AI’s Role in A Successful RGM Strategy

    In today’s world, CPG companies face a unique challenge – maintain and maximize top-line while lowering spend. Solving this challenge through RGM is often a balance between predicting consumer behavior across channels and analyzing data from assortment, distribution, and promotion activities. 

    A recent study by the Boston Consulting Group (BCG) found that CPG companies can generate over 10% top-line growth simply by investing in Artificial Intelligence (AI). While traditional RGM solutions rely heavily on historical data to create future roadmaps, AI-based solutions help in forecasting, simulating, and planning for any scenario. A differentiated RGM system enables CPG organizations navigate complex data structures. The focal point of such enhanced systems remains the optimization of assortment, pricing, promotions, distribution and marketing components. Currently, this differentiated factor has taken the form of AI. 

    The need of the hour is a holistic AI-based data-driven solution that brings CPG companies closer to their business objectives. 

    Insight-Driven Actions Through AI 

    Artificial Intelligence empowers CPG leaders with the right insights enabling them to make the right decisions and stop guessing the next step. 

    Through AI, extraction of valuable insights from a myriad of data sources becomes easy. Moving away from legacy processes and traditional tools facilitates speed and accuracy in creating an action oriented RGM model. 

    AI in Assortment 

    AI optimizes product assortment across retailers, brands, and SKUs. This reduces supply chain adjustments and clarifying assortment metrices at a micro level. Using AI, a local store manager has the right insight into the demand of a particular product and would use this information to improve customer engagement. Similarly, CPG companies can leverage AI to facilitate informed retailer negotiations for optimum shelf-space and sale maximization. 

    Artificial Intelligence helps tailor assortments that improve customer experience, mitigate out-of-stock incidences, and build product/brand visibility. 

    AI in Pricing 

    To tackle complex pricing challenges that yield profits, revenue growth management systems should deploy advanced analytical approaches that lead to better conversions. 

    In the same study mentioned earlier, BCG found that adopting AI-led revenue management systems for determining pricing strategies can increase revenues for companies by at least five percent in less than nine months. CPG companies should use data drawn from AI to locate areas of price differentiation, customer incentives, and discounts. Machine learning applications will also be able to highlight pricing gaps that CPG companies can consider while curating pricing strategies. With the right understanding and forecasting insight, CPG companies can create targeted periodical pricing strategies based on demand, geography, and buying patterns. 

    AI in Promotion and Marketing 

    Promotions and marketing are among the highest spend components in CPG organizations. With that said, most campaigns fail to break even. This may be due to the underutilization of data or failure to turn data into actionable insights. Adopting AI for CPG would lead to optimized promotions. Machine learning algorithms churn enormous amounts of data and predict trends. AI facilitates forecasting actions for the future based on previous patterns. This pattern may consider customers’ desires, inclinations, and motivations to buy a product. 

    Alignment between marketing and remaining RGM components is often overlooked by traditional systems, but a robust analytical infrastructure drives revenue growth by converting data into real-time insights. According to BCG, revenue growth for CPG companies can grow an additional five percent with companies implementing targeted selling programs. This includes relying on factual data fed by AI for improving promotions, customer loyalty, and capitalizing on potential demand. 

    AI in Distribution 

    The post-pandemic era has altered the touchpoints for customers. A customer’s purchasing power has always played a pivotal role in their decision-making process. Another factor that has recently joined the force is product availability. This may be due to increased market competition for substitute goods or the shift in customer touchpoints. 

    One can say that managing and analyzing distribution channels has become as complex as managing pricing strategies. It is imperative to gauge the gaps where customers fall out of the predicted buying journeys. AI and advanced analytics have made this possible. The need for the hour remains predictive analysis for shopping patterns, customer demand forecasting and faster data analysis. 

    A Solution That Delivers 

    An AI-based RGM solution that is predictive and prescriptive in nature enables CPG companies better define customer journeys and make decisions that are aligned with their business objectives. 

    Through AI-based tools/applications, businesses can penetrate markets by gaining deep market insights. By translating large amounts of data into actionable roadmaps, they are able to coordinate efforts between several RGM components for sustainable revenue growth. 

    A robust advanced analytical application, Co.dx integrates all aspects of RGM by identifying market trends and projecting actionable insights for faster decision-making. Moreover, building scalable applications that are unique to businesses remains at the heart of this advanced analytical tool. 

    To be able to generate business value, organizations need to turn to technology that bases itself in artificial intelligence to foster quick and effective decision making. The App suites developed by Co.dx are designed exclusively for the CPG industry to increase action-oriented decision making with quick turnaround applications.