Insights into Emerging Markets: Leveraging Social and E-commerce APIs to Track Consumption Trends in Lower-Tier Cities

From “Pinduoduo’s 10-Billion-Yuan Subsidy” to “Douyin Group Buys Reaching County-Level Markets,” lower-tier cities (tier-3 and below) have become the new growth frontier for brands. The rapid and fragmented consumer trends in these regions are difficult to capture using traditional methods. This article introduces how to utilize API tools from LuckData to conduct high-frequency monitoring, identify viral content, and analyze product conversion trends to help brands seize emerging opportunities.

Objectives

• Use Douyin API to extract trending videos from tier-3 and tier-4 cities to identify consumer content signals

• Integrate e-commerce data (Pinduoduo + Lazada) to analyze product sales trends

• Build a dashboard combining “city + product category + trend insights”

1. Key Features of Emerging Market Data

Compared to top-tier cities, consumer behavior, content preferences, and platform usage in lower-tier cities differ significantly:

These traits demand new approaches in product design, pricing strategy, and marketing pacing for brands targeting these regions.

2. Extracting City-Level Content Trends Using Douyin API

LuckData’s Douyin API allows filtering video hotlists by city, enabling rapid identification of local trending topics.

✅ Example API Endpoint (using city parameter):

GET https://luckdata.io/api/douyin-API/get_xv5p?
city=610100&          # Xi’an (tier-2 city)
type=rise_heat&
end_date=20241224&
page_size=10&
start_date=20241223

Using different city codes (e.g., Chongqing, Luoyang, Ganzhou, Yichang, Nanyang), users can retrieve localized hotlists to monitor regional content shifts.

✅ Example Python Script:

import requests
def get_city_douyin_hot(city_code):
url = "https://luckdata.io/api/douyin-API/get_xv5p"
params = {
"city": city_code,
"type": "rise_heat",
"start_date": "20241223",
"end_date": "20241224",
"page_size": 10
}
res = requests.get(url, params=params)
return res.json()["data"]
data = get_city_douyin_hot("511700")  # Suining
for video in data:
print(video["title"], video["like_count"], video["author_name"])

This API helps dynamically track hot content by city, offering early signals for marketing and product decisions.

3. Analyzing Product Sales with Pinduoduo Data

LuckData provides Pinduoduo sales data through sample fields or simulated inputs. These can be extended using crawlers or public rankings to model product trends.

Sample data format:

{
"title": "1.5L Automatic Thickened Glass Health Pot",
"price": 39.9,
"monthly_sales": 8523,
"area_trend": {
"Guilin, Guangxi": "High sales",
"Zunyi, Guizhou": "Continuous growth"
}
}

This structure allows for clustering of popular products by region and further validation of “content → conversion” effectiveness through Douyin signals.

4. Building a Viral Product Detection Model for Lower-Tier Markets

To effectively identify viral products in lower-tier markets, one can align content trends with product visibility, focusing on regional sales concentrations and price brackets.

✅ Step 1: Match Content Popularity with Product Exposure

Video Title: “Village Aunt Makes Corn Crackers, Everyone Wants Some”
→ Matched Product: “Box of Corn Crackers, ¥19.9 Free Shipping”
→ Platform Performance: Over 10,000 sales on Pinduoduo, price < ¥20

✅ Step 2: Define Key Market Heat Indicators

This framework enables effective detection of high-potential local products and content combinations.

5. Suggested Dashboard Design

Based on the above insights and data sources, the following dashboard structure is recommended for quick reference by field teams or product strategists:

This dashboard serves:

• Field operation teams planning local marketing strategies

• Merchandisers leveraging rural e-commerce opportunities

• Brand owners evaluating market penetration in emerging regions

✅ Summary

• LuckData’s Douyin API supports city-level hotlist extraction, ideal for insight into lower-tier markets

• Pinduoduo product data can be simulated or collected to supplement e-commerce trend analysis

• A “content → product → region → conversion” model helps brands detect viral opportunities and deepen market penetration

Articles related to APIs :

• One-Week Build: How a Zero-Tech Team Can Quickly Launch an "E-commerce + Social Media" Data Platform

• Cross-Platform SKU Mapping and Unified Metric System: Building a Standardized View of Equivalent Products Across E-Commerce Sites

• Practical Guide to E-commerce Ad Creatives: Real-Time A/B Testing with API Data

• Integrated Brand Sentiment Monitoring: Smart Consolidation and Early Warning System for Multi-Platform Keywords and Competitor Reviews

• API + AI: Building an LLM-Powered System for Automated Product Copy and Short Video Scripts

• End-to-End Automation for Short Video E-commerce Monitoring (Powered by Luckdata API)