Generative AI for Retail Analysts

1000+ GenAI Prompts for Retail Decision-Maker

Generative AI for Retail Analysts
Generative AI for Retail Analysts

Generative AI for Retail Analysts free download

1000+ GenAI Prompts for Retail Decision-Maker

This course provides a comprehensive exploration of how Generative AI is transforming the retail industry through intelligent automation, enhanced personalization, and real-time decision support. Participants will begin by understanding the foundational technologies behind Generative AI, including Large Language Models (LLMs), Diffusion Models, and Transformer architectures. Emphasis is placed on the role of Generative AI in modern retail data analytics, especially in contrast to traditional predictive AI methods.

Learners will master the art of prompt engineering, including crafting effective prompts, using zero-shot, one-shot, and few-shot learning, and deploying reusable prompt templates for daily analytics tasks. Through applied exercises, participants will use Generative AI to create customer personas, analyze basket and journey data, and implement churn prediction with tailored messaging strategies.

The course then shifts to merchandising and inventory, where Generative AI is applied to generate product descriptions, identify substitution patterns, and optimize shelf layouts. It also covers demand planning through stockout/overstock simulations, EOQ and reorder point narratives, and forecasting with external signals such as weather and events.

Advanced modules focus on pricing and promotions, including markdown strategy generation, dynamic pricing simulations, and campaign ROI analysis. Sentiment analysis using LLMs, competitor pricing intelligence, and social media trend mining are also integrated to enhance competitive positioning.

Operationally, learners will auto-generate executive summaries, charts for dashboards, and query business data using natural language. Finally, the course explores the deployment of AI-powered store assistants, FAQ bots, and CRM-integrated POS chatbots to enhance in-store efficiency.

Case studies from Amazon, Target, and Sephora highlight real-world applications, while a curated collection of 1000+ Generative AI prompts equips learners to apply these methods across the retail analytics spectrum.