per event plus Apify platform usage. The Pricing tab lists the current event rates and billing terms.

Event	Billing unit	When it applies
apify-actor-start	Actor Start	Charged when the Actor starts running. Number of events charged depends on Actor memory (one event per GB, minimum one event).
question-research-query	Question-research source query	One completed, validated, and persisted Google autocomplete source-query snapshot, including a valid empty suggestion list.

Run cost combines the charged events and Apify platform usage. Review the run charge limit and requested result count before starting.

Independent alternative

This Actor provides the specific workflow described above. It is not affiliated with or endorsed by AnswerThePublic; the named product and its trademarks belong to their respective owners.

Connect an AI agent

Use the Apify MCP configurator to choose an available client connection. Inspect this Actor’s current input schema and required credentials before running it.