A leading food and beverages manufacturer in the USA faced significant challenges in understanding SKU-level cannibalization and its impact on sales. Their reliance on brand-level ROI analysis led to inefficient resource allocation and a fragmented marketing strategy. Quantzig stepped in with an advanced analytics-driven approach to uncover demand transference and optimize their promotional efforts through a market cannibalization analysis.
Key Highlights of Market Cannibalization
- SKU-Level Insights : Identified demand transference and cannibalization effects
- Technology-Driven Approach : Integrated Power BI and Python on Azure for real-time analytics.
- Optimized Budget Allocation : 15% reallocation to impactful initiatives.
- Enhanced Promotion Planning : Improved efficiency in campaign execution and marketing strategies.
Problem Statement of the Client
The client struggled with SKU-level cannibalization, which limited their ability to make data-driven decisions and optimize resource allocation. There was an over-reliance on brand-level ROI analysis, leading to missed demand shifts across SKUs—particularly relevant for pricing strategies. The lack of SKU-specific insights resulted in inefficient resource distribution and fragmented promotional strategies, ultimately reducing the overall impact across brands. Additionally, the client’s limited in-house analytics capabilities hindered their ability to conduct an effective market cannibalization analysis.
The client sought an advanced analytics driven solution to measure demand shifts, optimize marketing spend, and enhance category share through a data-backed approach.
Objectives of the Client
Understanding SKU-level cannibalization is crucial for optimizing marketing strategies and resource allocation. Without clear insights into demand transference, businesses risk misallocating budgets and running ineffective campaigns. To address this, the client aimed to enhance decision-making through advanced analytics, beginning with a comprehensive market cannibalization analysis.
The first objective was to identify and quantify SKU-level cannibalization by analyzing sales data to measure demand shifts. This enabled more precise targeting and minimized overlap. Second, the client aimed to improve budget allocation by reallocating marketing investments to high-impact areas. The third objective focused on enhancing promotional strategies through the development of targeted campaigns that would maximize category share and minimize revenue loss. Finally, leveraging advanced analytics was critical to derive data-backed insights for strategic decision-making and performance improvement.
Solution Implemented
Quantzig implemented an AI-powered solution to analyze sales drivers and assess demand transference among SKUs. Our decomposed model evaluated competitive actions, category growth, and promotional impacts to quantify cannibalization effects. A Power BI dashboard integrated with a Python model on Azure provided real-time insights, enabling the client to optimize promotions and resource allocation.
Quantzig’s Solutions
- Competitive Actions: Assessed pricing and marketing strategies for competitive advantage.
- Category Growth Analysis: Identified key trends influencing consumer demand.
- Promotional Optimization: Enhanced customer engagement and sales performance.
- Cannibalization Measurement Tool: Provided real-time alerts to minimize revenue loss.
- AI-Powered Insights: Enabled predictive analytics for precise decision-making.
Technology Used
- Power BI : Interactive fast-moving consumer goods (FMCG) industry dashboards for real-time data visualization.
- Python on Azure : AI-driven model for demand transference analysis.
- Machine Learning Algorithms : Trend identification and predictive analytics.
- Data Integration Framework : Consolidated structured and unstructured data for in-depth analysis.
Results & Impact
| Metric | Before | After | Improvement |
|---|---|---|---|
| SKU-Level Cannibalization Insights | Limited visibility | Detailed SKU-level analysis | Enhanced decision-making |
| Budget Allocation | Inefficient spending | 15% budget reallocated | Optimized investments |
| Promotion Planning | Fragmented and inconsistent | Data-driven campaign execution | Improved marketing impact |
Qualitative Impact:
- Improved SKU Management : Clear understanding of demand shifts enabled better inventory and pricing decisions.
- Optimized Marketing Spend : Allocated budget towards high-impact initiatives.
- Enhanced Competitive Positioning : Data-driven insights strengthened market strategy.
- Faster Decision-Making : Power BI dashboards streamlined analytics and reporting.
How Quantzig Can Help?
With over 20 years of expertise in data analytics, Quantzig helps global enterprises tackle complex business challenges using cutting-edge AI and ML powered solutions. Our approach to SKU-level demand transference and cannibalization analysis ensures strategic marketing decisions, optimized budget allocation, and improved product development.
Quantzig's Expertise
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Advanced Analytics Solutions
AI-driven insights to tackle SKU cannibalization.
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Integrated Technology Stack
Power BI, Python, and Azure for real-time decision-making.
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Industry Expertise
Proven success in consumer goods and retail analytics.
