Shopsy Product Scraper with Seller

🛍️ Shopsy Product Scraper

🚀 Turn Shopsy product listings into structured, analysis-readye-commerce intelligence.

A powerful Apify Actor for collecting structured product data fromShopsy search results. Built for e-commerce research, competitoranalysis, price monitoring, catalog building, product discovery, andtrend analysis.

✨ What This Actor Does

Simply enter a Shopsy search keyword and choose how many productsyou want to collect. The Actor automatically:

🔎 Searches Shopsy using your keyword📦 Collects product information🧹 Normalizes and deduplicates product records🏪 Optionally enriches products with seller information📊 Pushes structured records to an Apify Dataset📁 Optionally generates CSV and Excel exports

The scraper uses paginated requests and dynamically calculates the pagesrequired for the requested product count.

🌟 Key Features

Feature Description

🔎 Keyword Search Scrape products using any Shopsysearch keyword

📦 Product Data Collect detailed productinformation

💰 Price Tracking Current price, MRP and discountpercentage

⭐ Ratings Rating, rating count and reviewcount

🏷️ Product Details Title, subtitle, brand andsize/variant

🖼️ Images Product image URL and image count

🏪 Seller Intelligence Optional seller enrichment

📊 Excel Export Generate .xlsx files

📄 CSV Export Generate .csv files

🚀 Scalable Configurable product limits

⚡ Concurrency Control Control seller-detail requestconcurrency

📍 Pincode Support Location-aware requests

☁️ Apify Dataset Ready-to-use structured datasetoutput

🔄 Retry Handling Handles retryable outbound requests

🎯 Perfect For

💼 Competitor ResearchCompare products, prices, brands and sellers.

📈 Market ResearchBuild datasets for understanding e-commerce markets and productcategories.

💰 Price & Discount AnalysisCollect current prices, MRP and discount information for analysis.

🛒 Product DiscoveryDiscover products and build structured product catalogs.

🏪 Seller AnalysisCollect available seller information and seller-quality metrics.

📊 Trend AnalysisCreate datasets for product and marketplace trend research.

🤖 Data & ML ProjectsUse structured product records as input for analytics, dashboards andmachine-learning workflows.

⚙️ Input Configuration

The Actor accepts the following inputs:

Input Type Default Description

🔍 keyword String jacket Shopsy searchkeyword

📦 maxItems Integer 500 Maximum productsto collect

🏪 Boolean true EnableincludeSellerDetails seller-detailenrichment

📍 pincode String 110001 Pincode used forlocation-awarerequests

📄 exportCSV Boolean false Generate CSVexport

📊 exportExcel Boolean true Generate Excelexport

📌 Input Limits

maxItems: 1--20,000

sellerConcurrency: 1--50

These inputs are defined in:

.actor/input_schema.json

🧪 Example Input

{ "keyword": "jacket", "maxItems": 100, "includeSellerDetails": true, "pincode": "110001", "exportCSV": false, "exportExcel": true, "sellerConcurrency": 10 }

💡 Recommended First Test

For your first run, start small:

{ "keyword": "jacket", "maxItems": 10, "includeSellerDetails": true, "pincode": "110001", "exportCSV": false, "exportExcel": true, "sellerConcurrency": 5 }

✅ Verify the Dataset and exports before increasing the product limit.

📦 Output Data

The Actor pushes normalized product records to the Apify Dataset.

🛍️ Product Fields

productId itemId listingId title subtitle size brand currentPrice mrp discountPercentage rating ratingCount reviewCount imageUrl numberOfImages productUrl availability vertical

🏪 Seller Fields

When seller enrichment is enabled, the following fields may beavailable:

sellerName sellerScore sellerDescription sellerSince productQuality serviceQuality

ℹ️ Seller information is best-effort. Some Shopsy products may notexpose seller information.

📊 Excel & CSV Exports

When enabled, the Actor creates exports in the run's Key-ValueStore.

For example:

jacket_products.xlsx jacket_products.csv

📊 Excel Workbook

The Excel workbook contains:

🛍️ Products --- normalized product records

📈 Summary --- high-level scraping and product statistics

The Summary can include:

Total products

Average price

Minimum price

Maximum price

Average rating

Average discount

Seller-enrichment statistics

🏪 Seller Enrichment

Enable seller enrichment with:

"includeSellerDetails": true

The Actor identifies seller references and fetches available sellerinformation.

You can control the number of concurrent seller/detail requests with:

"sellerConcurrency": 10

⚡ Concurrency Guidance

Concurrency Recommended Use

`1–5` 🐢 Conservative / testing
 `5–10` ⚖️ Recommended starting range
`10–25` 🚀 Higher throughput
`25–50` ⚠️ Use carefully and monitor requests

A lower value can reduce request pressure, while a higher value canimprove throughput depending on the target and proxy capacity.

🧹 Data Quality

The Actor normalizes raw Shopsy product objects into a consistentstructure.

✅ Data-quality behavior

Duplicate products are removed using productId.

Invalid product payloads are skipped.

Missing source data is represented as an empty/null value.

The scraper does not fabricate missing product information.

Some products may naturally have missing ratings, reviews,subtitles, images or seller information.

🚀 Running the Actor

☁️ Run on Apify

Open the Actor in Apify Console.

Enter your desired inputs.

Click Start.

Monitor the run logs.

Open the Dataset to inspect structured records.

Download generated exports from the run's Key-Value Store.

💻 Run Locally

Install dependencies:

npm install

Run the Actor:

node src/main.js

🚀 Deploy to Apify

From the project root:

apify login apify push

The project uses:

.actor/ ├── actor.json └── input_schema.json

for Actor configuration and input definition.

🗂️ Project Structure

shopsy-product-dataset/ │ ├── .actor/ │ ├── actor.json │ └── input_schema.json │ ├── src/ │ ├── main.js │ ├── normalize.js │ ├── search.js │ ├── export.js │ ├── crawler.js │ ├── headers.js │ └── retry.js │ ├── package.json ├── package-lock.json ├── dockerfile └── README.md

🧪 Recommended Workflow

1️⃣ Start Small

Use:

{ "keyword": "jacket", "maxItems": 10, "includeSellerDetails": true, "pincode": "110001", "exportCSV": false, "exportExcel": true, "sellerConcurrency": 5 }

2️⃣ Check Your Dataset

Verify:

✅ Product count✅ Product IDs✅ Prices✅ Titles & subtitles✅ Ratings✅ Seller information

3️⃣ Check Your Excel Export

Verify that the generated workbook contains the expected product andseller columns.

4️⃣ Scale Up 🚀

Once the small run works correctly, increase:

maxItems sellerConcurrency

according to your requirements.

🛡️ Responsible Use

Please use this Actor responsibly and respect Shopsy's applicableterms, policies, access restrictions and rate limits, as well asapplicable laws and regulations.

Do not use collected data in ways that violate contractual restrictions,privacy requirements, intellectual-property rights, or applicable law.

❓ Frequently Asked Questions

❓ What is the Shopsy Product Scraper?

It is an Apify Actor that collects structured product information fromShopsy search results and stores the normalized records in an ApifyDataset.

❓ What do I need to provide?

At minimum, provide a search keyword and maxItems. The othersettings control seller enrichment, exports, pincode and concurrency.

❓ Can I scrape different product categories?

Yes. Enter the desired search term in keyword, such as:

jacket kurti shoes t-shirt saree backpack

❓ Can I collect seller information?

Yes. Set:

"includeSellerDetails": true

Seller information is best-effort and may not be available for everyproduct.

❓ Can I export the results to Excel?

Yes. Set:

"exportExcel": true

The .xlsx file is generated in the run's Key-Value Store.

❓ Can I export CSV?

Yes. Set:

"exportCSV": true

❓ Where can I find the scraped data?

The normalized product records are available in the Actor's ApifyDataset. Generated Excel and CSV files are available through the run'sKey-Value Store when enabled.

❓ Why are some fields empty?

Shopsy may not provide every field for every listing. Missing sourceinformation is left empty/null rather than being guessed or fabricated.

❓ Why is my seller information missing for some products?

Seller enrichment is best-effort. Some products may not expose sellerreferences or complete seller information, and individual requests mayfail or return incomplete data.

❓ What does sellerConcurrency control?

It controls how many seller/product-detail requests can runconcurrently.

For initial testing, 5 is a good starting point.

❓ How many products can I request?

The current input schema allows:

1–20,000 products

For large jobs, start with a smaller test and scale gradually.

❓ Can I run the Actor locally?

Yes:

npm install node src/main.js

❓ How do I deploy updates?

From the project directory:

apify push

Apify will build and deploy the updated Actor version.

❓ Does the Actor automatically create an Excel file?

Only when:

"exportExcel": true

The current default is true.

❓ Does the Actor automatically create a CSV file?

Only when:

"exportCSV": true

The current default is false.

❓ Is proxy configuration supported?

The Actor is designed to work with Apify-compatible proxy configuration.For production-scale scraping, configure proxy usage appropriately inyour Apify environment and monitor request success rates.

💬 Need Help?

If a run fails:

🔍 Check the Actor Run Log.

📋 Copy the relevant error message.

⚙️ Note the input configuration used.

📊 Check whether partial Dataset data was produced.

🐛 Reproduce the issue with a small maxItems value.

Providing the run ID, input, error message and affected output fieldmakes troubleshooting much faster.

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🛍️ Turn Shopsy Listings Into E-Commerce Intelligence 🚀

Search → Scrape → Normalize → Enrich → Analyze 📊

⭐ Happy Scraping! ⭐