Meituan Instant Retail Business: Analysis of the Break-Even Point for Average Delivery Cost

Based on public market data and industry analysis, this report systematically analyzes the break-even point for average delivery cost of Meituan’s instant retail business.

The 2025 Chinese instant retail market presents a “three-way battle” pattern: Meituan maintains approximately 50% market share with its deep merchant coverage and delivery network; Alibaba integrates Ele.me and Taobao traffic to occupy 42%; JD.com, as a new entrant, gains 8% share [1]. This fierce competition led to a total increase of 61.4 billion yuan in takeaway-related marketing expenses among Meituan, Alibaba, and JD.com in Q3 2025, directly impacting profits [1].

In terms of stock performance, Meituan (3690.HK) saw its share price drop from HK$150.6 at the start of 2025 to HK$103.3 at the end of the year, with an annual decline of 31.41%, reaching a high of HK$189.6 and a low of HK$94.05, reflecting market concerns about competitive pressure [0].

Based on public industry information estimates, Meituan’s average delivery cost breakdown is as follows:

Cost Item	Amount (Yuan)	Proportion
Basic Delivery Cost (Rider Income, Vehicle Depreciation, etc.)	7.50	75.2%
Long-Distance Order Surcharge (Applicable to 30% of Orders)	0.36	3.6%
Special Time Period Surcharge (Applicable to 15% of Orders)	0.12	1.2%
Bad Weather Surcharge (Applicable to 10% of Orders)	0.05	0.5%
Platform Service Fee Allocation	2.00	20.0%
Weighted Average Delivery Cost per Order	8.03	100%

Item	Amount (Yuan)
Commission Revenue (18% Commission Rate)	8.10
Advertising Revenue	0.50
Other Revenue	0.80
Total Average Revenue per Order	9.40

• Break-Even Cost (Zero Profit):
  9.40 yuan
• Break-Even Cost for 5% Target Profit Margin:
  8.93 yuan
• Current Gross Margin:
  14.57%

The impact of Alibaba Group on Meituan is mainly reflected in the following four dimensions [1][2]:

Impact Factor	Impact Estimate	Cost Impact (Yuan)
Commission Rate Reduction Pressure (2-3 Percentage Points Drop)	Commission Revenue Decrease by ~10%	+0.50
Increased User Subsidies (15-20% Increase in Marketing Costs)	Higher Platform Subsidies	+0.80
Rising Rider Costs (10-15% Increase in Social Security and Other Costs)	Higher Rider Costs	+0.60
Decline in Order Density (5-8% Increase in Average Cost)	Lower Delivery Efficiency	+0.40
Comprehensive Impact	—	+2.30 yuan

1. Current Safety Margin is Negative
   : Considering the impact from Alibaba, the comprehensive break-even cost is approximately 8.60 yuan, while the current cost is 8.03 yuan, with a safety margin of -6.6%, meaning Meituan has approached the profit pressure line.
2. Cost Break-Even Thresholds
   :
   • Break-Even Point Without Alibaba Impact
     : 9.40 yuan
   • Break-Even Point With Alibaba Impact
     :8.60 yuan
   • Current Actual Cost
     :8.03 yuan
3. Sensitivity Analysis
   :
   • For every 0.5 yuan increase in delivery cost, gross margin drops by approximately 5 percentage points
   • When delivery cost reaches 9.0 yuan, gross margin is only 4.3%
   • When delivery cost exceeds 9.40 yuan, the business will enter a loss state

Based on analysis from 36Kr reports, Meituan is adopting the following strategies to respond [1][2]:

1. Shrink Non-Core Businesses
   : Integrate Flash Purchase into the first-level entry on the homepage, and consolidate the basic market with high-density fulfillment networks
2. Vertical Deepening
   : Efficiently reuse user habits, rider capacity, and merchant relationships accumulated from food delivery to retail categories
3. Cost Optimization
   : Improve operational efficiency through AI tools to reduce average cost

: If Alibaba continues to increase subsidies, Meituan’s average delivery cost break-even point may further decline.

[1] 36Kr - Ten Key Moments of Chinese Business in 2025: Reconstruction, Awakening, Coopetition (https://m.36kr.com/p/3618985319658249)

[2]36Kr - In 2026, Meituan Cannot Afford to Lose, But It’s Harder to Win (https://www.36kr.com/p/3625238415066373)

[0] Jinling AI - Meituan (3690.HK) 2025 Stock Price Data and Financial Analysis