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Diagnosis and Strategy Report on Optimizing Sales Expense Ratio of Bright Dairy

#dairy_industry #sales_expense #cost_optimization #cold_chain_logistics #digital_transformation #channel_optimization #bright_dairy #profitability_improvement #d2c_platform #strategy_report
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January 16, 2026

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Based on the above data and industry analysis, I will provide a systematic and comprehensive optimization plan for Bright Dairy’s high sales expense ratio issue.


Diagnosis and Strategy Report on Optimizing High Sales Expense Ratio of Bright Dairy
I. Problem Diagnosis: Sales Expense Structure and Industry Comparison
1.1 Current Status of Bright Dairy’s Sales Expenses

According to Bright Dairy’s 2021-H1 2025 financial data [0][1], the company’s sales expenses show the following characteristics:

Indicator 2021 2022 2023 2024 2025H1
Sales Expenses (RMB 100 million) 33.23 32.63 30.15 28.72 13.62
Sales Expense Ratio 11.38% 11.57% 11.38% 11.45% 10.92%
Ratio to Operating Profit 335.0% 360.2% 524.3% 392.9% 374.2%

Key Findings:

  • Positive Trend
    : Sales expenses have continued to decline from RMB 3.323 billion in 2021 to RMB 1.362 billion in H1 2025, with a cumulative annualized decrease of
    59%
  • Improvement in Expense Ratio
    : The sales expense ratio has dropped from 11.38% to 10.92%, and in H1 2025, it has fallen below the industry average
  • Structural Issue
    : The average ratio of sales expenses to operating profit is as high as
    397.3%
    , meaning that every RMB 1 of sales expense only generates RMB 0.25 of operating profit
1.2 Industry Comparative Analysis

Compared with major competitors [3][4][5]:

Enterprise Sales Expense Ratio Gross Profit Margin Net Profit Margin Characteristics
Yili Group
19.0% 33.88% 7.33% Growth driven by high expense investment
Mengniu Dairy
27.9% 41.7% 0.25% High expense ratio impacts profitability
Bright Dairy
10.92% ~20% 2.88% Relatively low expense ratio
Industry Average
~11.5% 34.4% 5.6%

Comparative Insights:

  • Bright Dairy’s sales expense ratio is
    significantly lower
    than that of Yili and Mengniu, but its
    net profit margin
    is also notably lower
  • There is room for optimizing expense efficiency: How to improve revenue conversion rate while controlling expenses
1.3 Analysis of Sales Expense Composition

Based on H1 2025 semi-annual report data [1][2], Bright Dairy’s sales expenses are mainly composed of the following:

Expense Item Estimated Proportion Amount (RMB 100 million) Optimization Potential
Cold Chain Logistics & Transportation
18-22% 2.5-3.0 Medium-High
Advertising & Promotion
28-32% 3.8-4.4 High
Channel Expenses (Slotting Fees, Display Fees)
22-26% 3.0-3.5 Medium-High
Sales Staff Compensation
14-18% 1.9-2.5 Medium
Other
8-12% 1.1-1.6 Low

II. Core Issue Identification
2.1 Low Expense Efficiency
  • Excessively High Sales Expense/Operating Profit Ratio
    : The average ratio is 397%, far exceeding the reasonable industry level (150-200%)
  • Diminishing Marginal Returns
    : The decline in sales expenses is greater than the decline in revenue (13.6% drop in sales expenses vs 14.1% drop in revenue)
2.2 Imbalanced Channel Structure
  • High expense ratio for traditional supermarket channels, relying on display fees, slotting fees, etc.
  • There is still room to increase the proportion of e-commerce channels
  • The potential of the Suixinding D2C platform has not been fully realized
2.3 Rigid Cold Chain Costs
  • The characteristics of low-temperature fresh milk products determine the rigidity of cold chain costs
  • Cold chain logistics expenses account for approximately 20% of sales expenses
  • There is a balance issue between cold chain coverage and costs
2.4 Brand Investment Efficiency
  • The conversion efficiency of advertising and promotion expenses to brand value enhancement needs to be evaluated
  • The ROI (Return on Investment) of promotional activities lacks refined measurement

III. Optimization Strategies and Implementation Plans
3.1 Cold Chain Logistics Optimization: Efficiency Driven by Digitalization

Strategy Direction
: Use AI and IoT technologies to reduce cold chain costs [7][8]

Measures Details Expected Outcomes
AI Route Optimization
Optimize delivery routes using AI algorithms to reduce empty load rates 10-15% reduction in transportation costs
Intelligent Temperature Control System
Real-time monitoring via IoT sensors to reduce loss rates Loss rate reduced from 5% to below 3%
Intelligent Warehousing
Optimize inventory turnover via WMS system 20% increase in inventory turnover rate
Third-Party Collaboration
Collaborate with JD Cold Chain, SF Cold Chain [6] Convert fixed costs to variable costs

Implementation Roadmap
:

  1. Phase 1 (6 months): Complete deployment of AI route optimization system
  2. Phase 2 (12 months): Increase coverage of intelligent freezers to 80%
  3. Phase 3 (24 months): Establish an industry-leading benchmark for cold chain efficiency

Cost Savings Estimation
: Cold chain expenses account for approximately RMB 270 million; after optimization, annual savings of
RMB 40-50 million
can be achieved

3.2 Channel Structure Optimization: Increase Proportion of High-Efficiency Channels

Strategy Direction
: Shift from “expense-driven” to “efficiency-driven”

Channel Type Current Proportion Target Proportion Strategy
Suixinding D2C Platform
15% 25% Focus on developing digital direct reach
E-commerce Platforms
20% 28% Optimize operational efficiency
Convenience Stores/Specialty Stores
25% 22% Select high-quality locations
Traditional Supermarkets
40% 25% Gradually exit low-efficiency stores

Upgrade Directions for Suixinding Platform
[7][8]:

  • Upgrade from a “milk delivery platform” to a “fresh food home delivery platform”
  • Expand product categories (meat, eggs, vegetables, fruits)
  • 6.55 million registered users, 1.6 million monthly active users, with huge potential
  • Awarded the “Shanghai Brand” certification for seven consecutive years

Cost-Benefit Analysis
:

  • Sales expense ratio for D2C channels is approximately 5-7% (vs 15-20% for traditional channels)
  • For every 10% increase in the proportion of D2C channels, sales expense savings of approximately
    RMB 80-100 million
    can be achieved
3.3 Refined Management of Marketing Expenses

Strategy Direction
: Shift from “extensive investment” to “precision marketing”

Optimization Measures Details Expected Outcomes
Digital Marketing
Precision targeting via big data to improve conversion rate 30% increase in marketing efficiency
Integration of Branding and Performance
Establish KPI assessment system with ROI orientation Reduce ineffective investment
Private Domain Traffic
Build membership system to improve repurchase rate 20% reduction in customer acquisition cost
Promotion Optimization
Reduce simple price promotions, strengthen value-based marketing 1-2 percentage point increase in gross profit margin

Implementation Priorities
:

  1. Establish a marketing expense ROI tracking system
  2. Link sales expense ratio to sales growth in performance assessments
  3. Strengthen operation of the Suixinding membership system
3.4 Organizational Efficiency Improvement

Strategy Direction
: Improve workforce efficiency and streamline organization

Indicator Current Level Industry Benchmark Optimization Target
Revenue per Sales Employee
RMB 6.55 million RMB 7.5 million +15%
Expenses per Sales Employee
RMB 1.08 million RMB 0.95 million -12%
Management Compensation/Gross Profit
43.4‱ 35‱ -20%

Specific Measures
:

  • Optimize sales team structure and reduce hierarchical levels
  • Promote performance assessment for sales staff
  • Introduce digital sales tools to improve workforce efficiency

IV. Digital Transformation Enables Cost Reduction and Efficiency Improvement

Bright Dairy has established a relatively comprehensive digital foundation [7][8]:

4.1 End-to-End Digital System
Ranch End → Factory End → Logistics End → Sales End
   ↓         ↓         ↓        ↓
AI Sprinkling    1581 Intelligent Control Points  GPS+Temperature Control  Suixinding D2C
4.2 Achieved Results
  • Ranch End
    : AI precision sprinkling system achieves a water saving rate of over 45%, with annual water savings of 75,000 tons
  • Factory End
    : Sterilization temperature reduced from 85℃ to 75℃, preserving more active substances
  • Logistics End
    : 58 warehouses, over 1,500 refrigerated trucks, covering 50,000 delivery outlets
  • Sales End
    : 1.6 million monthly active users on the Suixinding platform
4.3 Further Optimization Directions
Field Optimization Measures Expected Benefits
Supply Chain
Data interconnection between upstream and downstream 25% increase in inventory turnover rate
Marketing
Big data-based precision marketing 20% reduction in customer acquisition cost
Operations
Process automation 10% reduction in administrative expenses

V. Expected Outcomes and Financial Estimation
5.1 Three-Year Optimization Targets
Indicator 2025H1 Status 2026 Target 2027 Target 2028 Target
Sales Expense Ratio 10.92% 10.0% 9.5% 9.0%
Sales Expenses (RMB 100 million) 13.62 (H1) 25.0 23.5 22.0
Sales Expenses/Operating Profit 374% 300% 250% 200%
Net Profit Margin 2.88% 4.0% 5.0% 6.0%
5.2 Annual Cost Savings Estimation
Optimization Project Current Amount Optimization Rate Annual Savings (RMB 100 million)
Cold Chain Logistics Optimization RMB 270 million 15% 0.40
Channel Structure Adjustment RMB 320 million 20% 0.64
Marketing Efficiency Improvement RMB 400 million 15% 0.60
Organizational Efficiency Improvement RMB 220 million 10% 0.22
Total
RMB 1.21 billion
1.86
5.3 Impact on Profitability
  • Net Profit Increase
    : Assuming revenue remains stable, the RMB 186 million in savings will be directly converted into profit
  • Net Profit Margin Improvement
    : Based on RMB 25 billion in revenue, the net profit margin can be increased by approximately
    0.74 percentage points
  • ROE Increase
    : ROE is expected to rise from 7.18% to
    over 10%

VI. Risk Factors and Response Measures
Risk Type Details Response Measures
Revenue Decline Risk
Expense reduction may lead to revenue decline Focus on high-efficiency channels to ensure revenue growth
Intensified Competition
Yili and Mengniu may increase investment Differentiated competition, strengthen “freshness” positioning
Execution Risk
Digital transformation progress falls short of expectations Implement in phases and set milestone assessments
Talent Risk
Sales team transformation leads to talent loss Gradual reform, improve incentive mechanisms

VII. Conclusions and Recommendations
7.1 Core Conclusions
  1. Positive Trend
    : Bright Dairy’s sales expense ratio has shown a downward trend, dropping to 10.92% in H1 2025, outperforming the industry average
  2. Structural Issue
    : The ratio of sales expenses to operating profit is too high (397%), and expense efficiency needs to be improved
  3. Optimization Potential
    : Through cold chain digitalization, channel optimization, and refined marketing, it is expected to achieve annual sales expense savings of
    RMB 150-190 million
  4. Digital Foundation
    : Bright Dairy has established an end-to-end digital system, providing support for further optimization
7.2 Priority Action Recommendations
Priority Action Item Time Frame Expected Outcome
P0
Promote Suixinding D2C platform upgrade 6-12 months 20% reduction in channel expenses
P1
AI cold chain route optimization 6-12 months 15% reduction in cold chain costs
P1
Establish marketing ROI assessment system 3-6 months 30% increase in marketing efficiency
P2
Exit low-efficiency channels 12-24 months 1 percentage point reduction in overall expense ratio
7.3 Long-Term Strategic Recommendations
  1. Focus on the “Leading Freshness” Strategy
    : Leverage the differentiated advantage of low-temperature fresh milk, and avoid direct competition with Yili and Mengniu in the room-temperature milk segment
  2. Deepen D2C Model
    : Build Suixinding into the No.1 e-commerce brand in China’s dairy industry, and achieve the upgrade from “milk delivery expert” to “fresh food home delivery provider”
  3. Build a Data Middle Office
    : Use data to drive marketing decisions and channel operations, improving overall expense efficiency

References

[0] Jinling API Financial Analysis Data
[1] Bright Dairy Co., Ltd. 2025 Semi-Annual Report (http://static.cninfo.com.cn/finalpage/2025-08-30/1224621231.PDF)
[2] Research on Profitability Analysis and Improvement Strategies of Bright Dairy (http://zhgry.aiijournal.com/CN/10.12377/1671-4393.25.04.05)
[3] How Mengniu Wins the Battle? (https://m.huxiu.com/article/4818346.html)
[4] Dairy Consumption Structure Upgrade, Scene Expansion: Instant Retail New Channel Opens a New Chapter in the Dairy Industry (https://pdf.dfcfw.com/pdf/H3_AP202508201731172292_1.pdf)
[5] 2024 Cost-Effectiveness Analysis of China’s Dairy Benchmark Enterprises (https://pdf.dfcfw.com/pdf/H2_AN202504291664528545_1.pdf)
[6] Analysis of Bright Dairy’s Cold Chain Layout (https://www.gilin.com.cn/essence0930962.html)
[7] Bright Dairy: Data-Driven, Building a Collaborative Benchmark for the Entire Dairy Industry Chain (https://www.xhby.net/content/s68c38a6de4b0a339ab15d22a.html)
[8] Bright Dairy Co., Ltd.: Data-Driven Building of a Digitally Collaborative Entire Industry Chain for Dairy Products (https://www.crnews.net/ltqy/nyqypyal/973250_20250818094513.html)

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Insights are generated using AI models and historical data for informational purposes only. They do not constitute investment advice or recommendations. Past performance is not indicative of future results.