Expertise in agentic commerce AI design, from intent recognition through checkout orchestration
Retail & Commerce
Turning conversations into conversions
A growing e-commerce retailer experiencing strong traffic but struggling with discovery-to-checkout drop-off rates that were eroding return on significant marketing investment.
The challenge
Friction throughout the purchase journey was suppressing conversion and increasing customer acquisition cost:
- Customers abandoning product discovery due to poor search relevance and generic recommendations
- Cart abandonment elevated as customers encountered friction during purchase decision-making
- Support queries during purchase journeys going unanswered, causing hesitation and drop-off
- Customer acquisition costs rising while conversion rates failed to improve proportionally
- No scalable mechanism to deliver personalized, guided shopping experiences at volume
The solution
JBS developed an AI agentic shopping assistant enabling:
- Natural language product discovery enabling customers to find what they need through conversation
- Guided purchase journey flows taking customers from initial inquiry through to checkout completion
- Real-time intent detection identifying buying signals and responding with contextually relevant offers
- Proactive engagement at known drop-off points in the purchase funnel before customers abandon
- Seamless integration with product catalogue, inventory, and checkout infrastructure
The business impact
- Conversion rates improved across AI-assisted customer journeys versus unassisted browse sessions
- Cart abandonment reduced through proactive, intelligent assistance at high-friction purchase moments
- Average customer interaction quality elevated through personalized, conversational guidance
- Customer support load reduced as the assistant handled product and purchase queries independently
- Scalability of customer engagement achieved without proportional growth in support staffing
Results achieved
- Conversion rates improved measurably across AI-assisted browsing and purchasing sessions
- Cart abandonment meaningfully reduced through intelligent, timely engagement at friction points
- Customer engagement scalability achieved without headcount growth in support operations
Why JBS
Experience integrating conversational AI with e-commerce infrastructure including catalogues and payments
Human-centered design ensuring AI interactions feel helpful and trust-building, not disruptive
Outcome-focused delivery with conversion improvement as the primary success measure
AI shopping assistant for guided discovery and checkout
The AI shopping assistant guides customers from natural-language product discovery through comparison to checkout completion. As one of the new generation of AI-powered shopping assistants, it detects buying intent in real time and intervenes at known drop-off points before customers abandon their carts.
Best practices for optimizing product descriptions for AI shopping assistants
To get the most from AI shopping assistants, product data has to be machine-readable. Best practices for optimizing product descriptions for AI shopping assistants include: 1) lead with the specific product type and key attributes; 2) use consistent, structured fields for size, material, and compatibility; 3) write in plain language the model can match to customer questions; and 4) keep inventory and pricing synchronized so recommendations stay accurate.
Frequently asked questions
What is an AI shopping assistant?
An AI shopping assistant is a conversational agent that helps customers find, compare, and buy products through natural dialogue. JBS built one as an agentic system that not only answers questions but completes the guided journey to checkout, improving conversion and reducing cart abandonment.