Globalpraxis and artificial intelligence: Pricing

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Pricing is a field where artificial intelligence is bringing massive changes and improvements, with pricing strategy being one of the key concerns raised today by most of our clients. AI is increasingly utilized in pricing strategies and management to optimize decisions, enhance competitiveness, and maximize profits. For fast-moving consumer goods industries – with muti-channels, mutli-occasions, complex packaging offers –, the role of dynamic pricing is becoming critical. Dynamic pricing allows companies to adjust prices in real time, based on factors such as demand, competition, inventory levels, and even customer behavior. Retailers, for example, have a net competitive advantage as they can implement dynamic pricing in real time with their own brands.

Artificial intelligence helps also in demand forecasting. Specific algorithms can analyze vast amounts of historical sales data and other information to forecast future demand accurately. For beverages, seasonality is a critical element that can be addressed specifically. AI will help businesses set optimal prices to match demand fluctuations.

Like hyper-personalization, addressed in our last article, AI can help managers create personalized pricing; in other words, the right price, for the right product or service, on the right occasion for the right customer, based on individual customer behavior, preferences, purchase history, and other relevant data points. This approach can improve customer satisfaction, increase revenues, and above all, customer loyalty. In fact, above and beyond the pricing issue, AI plays a significant role in churn prediction – an issue to be addressed in our discussion of AI and customer segmentation – and prevention for businesses. By analyzing vast datasets of customer behavior, AI algorithms can identify patterns and signals that indicate when a customer is at risk of churning. These signals can include factors such as decreased usage, changes in purchasing behavior, or sentiment analysis of customer interactions.

There is no valid business strategy without serious competitive analysis. As Michael Porter says, “Understanding the competitive forces, and their underlying causes, reveals the roots of an industry’s current profitability while providing a framework for anticipating and influencing competition…” This is the case with pricing strategy. AI plays a very important role here. AI tools can continuously monitor competitor pricing strategies and market trends, providing valuable insights for adjusting pricing and staying competitive.

The critical task of a manager is to optimize pricing across product lines, channels, and geographies. AI supports the analysis of constraints and objectives such as revenue maximization, share growth, channel relevance, or margin improvement. The optimization algorithms are used extensively today in airlines, telecoms, banking and financial services, and retail and are gaining traction in FMCGs.

To be sure, AI is creating a real revolution in pricing management.