As commodity prices continue to fluctuate, the pressure on retailers and consumer packaged goods (CPG) companies to remain profitable is at an all-time high.
As an example, the rising cost of cocoa affects manufacturers and retailers alike, forcing them to reevaluate their pricing strategies. Meanwhile, consumers are growing increasingly price-sensitive. In this volatile environment, businesses must adjust their operations and turn to technology to navigate these challenges effectively.
The key to success lies in leveraging advanced technology and data-driven strategies to understand core customers, apply real-time dynamic pricing strategies, optimise product portfolios, and enhance supply chain agility.
Dynamic Pricing: Balancing competitiveness and profitability
Dynamic pricing adjusts prices based on demand and market conditions, allowing retailers to stay competitive while managing margin pressures. AI-powered segmentation enables companies to quickly adjust pricing and product availability based on insights into local customer demand and purchasing patterns. By analysing big data from various sources, companies can develop granular insights into what drives purchasing decisions.
1. Leveraging AI to balance pricing and promotions
Commodity price volatility requires a real-time, data-driven approach to pricing and promotions. Retailers must identify which products are most price-sensitive and adjust strategies accordingly. AI-driven pricing optimization allows businesses to adjust prices quickly, responding to real-time market conditions, competitor pricing, and consumer demand. AI-powered promotions planning can predict the effectiveness of various strategies, ensuring they boost sales without harming long-term profitability.
2. Optimising margins through portfolio management and AI
Optimising product portfolios is essential to maintaining healthy margins. Major grocery chains often increase the availability of private-label products when commodity costs rise. By leveraging AI and predictive analytics, retailers can streamline their offerings, removing low-demand items and increasing the share of high-margin products. Machine learning models can predict shifts in consumer demand, enabling businesses to adjust production and supply chains with speed and accuracy.
3. Facilitating data-driven supply chain agility
Retailers and CPG companies must prioritise fast and responsive supply chain agility. Technologies like AI and digital twins enable businesses to simulate various scenarios to optimise decision-making. Digital twin technology helps forecast the impact of rising costs on product availability and pinpoint areas for cost-saving adjustments. AI-powered inventory management systems can optimise stock levels, reducing the need for excessive safety stock and improving agility in response to changing consumer demand.
Getting started with AI and advanced technologies
While the advantages of leveraging AI in retail and CPG are well-documented, businesses must address obstacles early to integrate these tools effectively. Challenges include data quality, security and privacy, infrastructure readiness, skill gaps, and change management. By proactively addressing these challenges, businesses can unlock the full potential of AI and advanced technologies, positioning themselves for sustainable success in an increasingly dynamic landscape.
Shortened version of Mikko’s piece in Forbes: https://www.forbes.com/councils/forbestechcouncil/2025/01/06/how-to-leverage-ai-to-conquer-price-fluctuations-in-retail-and-cpg/
By Mikko Kärkkäinen, CEO, RELEX Solutions.
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