Building an Intelligent Cross-Platform Price Comparison System: Integrating Taobao, JD.com, and Pinduoduo Data Streams

1. Introduction

With the rapid growth of e-commerce, cross-platform price comparison has become an essential tool for business operations, user experience enhancement, and advertising optimization. By using a price comparison system, businesses can gain real-time insights into pricing differences across platforms, enabling precise marketing, supply chain adjustments, and even predictive modeling.

This article introduces how to integrate the official Taobao API and LuckData APIs for JD.com, Pinduoduo, Amazon, and more to build a scalable, stable price comparison system. We cover product matching strategies, API integration, data normalization, and visualization, accompanied by code examples and architecture design to help readers get started efficiently.

2. System Objectives and Architecture Overview

Objectives:

• Support keyword-based product searches across multiple platforms (Taobao, JD.com, Pinduoduo)

• Extract unified fields such as price, title, store name, and promotional details

• Sort and present product information in a standardized, visual format

• Ensure extensibility for additional platforms or functionalities in the future

Architecture Overview:

┌────────────────┐
│ User inputs keyword │
└────────────────┘
↓
┌────────────────────────────┐
│ Compare Service Layer      │
│  ┌──────────────┐         │
│  │ Taobao API   │         │
│  └──────────────┘         │
│  ┌──────────────┐         │
│  │ JD API (LuckData) │     │
│  └──────────────┘         │
│  ┌──────────────┐         │
│  │ Pinduoduo API (LuckData) │
│  └──────────────┘         │
└────────────────────────────┘
↓
Data merging / deduplication / price sorting
↓
Web frontend / API return

3. Product Matching Strategy

Because product IDs, URLs, and naming conventions vary by platform, accurate product matching is critical for comparison. The system adopts the following strategies to improve matching accuracy:

3.1 Keyword Matching and Chinese Word Segmentation

When users search for items like "iPhone 13 Pro 128G", the system queries each platform using its respective API, then analyzes the returned titles using Chinese word segmentation and semantic filtering to improve retrieval precision.

3.2 Specification Extraction and Standardization

To enable cross-platform comparison, product titles must be parsed to extract common attributes such as brand, model, and storage capacity.

import re
def extract_specs(title):
brand = re.search(r'(Apple|華為|小米|三星|OPPO)', title)
storage = re.search(r'(128G|256G|512G|1T)', title)
return (brand.group() if brand else ''), (storage.group() if storage else '')

This rule-based extraction helps match equivalent products despite differences in wording or order.

4. Taobao API Implementation: Keyword-Based Product Search

Taobao’s developer API allows keyword searches and returns essential fields such as title, price, item URL, and shop name.

def search_taobao(keyword):
return call_taobao('taobao.tbk.item.get', {
'q': keyword,
'fields': 'title,price,item_url,nick',
'adzone_id': 'your_pid',
'page_size': 10
})['tbk_item_get_response']['results']['n_tbk_item']

The API returns structured responses that can be directly used in the comparison process.

5. Integrating JD.com and Pinduoduo via LuckData

LuckData offers a unified data service for accessing platforms like JD.com, Pinduoduo, Amazon, and TikTok. This significantly reduces the cost of integration. You can retrieve data using simple RESTful requests:

import requests
HEADERS = {'X-Luckdata-Api-Key': 'your_luckdata_key'}
def search_luckdata(platform, keyword):
url = f"https://luckdata.io/api/{platform}/search"
params = {'keywords': keyword, 'count': 10}
resp = requests.get(url, headers=HEADERS, params=params)
return resp.json()['data']

Platform Codes:

• JD.com: jd-api/xxxx

• Pinduoduo: pdd-api/xxxx

• Taobao (fallback): taobao-api/xxxx

6. Unified Data Format and Price Sorting

To ensure consistent comparison and visualization, we standardize data fields returned from various platforms:

def normalize_item(source, item):
return {
'title': item['title'],
'price': float(item['price']),
'shop': item.get('nick') or item.get('shop_name'),
'url': item['item_url'],
'source': source
}
results = []
results += [normalize_item('taobao', i) for i in search_taobao('iPhone 13')]
results += [normalize_item('jd', i) for i in search_luckdata('jd-api/xxxx', 'iPhone 13')]
results += [normalize_item('pdd', i) for i in search_luckdata('pdd-api/xxxx', 'iPhone 13')]
sorted_results = sorted(results, key=lambda x: x['price'])

After normalization and sorting, the data is ready for display or API output.

7. Frontend Display Options (Optional)

To enhance user interaction and visualization, consider the following options:

• Use Pandas to display data tables

• Build interactive price comparison interfaces using Streamlit, Dash, or Flask

• Export results to HTML or Excel reports for marketing analysis

import pandas as pd
df = pd.DataFrame(sorted_results)
print(df[['source', 'title', 'price', 'shop']].head(10))

This can also be extended to chatbot applications or web widgets.

8. Advanced Optimization Strategies

To enhance performance and functionality, consider the following strategies:

• ✅ Price Monitoring and Alerts: Schedule daily data pulls and send alerts (via Telegram, LINE, etc.) if prices drop below predefined thresholds

• ✅ Asynchronous and Multi-threaded Requests: Use asyncio or concurrent.futures to speed up multi-platform data collection

• ✅ Data Caching: Use Redis or local storage to cache frequently searched keywords and avoid repeated API calls

9. Conclusion

This article presented a practical approach to building a cross-platform price comparison system using the official Taobao API and LuckData’s APIs for JD.com, Pinduoduo, Amazon, and more. With this setup, businesses can implement efficient, scalable solutions to support pricing analysis, promotional strategies, and automated monitoring.

As the system evolves, it can serve as the foundation for more advanced features like automated product recommendations and price trend forecasting—paving the way for truly intelligent commerce decision-making.

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• Integrating Taobao API and LuckData Scraping: Efficient Data Fusion Across E-Commerce Platforms

• NLP-Based Product Review Analysis: Mining User Sentiment and Keyword Hotspots

• Image Recognition and Reverse Image Search: Building an Intelligent Visual Matching System for Taobao Products

• Implementing a Recommendation System: Personalized Product Suggestions Using Taobao API and User Behavior

• Sales and Inventory Forecasting Practice: Time Series Modeling with Taobao API

• Building an Interactive Reporting and Visualization Platform: A Practical Guide to Unlocking the Value of Taobao Data

If you need the Taobao API, feel free to contact us : support@luckdata.com