(Source: https://pltfrm.com.cn)
Introduction
In China’s competitive retail landscape, pricing is not just a tactic—it’s a science. An advanced demand curve pricing model helps overseas brands move from reactive markdowns to predictive, data-informed pricing. By analyzing how different price points impact demand, brands can optimize for revenue, margin, or market share depending on the scenario. This article explores how to apply demand curve modeling to retail operations in China for maximum commercial impact.
1. Understand the Shape of Your Product’s Demand Curve
1.1 Elastic vs. Inelastic Product Categories
Determine whether your product is price-sensitive (elastic) or not (inelastic) in the Chinese market. For instance, commodity skincare may be elastic, while imported health supplements may hold pricing power.
1.2 Data Sources for Curve Estimation
Leverage Tmall transaction logs, Douyin live-stream metrics, and JD cart abandonment data to map the relationship between pricing and volume across campaigns and seasons.
2. Build and Train a Pricing Model Based on Real Behavior
2.1 Use Regression Analysis or Machine Learning
Employ linear or non-linear regression models, or ML algorithms like XGBoost, to predict how changes in price affect units sold. Train the model with data segmented by region, platform, and promotional context.
2.2 Segment by Buyer Persona or Channel
Build separate demand curves for high-AOV buyers, Douyin users, or shoppers in Tier 3 cities. This allows for differentiated pricing across customer segments or sales platforms.
3. Apply the Model to Drive Pricing Decisions
3.1 Optimize for Margin or Volume Based on Curve Slope
If the model shows steep volume gains from small price drops, use aggressive pricing to capture market share. If demand is flat, hold price and push value messaging to protect margin.
3.2 Tailor Pricing by Product Lifecycle
Early-stage SKUs may benefit from low-price, high-volume strategies. Mature products might shift toward margin maximization as brand equity increases.
4. Test, Refine, and Operationalize Your Demand Curve Strategy
4.1 A/B Test Price Points on Controlled Cohorts
Run A/B tests with two price points to validate model predictions. Use China’s digital platforms—especially mini programs and CRM-integrated coupons—for clean test environments.
4.2 Continuous Feedback Loop
Integrate new sales and behavioral data into the model on a rolling basis. Retail conditions in China shift quickly, so model accuracy depends on regular recalibration.
Case Study: Scandinavian Beverage Brand Optimizes Douyin Pricing Using Demand Curves
A Nordic sparkling water brand tested demand curve modeling on its Douyin store, mapping price sensitivity across 12 SKUs. The model revealed that reducing price by 12% led to a 60% increase in conversion during live-stream campaigns. They deployed differentiated pricing by SKU and region, improving gross revenue per campaign by 27% and reducing unnecessary markdowns.
PLTFRM is an international brand consulting agency that works with companies such as Red, TikTok, Tmall, Baidu, and other well-known Chinese internet e-commerce platforms. We have been working with Chile Cherries for many years, reaching Chinese consumers in depth through different platforms and realizing that Chile Cherries’ exports in China account for 97% of the total exports in Asia. Contact us, and we will help you find the best China e-commerce platform for you. Search PLTFRM for a free consultation!
