# Walmart Product Result & Availability Signal Monitor (`glowing_glove/walmart-product-price-stock-monitor`) Actor Find Walmart product result signals, item matches, fulfillment language when visible, and retail evidence links for competitor research. - **URL**: https://apify.com/glowing\_glove/walmart-product-price-stock-monitor.md - **Developed by:** [Ushba Khan](https://apify.com/glowing_glove) (community) - **Categories:** E-commerce, Automation, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $17.00 / 1,000 monitored walmart keywords This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Walmart Product Result & Availability Signal Monitor Find Walmart product result signals, item matches, fulfillment language when visible, and retail evidence links for competitor research. ### Why use this actor? This actor monitors Walmart product result signals for retail intelligence and arbitrage research. It returns monitored item signals and product evidence links. Fulfillment hints are included when they are visible in the public result context. ### Best for - Track competitor product results - Find retail product matches - Monitor merchandising language - Research arbitrage ideas ### Input Use `walmartKeywords` with focused values that match this actor's purpose. Use retail product keywords such as `air purifier`, `car vacuum`, or `protein powder`. Good example inputs: - `air purifier` - `car vacuum` For larger Walmart monitoring, use product categories that share the same buyer or price range. ### Output you get The dataset is intentionally compact and designed around this actor's actual buyer workflow. The most important fields are: - `retailSignalLevel` - `walmartItemSignals` - `marketUse` Rows return retail signal level and Walmart item signals with evidence links for product-result validation. ### Practical workflow 1. Run product keywords. 2. Review retail signal level and item matches. 3. Open item evidence for promising products. 4. Track repeat runs for competitor movement. ### Notes - Uses Walmart product search and item result pages; exact price and local stock can vary by store, region, and bot-wall behavior. # Actor input Schema ## `walmartKeywords` (type: `array`): Walmart Product Result & Availability Signal Monitor accepts focused inputs for this actor's exact job. Add up to 20 values. Good examples: air purifier, car vacuum. ## `maxItems` (type: `integer`): Maximum top links/items included inside each result row. ## `requestTimeoutSecs` (type: `integer`): Timeout for each public source request in seconds. ## `maxConcurrency` (type: `integer`): How many inputs to process at the same time. ## `proxyConfiguration` (type: `object`): Optional Apify Proxy for websites that limit cloud traffic. ## Actor input object example ```json { "walmartKeywords": [ "air purifier", "car vacuum" ], "maxItems": 10, "requestTimeoutSecs": 20, "maxConcurrency": 4, "proxyConfiguration": { "useApifyProxy": false } } ```` # Actor output Schema ## `results` (type: `string`): No description ## `summary` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "walmartKeywords": [ "air purifier", "car vacuum" ] }; // Run the Actor and wait for it to finish const run = await client.actor("glowing_glove/walmart-product-price-stock-monitor").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "walmartKeywords": [ "air purifier", "car vacuum", ] } # Run the Actor and wait for it to finish run = client.actor("glowing_glove/walmart-product-price-stock-monitor").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "walmartKeywords": [ "air purifier", "car vacuum" ] }' | apify call glowing_glove/walmart-product-price-stock-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=glowing_glove/walmart-product-price-stock-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Walmart Product Result & Availability Signal Monitor", "description": "Find Walmart product result signals, item matches, fulfillment language when visible, and retail evidence links for competitor research.", "version": "1.0", "x-build-id": "Qq0PRnNKrO3VqizWY" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/glowing_glove~walmart-product-price-stock-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-glowing_glove-walmart-product-price-stock-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/glowing_glove~walmart-product-price-stock-monitor/runs": { "post": { "operationId": "runs-sync-glowing_glove-walmart-product-price-stock-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/glowing_glove~walmart-product-price-stock-monitor/run-sync": { "post": { "operationId": "run-sync-glowing_glove-walmart-product-price-stock-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "walmartKeywords" ], "properties": { "walmartKeywords": { "title": "Product keywords", "type": "array", "description": "Walmart Product Result & Availability Signal Monitor accepts focused inputs for this actor's exact job. Add up to 20 values. Good examples: air purifier, car vacuum.", "items": { "type": "string" } }, "maxItems": { "title": "Max items per row", "minimum": 1, "maximum": 30, "type": "integer", "description": "Maximum top links/items included inside each result row.", "default": 10 }, "requestTimeoutSecs": { "title": "Request timeout", "minimum": 5, "maximum": 90, "type": "integer", "description": "Timeout for each public source request in seconds.", "default": 20 }, "maxConcurrency": { "title": "Concurrency", "minimum": 1, "maximum": 8, "type": "integer", "description": "How many inputs to process at the same time.", "default": 4 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional Apify Proxy for websites that limit cloud traffic.", "default": { "useApifyProxy": false } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```