Trade Promotions Optimization for a Leading CPG Manufacturer
Trade Promotion Optimization (TPO) is the process of utilizing integrated goals, factoring in promotion and supply constraints, and predictive analytics for precise promotion planning and increasing client loyalty. With declining sales and intense competitive pressure, the manufacturers in the consumer packaged goods (CPG) industry need a reliable trade promotion optimization (TPO) strategy. The existing attempts […]READ MORE >>
Trade Promotion Optimization (TPO) is the process of utilizing integrated goals, factoring in promotion and supply constraints, and predictive analytics for precise promotion planning and increasing client loyalty. With declining sales and intense competitive pressure, the manufacturers in the consumer packaged goods (CPG) industry need a reliable trade promotion optimization (TPO) strategy. The existing attempts at TPO lack depth and are primarily based on qualitative information. TPO is one of the key activities for manufacturers in the CPG industry to increase short-term sales of the products.
Quantzig’s trade promotions optimization utilizes data from various promotions, price points, and sales forecasts to offer actionable insights to the client. Our solutions help businesses generate better forecasts to analyze promotion efficiency of their products. Our ability to derive insights into the impact of trade promotions on consumer buying behavior offers a significant competitive advantage to manufacturers in the CPG industry.
The Business Challenge and Quantzig’s Approach
To improve sales and battle competitive pressure, the client, a leading CPG manufacturer in the US approached Quantzig to perform a trade promotions optimization. The client was struggling with promotion planning and execution due to the seasonal nature of their products. The client’s capability to plan promotions lacked depth and was based on qualitative or incomplete information. Volume planning was not linked to realistic promotional outcomes leading to inappropriate inventory levels and reduced profits. As a result, the client needed to develop a solution that could improve the ROI and overall cost savings.
The primary objective of this trade promotions optimization was to develop capabilities for precise promotion planning and increase client loyalty for their products. The team developed a pricing simulations model that could model sales volumes based on different market scenarios that were needed to replace the instinct-based approach of the category management department.
To meet the specific requirements of the CPG manufacturer, the analytics team analyzed various historical sales data, category and product data, pricing data, and shipment data to offer insights on trade promotion optimization strategy. The research team focused on developing a solution that would improve the client’s promotional executions by combining these optimizations with simulations. The team developed effective pricing and promotions strategy and simulated sales based on different scenarios.
An overview of the data used and models applied are given below
Business Benefits and Insights
With the objective of improving overall sales and ROI, and to create precise promotion planning to increase client loyalty, the predictive analytics team analyzed promotion efficiencies, based on time of day/month, retailer segments, and region to improve promotion reach and effectiveness and created a promotion plan options based on levers such as cost, timing, and depth of promotional activities. The trade promotions optimization improved the client’s trade promotion planning process based on accurate volume forecasts and promotional efficiency.
It derived insights about the promotional impact on consumer buying behavior. The client achieved cost savings on packaging destruction costs from seasonal products due to the ability to forecast demand with high accuracy. A better forecast to analyze promotional efficiency helped the client achieve time savings of more than three months in the promotion planning process. The analysts assessed campaign effectiveness based on available data to make dynamic adjustments. The solutions from the trade promotion optimization engagement helped the client generate price simulations and discount offers based on retailer segment and promotional tactics. The team provided the user with accurate baselines and lift coefficients, and the ability to deliver one-off promotion predictions based on numerous pricing scenarios.
The client was able to create an effective promotion planning with the help of trade promotion optimization which helped improve customer loyalty. There was an increase in ROI and improvement in cross-selling and up-selling based on targeted promotions and pricing. The historical sales were broken into base, incremental, and total sales and incremental sales were mapped to the set of individual promotions and campaigns. The solutions helped the client develop an optimized annual plan for strategic promotions based on profit, volume, and revenue.
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