Cross-Platform User Analysis: A Practical Guide to Building Precise Personas with TikTok, Douyin, and Lazada Data

Introduction

In the era of digital marketing, understanding users' interests and behavioral preferences is essential for creating content, selecting products, and placing ads that hit the right audience. This article leverages LuckData's TikTok, Douyin, and Lazada APIs to break down the full-cycle path from “social interests” to “purchase conversion,” helping you construct a multi-dimensional, actionable user persona framework to improve targeting precision and marketing efficiency.

1. Why Build Cross-Platform User Personas?

Cross-platform personas enable deeper, smarter decisions in product selection, ad targeting, and content creation.

2. Key APIs and Data Points Overview

These APIs provide essential insights across behavior and content signals—forming the basis of a robust persona model.

3. Five Steps to Building a User Persona

1. Collect Social Interaction Data

• TikTok API Influencer Filtering

res = requests.get(
"https://luckdata.io/api/tiktok-api/user_follower_list?user_id=<InfluencerID>",
headers=headers
)
followers = res.json()['data']['followers_count']

• Douyin API Hot List Author Extraction

res = requests.get(
"https://luckdata.io/api/douyin-API/get_xv5p?city=110000&type=rise_heat",
headers=headers
)
authors = [v['author_id'] for v in res.json()['data']['list']]

Analyze influencer content metrics, engagement rates, and relevance to determine real impact and influence.

2. Extract Interest Tags

• Use hashtags and challenge topics from TikTok and Douyin videos to infer interest dimensions

• Apply NLP to titles, captions, and high-frequency comments to generate tag clouds

• Examples: “#skincare,” “#dailyworkout,” “#ingredientreview,” “#unboxing”

These signals help classify users into interest-based clusters for more effective targeting.

3. Link to E-commerce Behavior

• Use search_product to analyze high-performing product categories on Lazada

• Extract customer review keywords via product_detail, such as “value for money,” “gentle formula,” “new launch”

• Cross-analyze purchase patterns and inferred motives

This builds the bridge between “interest” and “intent,” revealing deeper motivations.

4. Build a Persona Schema

Example JSON structure for a refined user persona:

{
"user_segment": "Young Female Skincare Enthusiast",
"social_metrics": {
"avg_tiktok_views": 120000,
"avg_douyin_likes": 3500
},
"interest_tags": ["skincare", "reviews", "ingredient-focused"],
"purchase_behavior": {
"avg_order_value": 25.4,
"fav_categories": ["masks", "serums"],
"top_keywords": ["hydrating", "brightening"]
}
}

This structured data can directly power ad platforms and personalization engines.

5. Visualization & Deployment

• Radar Charts: Quantify key metrics such as influence, interest density, and buying power

• Persona Cards: Generate visual summaries for each audience cluster for easy team use

• Automated Tag Sync: Push persona tags to ad platforms for real-time precise targeting ✅

4. Real-World Case Study: Skincare Influencers + Face Mask Buyers

1. Social Media Signals

• TikTok Influencer A: 800K+ followers, 150K average video views

• Douyin Hot List Author B: Focuses on “plant-based skincare,” 500K followers

2. Interest Tags and Content Themes

• Shared focus on “ingredient transparency,” “sensitive skin,” and “repair routines”

• Frequent tags include: “#hyaluronicacid,” “#recoverymask,” “#sensitivefriendly”

3. E-commerce Data Analysis

• High-performing Lazada face masks include reviews mentioning “hydration,” “soothing,” and “hypoallergenic” in over 45% of cases

• Average product price ranges from $20–$30

4. Final Persona Output

{
"segment": "Hydration-Seeking Sensitive Skin Users",
"social": {
"tiktok_views": 150000,
"douyin_plays": 200000
},
"tags": ["sensitive skin", "hydration", "repair"],
"ecom": {
"price_range": [20, 30],
"keywords": ["hydration", "soothing", "hypoallergenic"]
}
}

With this persona, brands can invite relevant influencers for deep product testing or launch targeted ads for best-selling hydration masks ✅

5. Conclusion

Cross-platform user persona development enables full-funnel optimization—from interest recognition to product conversion. It empowers:

• Content teams to design scripts aligned with user interests

• Product teams to optimize SKUs based on real preferences

• Marketing teams to execute precision-targeted campaigns that boost ROI ✅

The power of cross-platform analysis lies not just in seeing more, but in acting smarter. Now is the time to upgrade your understanding of your audience.

Articles related to APIs :

• Behind Viral Short Videos: How to Predict TikTok Trends Using API

• From Comments to Trends: Uncovering User Needs and Sentiments with TikTok Comment Data

• Practical Guide: How to Build a Multi-Platform Automated Inventory and Logistics Alert System Using APIs

• Lazada API Mastery: Practical Guide for Product Research and Price Monitoring in Southeast Asia

• Reverse-Driven Optimization: Turning User Complaints into Powerful Copy and Product Advantages

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