Generative AI can make the customer journey more efficient—for both retailer and shopper.
Before generative AI
After generative AI
Retail customer journey
Selection of items and quantity
Manually comparing each product across multiple dimensions (eg, price, quality, reviews and ratings, size)
Order confirmation, delivery date selection
Navigating through multiple checkout pages, entering delivery and payment information, and choosing from limited delivery slots that may not align with the customer’s schedule
Product usage
Analyzing online reviews and web forums to gain insights into product usage methods
End-to-end value chain
Independent decision making by individual functions, leading to a recurring cycle of searching for the underlying causes of commercial events, often failing to identify the true underlying factors
Search for required items
Time-consuming browsing through multiple categories and filters online to find the right SKU
Creation of purchase list
Manually creating the purchase list, relying on customer memory or experience
Purchase idea and context
Manually searching across multiple sources, or ideating independently
End-to-end value chain
End-to-end optimization of decision making across the value chain through faster, more precise, and personalized insights from structured and unstructured data sources, fueling decision on pricing, promotions, stock allocation, digital marketing, and other levers of performance
Product usage
Recommendations for videos, production usage insights, and step-by-step instructions, tailored to customer context
Order confirmation, delivery date selection
Confirmation of order and specifying delivery preferences in a conversational style (eg, “Please deliver this order to my mother‘s address on any day except Wednesday”)
Selection of items and quantity
Adaptation of basket for customer needs, including smart comparisons of products, considering factors from unstructured data (eg, style, customer and market reviews)
Search for required items
Generative AI intelligently navigates through catalogs to find items that perfectly match the customer’s purchase history and preferences
Selection of preferred retailer
Generative AI minimizes switching, as the customer is already shopping in the retailer’s app
Creation of purchase list
Generative AI agent provides an accurate shopping list that includes the items/ingredients needed for the purchase idea
Purchase ideas and context
Customer provides brief context
Generative AI agent understands the intent and offers suggestions based on preferences
Selection of preferred retailer
Choosing based on past experiences or spontaneity—hard to control
McKinsey & Company
McKinsey & Company