Written By: Gargi Sarma
Artificial intelligence (AI) breakthroughs drive a huge revolution in the consumer packaged goods (CPG) industry. Artificial Intelligence (AI) transforms pricing tactics by enabling merchants to optimize prices, boost consumer pleasure, and improve profitability. AI can evaluate large volumes of data in real-time. This paper examines how artificial intelligence (AI) is changing consumer packaged goods (CPG) pricing tactics, including retail examples to bolster the findings.
The AI Pricing Boom Market Size: According to Grand View Research, the worldwide AI in pricing market is expected to expand at a compound annual growth rate of 20.4% from 2023 to 2028, reaching $12.7 billion.
Adoption Rate: Compared to industries like retail and e-commerce, the CPG business is still in the early phases of adopting AI, although there is a rising awareness of its potential. Only 20% of CPG businesses have used AI-driven pricing solutions, according to a recent McKinsey report, while 70% are considering the possibility.
Investment: Major CPG companies are making significant investments in data analytics and artificial intelligence. Leading the way are businesses like Nestle, Unilever, and Procter & Gamble.
Figure 1: Digital and AI Impact Varies by Sector
The Role of AI in Pricing Strategies
AI enhances pricing strategies in the CPG industry with several important capabilities:
Dynamic Pricing: To dynamically modify prices, AI algorithms may evaluate rival pricing, customer demand, and real-time market data. In doing so, pricing is guaranteed to stay competitive while income is maximized.
Predictive Analytics: Artificial Intelligence (AI) can forecast future product demand by examining past sales data and industry patterns. This lowers the possibility of overstocking or stockouts by assisting merchants in setting pricing that corresponds with anticipated market circumstances.
Personalized Pricing: Retailers are able to provide customized prices and promotions by using AI to segment their consumer base depending on their preferences and shopping habits. This promotes repeat business and fosters client loyalty.
Competitive Pricing Intelligence: For CPG businesses, monitoring rivals' prices is crucial. Artificial intelligence (AI)-powered solutions can continually track the prices and market circumstances of rivals, giving real-time insights that guide pricing decisions. This keeps businesses competitive and enables them to react swiftly to changes in the market.
Optimization of Promotional Strategies: AI has the ability to assess the success of previous campaigns and provide the best price plans for the next ones. Retailers may accomplish greater outcomes and more efficient use of their promotional money as a consequence.
Figure 2: Top AI Use Cases in CPG
Examples:
Here are some key ways AI is transforming pricing strategies, along with retail examples:
Walmart employs AI to execute dynamic pricing techniques, which modify prices in real-time in response to a range of factors, including competition, demand, and inventory levels. Walmart can ensure competitive pricing and maximize revenues by optimizing prices for millions of goods across several locations through extensive data analysis.
Amazon uses AI to provide its consumers with customized deals and prices. Amazon enhances the buying experience and increases customer loyalty by customizing its pricing methods to each consumer based on their browsing habits, past purchases, and demographic information.
Target determines the optimal pricing points for their items using AI-driven price optimization techniques. These programs provide the best rates by weighing sales volume and profitability by analyzing competition pricing, market trends, and previous sales data. Target is able to satisfy customer expectations and maintain its competitiveness with this method.
Kroger uses artificial intelligence (AI) to improve its promotional pricing tactics. Kroger may create tailored promos that are more likely to appeal to particular consumer categories by examining purchase trends and customer data. This focused strategy reduces needless discounting while simultaneously boosting the efficacy of promotions.
Unilever predicts future sales patterns and modifies pricing in accordance with them using demand forecasting models driven by AI. With the use of these models, Unilever is able to better inform its pricing choices and better match supply with demand by taking into account a variety of factors such as macroeconomic data, marketing campaigns, and seasonality.
P&G uses artificial intelligence (AI) to track rival prices in real-time and modify its own pricing policies appropriately. P&G is able to maintain its agility in a very competitive market by using competitive pricing research to make sure that its goods continue to be priced competitively with those of its rivals.
Macy's uses AI to maximize markdown pricing and control inventory levels. AI algorithms can suggest the best markdown schedules and discount levels based on sales data and inventory turnover rates, assisting Macy's in cutting surplus inventory while preserving profitability.
Costco improves its membership price structure with AI. Costco may provide tailored offers and discounts that enhance the value of its membership program, enticing new members and promoting renewals by examining the buying patterns and preferences of its customers.
Figure 3: Digital and AI Maturity Scores for Individual Companies Show Significant Spread Within Each Sector
Challenges and Considerations:
Data Quality: The caliber of the data used to train AI models determines how accurate the models will be.
Ethical Concerns: The fairness and discrimination of personalized pricing may give rise to ethical questions.
Costs Associated with Implementation: AI-driven pricing solutions may need large sums of money for both personnel and technology.
Acceptance by Customers: If customers believe that tailored pricing is unjust or deceptive, they may reject it.
Benefits of AI-Driven Pricing:
Increased Revenue: Retailers can increase revenue by customizing offerings to consumers and optimizing prices.
Increased Profit Margins: AI lowers expenses and finds possibilities for pricing, which increases profit margins.
Enhanced Customer Satisfaction: Customized pricing can improve client relations and foster a stronger sense of loyalty.
Faster Decision-Making: More educated and expedient pricing decisions are made possible by AI-powered insights.
Competitive Advantage: Organizations may outmaneuver rivals and obtain a competitive edge by utilizing AI.
Leveraging Gen AI for Advanced Insights
With its cutting-edge insights and suggestions, generative artificial intelligence, or Gen AI, is further revolutionizing the CPG industry. Gen AI is able to simulate different market scenarios and provide possible results, in contrast to standard AI models that evaluate data that already exists. With the use of this capacity, CPG businesses may investigate various pricing approaches and evaluate the possible outcomes before to putting them into practice.
A CPG Company, for example, might utilize Gen AI to model how a price rise will affect a particular product line while taking into account the activities of competitors, customer behavior, and market circumstances. By lowering risks and optimizing income, this proactive strategy assists businesses in making well-informed pricing decisions.
Figure 4: Generative AI in the CPG Market
RapidPricer's RASPER:
RASPER (RapidPricer Automation as a Service for Pricing in E-commerce and Retail) is one of the most innovative AI-driven pricing solutions. Using just 12 weeks of data, RASPER provides quick pricing suggestions on any device, assisting CPG firms in automating pricing and promotion choices in real-time. RASPER ensures that price choices are efficient and successful by eliminating the need for complicated integrations and a large amount of historical data, freeing up category managers to concentrate on strategic operations.
Conclusion:
AI is revolutionizing pricing methods in the consumer packaged goods (CPG) industry by facilitating trade promotion optimization, competition research, individualized pricing, precise demand forecasts, and dynamic price optimization. These developments are supporting CPG firms in being more profitable, more customer-satisfied, and competitive in a market that is evolving quickly. AI is predicted to have a greater influence on pricing tactics in the CPG sector as it develops, spurring efficiency and innovation in the sector as a whole.
About RapidPricer
RapidPricer helps automate pricing and promotions for retailers. The company has capabilities in retail pricing, artificial intelligence, and deep learning to compute merchandising actions for real-time execution in a retail environment.
Contact info:
Website: https://www.rapidpricer.com/
Email: info@rapidpricer.nl
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