How to increase profitability with revenue growth management

From dramatic shifts in consumer behavior to stubborn inflation to decreasing brand loyalty, CPGs have had to adapt their revenue growth management (RGM) strategies faster than ever to prioritize relevant offers in the face of changing consumer preferences. This calls for CPGs to reshape their RGM strategies to follow these shifts and prioritize relevant offers to adapt to changes in consumer preference. 

Cognitive technology can help CPGs significantly optimize their RGM strategies. Blending human expertise with advanced mathematical techniques, cognitive technology is a step ahead of AI and machine learning (ML) alone. It captures a large range of data from multiple sources and enables a more pragmatic, practical, and impactful approach to making decisions. The data-led insights it delivers can fuel more profitable and commercial decision-making. 

But, what types of data should be used to achieve more than the basic RGM fundamentals? 

Types of data for scalable revenue growth

To achieve sustainable revenue growth in line with dynamically changing market demands, essential data includes: 

Historical data

Capturing past promotional activities, pricing strategies and sales performance is pivotal to informing future optimization. Cognitive technology can not only use this data to identify gaps, but also deliver recommendations on how to improve future performance. 

Market data

Gathering information on trends, competitor pricing and promotions, and consumer behavior can surface unparalleled insight. This equips CPGs with the data needed to identify why consumers are buying and when, offering insights that inform new product lines and promotional opportunities - with the ultimate goal of driving more sales. 

Operational data

Tracking inventory levels and on-shelf availability can offer critical insight into supply chain and distribution channel efficiency. Cognitive technology can constantly monitor this data, bringing new insights to light as markets, consumer demand, and operational processes shift. 

Why are additional RGM data sources so important?

RGM typically harnesses data from ERP systems. But, to provide richer insights, integrating additional data sources beyond ERP is invaluable. Data can be obtained from secondary sources covering competitor positioning, market trends, and consumer behavior. This level of insight leverages advanced analytics and subsequently creates deeper segmentation which can be pivotal to unlocking winning strategies. 

By cross-analyzing these sources of data, CPGs can make improved commercial decisions regarding pricing, promotions, assortment, distribution, and new product development - ensuring real-time consumer demands are met, and every dollar spent is optimized fully. Bringing it all together in one source of truth for RGM management.Once you’ve sourced the various data points into your RGM platform, you can then begin devising different RGM approaches to meet your needs. There are three primary RGM approaches¹ CPG companies can take to consolidate their data and achieve more profitable outcomes. 

Strategic RGM

This approach focuses on leveraging data that understands trends in category sales, taking into account possible influences on region, consumers, customers, and promotional effectiveness. It can be used to help expand your global strategy to be relevant in different regions and markets. 

Precision RGM

This approach delves deep into the root causes of potential lost sales, enabling CPGs to develop the most effective approaches to pricing, promotion and assortment strategies. This approach is effective when you are dealing with a wide range of manufacturers, suppliers, and logistics providers and need to identify where opportunities lie to cut waste.

Extended RGM

Creating centralized spaces where data is accessible to more people than before, makes this approach critical to scaling your RGM capabilities internally and enhancing access to insights. This enables a greater volume of people in your organization to learn from historical performance and develop improved strategies that drive sustainable growth. 

Precise data = optimized decisions 

So how can you achieve more? Equip your RGM strategy with multiple integrated data sources and clear data pipelines, and you’ll be on the right path to faster, more precise revenue growth. The benefit? Smarter segmentation and targeted strategies to drive more profitable outcomes.

Relying solely on data from ERP systems offers a limited perspective, while broadening your data sources enriches your dataset. At Retail Insight, we’ve designed the modular RGMInsight solution which captures data from any data source and uses advanced cognitive technology. This means you can execute all three RGM approaches in one single place, whenever and wherever you need it, using any data source for maximum flexibility. 

Find out more about how RGMInsight can help you achieve your RGM goals. 

References

¹https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/revenue-growth-management-the-next-horizon