Walmart Keyword Suggest Scraper

What does Walmart Keyword Suggest Scraper do?

Walmart Keyword Suggest Scraper expands seed terms into ranked suggestions returned by Walmart's public typeahead services. It supports Walmart Canada (CA, the default) and Walmart US (US), records the exact source URL and market, and reports blocked, malformed, unavailable, or empty responses in logs and OUTPUT metadata.

The Actor uses ordinary public HTTP requests with a transparent user agent. It does not log in, use cookies or private headers, solve CAPTCHAs, bypass access controls, or fabricate suggestions.

Why use Walmart Keyword Suggest Scraper?

Use it for search-term research, catalog navigation, query expansion, autocomplete analysis, and content planning. Suggestions are deduplicated case-insensitively and ranked in the order returned by the source for each seed query.

What data can Walmart Keyword Suggest Scraper extract?

Group	Fields
Suggestion	query, suggestion, rank, suggestionType
Source	market, source, sourceUrl, sourceTransport, extractionMethod
Contract	recordType, status, dataAvailable, provenance, scrapedAt
Run metadata	status, diagnosticCount, queryCount, completedAt

The dataset contains source-backed suggestions only. Source failures and empty responses are not suggestion rows and are reported separately in run metadata.

How to scrape Walmart keyword suggestions

1. Open the Input tab and choose CA or US.
2. Enter one query, or provide queries/searchTerms for a batch of up to 50 seed terms.
3. Set maxSuggestions for the total number of unique suggestions across the batch.
4. Start the Actor and inspect the dataset and the OUTPUT key-value record.

Canada requests use https://www.walmart.ca/typeahead/v3/complete?term=.... US requests use Walmart's public autocomplete route. An access boundary is reported in logs and run metadata rather than as a suggestion row.

How much will it cost to scrape Walmart keyword suggestions?

Apify bills the run according to the account and pricing configuration shown in the Console. Cost is driven primarily by the number of seed queries, request time, proxy/container resources, and stored output. Keep the query list and maxSuggestions bounded; direct requests are used by default and each seed has at most one bounded retry.

Input

The following settings are supported:

• market: CA or US; defaults to CA.
• query: one non-empty seed term, up to 180 characters; defaults to phone.
• queries: an array of up to 50 non-empty seed terms. It takes precedence over searchTerms when non-empty.
• searchTerms: compatibility alias for queries, up to 50 terms.
• maxSuggestions: total unique suggestions across all seeds, from 1 to 1,000; defaults to 1,000.
• timeoutMs: per-request timeout from 10,000 to 120,000 milliseconds; defaults to 30,000.
• proxyConfiguration: optional ordinary Apify Proxy settings. Proxy use is not an access-control bypass.

One seed query

{
  "market": "CA",
  "query": "phone",
  "maxSuggestions": 10,
  "timeoutMs": 30000
}

Batch query expansion

{
  "market": "CA",
  "queries": ["phone", "wireless headphones"],
  "maxSuggestions": 100,
  "timeoutMs": 30000,
  "proxyConfiguration": { "useApifyProxy": false }
}

Output

You can download the dataset in various formats such as JSON, HTML, CSV, or Excel.

Suggestion row

{
  "recordType": "suggestion",
  "status": "success",
  "dataAvailable": true,
  "source": "walmart_ca_typeahead_v3",
  "provenance": {
    "market": "CA",
    "query": "phone",
    "rank": 1,
    "sourceUrl": "https://www.walmart.ca/typeahead/v3/complete?term=phone"
  },
  "sourceTransport": "got_scraping_direct",
  "extractionMethod": "json_typeahead_queries",
  "market": "CA",
  "query": "phone",
  "suggestion": "phone case",
  "rank": 1,
  "suggestionType": "QUERY",
  "sourceUrl": "https://www.walmart.ca/typeahead/v3/complete?term=phone",
  "scrapedAt": "2026-09-08T12:00:00.000Z"
}

The OUTPUT key-value record contains status, recordCount, suggestionCount, diagnosticCount, queryCount, and completedAt. Failure details are written to actor logs. Only source-backed suggestions are written to the dataset.

Tips and advanced options

Start with one Canadian query and a small limit. Batch queries when you need comparable expansion, but remember that maxSuggestions is global rather than per query. Preserve provenance and sourceUrl when storing results. If a run returns no suggestions, check its status, diagnostic count, and market before retrying; changing markets may change the public endpoint, but the Actor never attempts to defeat a challenge.

FAQ, support, and responsible use

If a query returns no suggestion rows, inspect the status and diagnostic count in OUTPUT, then use the run logs to distinguish empty results from an access boundary, malformed response, or request failure. For support, use the Actor Issues tab or API tab and include the run ID, market, sanitized input shape, and summary counts. Do not submit credentials, cookies, private headers, or personal data.

This Actor is not affiliated with Walmart. It reads only public autocomplete responses and does not access private user information, authenticate, solve CAPTCHAs, or bypass access controls. Follow Walmart's terms, robots guidance, rate limits, applicable law, and privacy obligations.

Local verification

Run npm test, npm run lint, npm run schema, apify run --purge --input-file qa-input-278.json, and npm run validate. The checked-in QA input exercises the public Canada endpoint; live source behavior can change, and diagnostic counts are reported in OUTPUT while details remain in logs without adding non-suggestion dataset rows.