Retail & Ecommerce
Find and fix friction that costs you sales
Shoppers don’t explain why they leave. Fullstory shows you exactly where they struggled, so your team can step in, fix what’s broken, and keep it from happening again.
Find hidden friction
Spot where shoppers struggle—broken fields, slow load times, payment errors your funnel data never captures.
Recover lost revenue
Trigger guides, surveys, and context-aware AI agents the moment shoppers hit a wall so you can assist before they leave.
Build shopper confidence
Reproduce bugs from real sessions, prioritize by revenue impact, and give AI agents the context to intervene before it happens again.
Built to work with the tools you use
Skip the back-and-forth entirely
Fullstory provides Fin with a complete session summary the moment a shopper reaches out. Diagnosing the issue and resolving it without a human handoff.
More issues are closed before they reach the queue
Session signals give Sierra what it needs to triage and resolve issues, so more conversations close before they reach a human queue.
Power a digital personal shopper
Behavioral data flows into Google Cloud to build a proactive shopping assistant that understands intent and guides shoppers through buying decisions.
79% of tickets resolved—how Ninety.io made Fin a smarter agent
“We all experience AI fatigue; AI interactions can feel less friendly. They lack the conversational warmth of a human touch. This is something we didn't realize we were missing. Fullstory adds a layer that makes Fin a more personable and friendly experience for our clients."
What retailers are building
The right product, before they search
Quantiphi used behavioral signals to build a co-shopping assistant that guides shoppers to the right product.
Behavioral data as a merchandising roadmap
Slalom relied on behavioral data to validate friction and deliver a concrete roadmap for improving product discovery.
Resolve the moment before shoppers leave
When payment failed, Fin read the behavioral context, stepped in autonomously, and resolved the issue before abandonment.
Data & analytics teams