Dynamic Pricing and Hyper-Personalization: Generative AI in Grocery and Convenience Retail

Grocery and convenience retail operate in one of the most demanding and dynamic environments in commerce. With razor-thin margins, extreme price sensitivity, rapid inventory turnover, and the expectation for real-time, personalized experiences, retailers in this sector face unique challenges—and opportunities. Generative and conversational AI are now at the forefront of addressing these challenges, enabling a new era of dynamic pricing and hyper-personalized customer engagement that is transforming the industry.

Generative AI refers to advanced machine learning models capable of creating new content—text, images, recommendations, and more—by learning from vast datasets. Unlike traditional automation, generative AI brings a human-like ability to converse, recommend, and create, allowing retailers to move beyond static, one-size-fits-all interactions. In grocery and convenience, this means:

• Conversational shopping assistants that help customers build grocery lists tailored to dietary needs, budget, and purchase history.
• Dynamic pricing engines that optimize prices in real time, reduce waste, and respond to market shifts—often via electronic shelf labels (ESLs).
• Hyper-personalized offers and content that drive loyalty and increase basket size.

Today’s grocery and c-store customers expect seamless, relevant experiences—whether they’re shopping online or in-store. Generative AI makes hyper-personalization a reality by:

• Analyzing customer data (purchase history, dietary preferences, regional trends) to generate individualized product recommendations, recipes, and offers.
• Powering conversational commerce through AI-driven chatbots and virtual assistants that guide shoppers from discovery to checkout, answer questions, and make tailored suggestions in natural language.
• Automating content creation at scale, from product descriptions to personalized emails, ensuring consistency and relevance across channels.

For example, grocers can deploy generative AI bots that allow shoppers to create grocery lists based on their budget, dietary restrictions, and past purchases through a simple conversation. These assistants can suggest recipes, recommend substitutions, and even highlight local promotions—offering a more tailored and valuable experience than generic search tools. As inflation and economic pressures shape consumer behavior, shopping assistants that help customers save both time and money will stand out in the market.

Price sensitivity is especially acute in grocery and convenience retail, where small changes can have a significant impact on customer loyalty and margins. Generative AI-powered dynamic pricing engines analyze real-time demand, inventory levels, competitor pricing, and product expiration dates to recommend optimal price points. This enables:

• Real-time price adjustments that keep prices competitive while protecting margins.
• Automated markdowns for products nearing expiration, reducing food waste and improving profitability.
• Implementation via electronic shelf labels (ESLs), allowing for instant, store-wide price updates without manual intervention.

Major retailers are already leveraging ESLs and dynamic pricing algorithms to enhance both the customer experience and operational efficiency. For c-stores, where customers are highly price sensitive, these tools ensure prices remain attractive without alienating loyal shoppers through sudden or extreme changes.

While the dream of a fully conversational, end-to-end grocery shopping assistant is still evolving, leading grocers are already experimenting with generative AI in practical, high-ROI applications:

• Personalized recipe and shopping list generation: AI-powered assistants suggest meal plans and automatically build shopping lists, factoring in dietary needs, budget, and purchase history.
• Smart carts and in-store experiences: AI-enabled carts tally prices in real time, recommend available coupons, and streamline checkout.
• Dynamic pricing and waste reduction: ESLs powered by AI automatically discount products approaching expiration, reducing shrink and improving margins.

These innovations are not just theoretical—retailers are seeing measurable gains in engagement, efficiency, and revenue by moving beyond pilots to scalable, enterprise-grade solutions. For example, clients adopting advanced AI-driven dynamic pricing platforms have reported revenue increases of up to 8% and profit improvements of 3-5% within the first few months of implementation.

Unlocking the full potential of generative AI in grocery and convenience retail requires more than technology. Key success factors include:

• Data quality and integration: Generative AI models thrive on clean, unified customer and operational data. Many retailers struggle with fragmented or unstructured data, making investment in data strategy and governance essential.
• Ethical and responsible AI: Transparency, fairness, and privacy are critical. Retailers must establish clear policies, avoid bias, and ensure customers know when they’re interacting with AI.
• Change management and upskilling: Integrating generative AI into workflows requires new skills and ways of working. Training and upskilling teams is essential for successful adoption.

For grocery and c-store leaders, the journey to generative AI maturity starts with focused micro-experiments—testing high-impact use cases like conversational shopping assistants or dynamic pricing in specific categories or stores. Success depends on building robust data foundations, integrating AI into core business processes, and implementing strong governance to balance innovation with risk.
Retailers that act now—investing in data, talent, and strategic experimentation—will define the next era of grocery and convenience retail. Generative AI is not just a technological leap; it’s a strategic imperative for those seeking to thrive in a rapidly changing landscape.

Publicis Sapient is uniquely positioned to help grocery and convenience retailers unlock the full potential of generative AI. With deep expertise in digital business transformation, data strategy, and AI engineering, we partner with clients to:

• Cleanse, organize, and structure customer data for AI readiness
• Design and deploy scalable generative AI solutions tailored to business objectives
• Implement robust governance and ethical frameworks
• Upskill teams and drive change management for successful adoption

Our proven methodologies, including micro-experiments and scalable pilot programs, help retailers move beyond proof of concept to measurable ROI. Whether you’re looking to enhance personalization, optimize pricing, or reimagine the customer journey, Publicis Sapient can guide your generative AI transformation every step of the way.

Ready to transform your grocery or convenience retail business with generative AI? Connect with our experts to start your journey toward smarter, more engaging, and more profitable retail experiences.

Relevant Links

• Three Opportunities for Conversational AI in the Consumer Packaged Goods Industry
• Three Opportunities for Conversational AI in the Consumer Packaged Goods Industry
• Regional Spotlight: Conversational AI Adoption in EMEA and APAC CPG Markets
• Composable Architecture and AI: Unlocking Agility for Consumer Products and Retail
• IA Generativa en el Retail y CPG de América Latina: Hiperpersonalización y Precios Dinámicos para la Nueva Era del Consumo (LATAM)
• Générative IA dans le secteur des produits de grande consommation en Europe : Hyper-personnalisation et tarification dynamique (Europe)