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Douyin/Kuaishou E-commerce Product Selection Strategy: Leveraging Social Popularity and Sales Data
Introduction: Trending ≠ Best-Selling — How to Use Data to Identify High-Potential Products?
In the age of short video e-commerce, content-driven traffic has reshaped consumer behavior. “Product selection” is now a critical factor that determines whether your campaign succeeds or fails.
However, many merchants and brands face a common dilemma:
Should you prioritize platform popularity?
Or go straight to sales data?
The answer is: both are indispensable.
This article presents a data-driven product selection method — combining Douyin video popularity with Lazada/Pinduoduo e-commerce sales data to identify high-conversion, high-traction items that are both talked about and purchased.
1. Why "Social Popularity + Sales" Is the Golden Formula for Product Selection
A sound product strategy needs to capture both momentum and purchase intent:
Relying solely on sales data: You’re looking at past winners, which might miss emerging trends.
Relying solely on social heat: May lead to selecting viral but non-converting “hype products.”
Combining both: Pinpoints products with high “content-to-conversion” efficiency.
Take for example a facial cleansing device that rapidly climbs Douyin's trending charts. If sales on Lazada surge simultaneously, this indicates not only strong engagement but also high buyer intent — a clear sign of a winning product.
2. Building the Data Stack: Required APIs and Fields
To implement this strategy, we combine insights from short video platforms and e-commerce platforms through API integration.
1. Douyin Trending API + Video Data
GET https://luckdata.io/api/douyin-API/get_xv5p?city=110000&type=rise_heat&start_date=20241223&end_date=20241224&page_size=10Returns fields like:
title: Video titleitem_id: Unique ID of the videolike_count: Total likesauthor: Creator username
This helps measure content appeal and viral potential.
2. Douyin Video Details API (Detect Product Links)
GET https://luckdata.io/api/douyin-API/get_pa29?item_id=7451571619450883355&type=items,cnt,trends,authorIf the response contains fields like product_id or external_link, it’s a product-linked, commerce-ready video.
3. E-commerce Product Data (Lazada API Example)
GET https://luckdata.io/api/lazada-online-api/x3fmgkg9arn3?site=th&itemId=2396338609Returns:
product_name: Product nameprice: Listing pricemonthly_sales: Monthly sales volumecoupon: Discount infoproduct_url: Direct product page
This allows quantifying real-world buyer response and pricing strategy.
3. Execution Guide: How to Filter “Hot & Shoppable” Products
Scrape Douyin trending content (using
rise_heator product-tagged filters)Filter for videos with commerce links, extract product keywords
Search keywords on Lazada/Pinduoduo, locate matching products
Collect sales, pricing, reviews, and promotion data
Calculate dual-metric score based on video engagement and e-commerce performance
Scoring model example:
Hot-Sale Score=(Views×0.3+Likes×0.7)0.5+(MonthlySales×0.5+DiscountStrength×0.5)\text{Hot-Sale Score} = (Views × 0.3 + Likes × 0.7)^{0.5} + (Monthly Sales × 0.5 + Discount Strength × 0.5)
Where discount strength is the percentage (e.g., 20% OFF = 20).
This score helps prioritize products with both content virality and actual consumer demand.
4. Sample Product Ranking Table
Product Name | Douyin Likes | Lazada Monthly Sales | Promotion | Hot-Sale Score |
|---|---|---|---|---|
Upgraded Facial Cleanser | 23,400 | 5,800 | 20% OFF | 89.3 |
Hyaluronic Acid Mask | 18,600 | 7,200 | 15% OFF | 91.2 |
Meal Replacement Biscuits | 31,200 | 2,000 | None | 75.8 |
Zero Sugar Sparkling Water | 15,700 | 4,900 | Buy 1 Get 1 50% | 82.1 |
Portable Juicer Cup | 27,800 | 3,300 | 10% OFF | 80.5 |
✅ Recommended: Prioritize the top 2 products in paid traffic campaigns or video production to test ROI quickly.
5. Who Should Use This Method?
This dual-indicator approach suits a wide range of business scenarios:
Douyin/Kuaishou merchants: Rapidly identify high-potential items for short video or livestream campaigns
E-commerce operations teams: Add data-backed logic to product sourcing decisions
Content creators / MCN agencies: Match trending products to creator style and audience
Cross-border sellers: Track overseas TikTok trends to find sourcing opportunities or reverse-import ideas
It can also support mid-to-long term product forecasting systems with historical data accumulation.
Conclusion
Product selection is no longer just about instinct or supplier suggestion — it’s a data battle. The fusion of social virality with real sales traction enables smarter, faster, and more stable decisions.
With this “Social + Sales” double-validation framework, you don’t just chase trends — you catch them early and convert them with precision.
✅ Make your product strategy a growth engine, not a gamble.
