As their products have such a high turnover rate, it's unsurprising that the consumer packaged goods (CPG) industry is the fastest moving. But this creates unique challenges in the value chain, such as managing rapid changes in consumer behavior, mitigating supply chain risks, and maintaining profitable growth.
This is where revenue growth management – the decisions made on pricing, products, placement, and promotions – becomes extremely important. In fact, revenue growth management is responsible for 70% of the organic growth of CPG companies.1 But in a world where AI is disrupting every industry, CPG companies must rethink revenue growth management and bring in AI to not only meet but also exceed sales targets, increase market share, and boost brand loyalty.
In this blog, we'll outline three major challenges CPG companies face in revenue growth management and how AI can help.
Challenge 1: Fragmented and underused data
Most CPG companies have limited point-of-sale data or struggle with data silos internally. This means they are often manually creating insights for revenue growth management. Why? Because a lack of connected and quality data makes it almost impossible to apply AI and other technology for smarter decision-making.
How AI can help
Data quality: Agentic AI can industrialize data quality. Think of these intelligent AI agents as an extension of your team. Alongside employees' expertise, they can learn, adapt, and make autonomous decisions for cleansing and collating data based on real-world feedback, generating insights, sharing recommendations, and acting on business KPIs
User-friendly insights dashboards: AI tools can transform the decision-making experience by creating intuitive dashboards for employees. Think of a ChatGPT-style experience where you can ask for insights into consumer, market, and product trends to strengthen your revenue growth management strategy
Challenge 2: Rising costs and price pressure
Changes in raw material prices, fluctuating tariffs, and rising operational expenses have hit CPG revenue hard. But CPGs need to make sure these costs aren't passed on to consumers if they want to protect profits.
How AI can help
Price pack architecture: Rising costs put huge pressure on the bottom line for CPG companies. They must continually resize products while considering consumer needs, price sensitivity, and channel strategies. AI can help structure the product portfolio to maximize sales, profitability, and consumer appeal to make sure the consumer doesn't feel shortchanged while revenue still grows steadily
Cost prediction models and dynamic pricing: AI-powered algorithms can analyze market trends, supplier data, and historical costs to forecast price fluctuations. AI tools can then adjust pricing in real time based on demand, inventory, and competitor actions to keep profitability intact. This is very useful for CPG companies that have products with seasonal peaks and troughs
Challenge 3: ROI of promotions
Today's consumers tend to buy either premium products as a treat or white-label (also known as own-brand) products to cut costs. Plus, spending habits change all the time, so if a CPG company simply reuses trade promotions from the previous year, they're unlikely to have much success. It all comes down to spending trade funds on the right promotion at the right time with the right ROI.
How AI can help
Consumer behavioral analytics: By mining point-of-sale data and online spending trends, AI can identify emerging purchasing behaviors and help businesses adjust or launch customized promotions faster than ever
- Real-time insights for promotional trade spend: AI can effectively manage a variety of data types and tailor promotional discounts while considering product cannibalization. Promotions can then shift from blanket tactics to highly targeted incentives using real-time shopper insights
- Promotion effectiveness evaluation: Many CPG companies lack the data and resources needed to fully evaluate the ROI of promotions. With help from AI, these companies can structure data for analysis of promotions both before and after sales
As the CPG industry evolves, sticking to traditional methods for revenue growth management is no longer an option. It's why the leading companies are also starting to experiment with agentic AI – because success belongs to those ready to adopt an approach that places AI at the heart of decision-making.
