Move slow inventory before it becomes a markdown.
See where sell-through is slipping, understand why, and get the pricing, listing, or transfer action most likely to fix it.
Actions for the blockers hiding in your inventory data.
Turn slow movement into actions your team can perform and track.
Slow Movers & Aging Inventory
Catch stock aging faster than demand before it needs a markdown.
Channel & Store Mismatch
See when inventory should transfer, move online, or shift marketplaces.
Pricing & Listing Gaps
Flag stale listings, weak conversion, and markdown candidates.
Demand Forecast Variance
Compare forecast to actual sales by SKU, store, and channel.
Lister & Team Performance
See how listing quality and relisting cadence affect sell-through.
Measured Action Outcomes
Track sell-through changes after each action.
Detect, act, and measure the effect.
Path Analytics doesn't stop at a recommendation — it tracks the real-world result. Here's what sell-through lift means, how AI improves it, and who uses it.
What powers sell-through lift analytics?
Connected retail, ecommerce, inventory, and fulfillment data keeps every recommendation tied to the actual blocker.
Inventory Movement
SKU, store, channel, days listed, inventory age, and sell-through rate.
Demand & Listing Signals
Views, carts, orders, conversion, listing quality, and category demand.
Price & Outcome Tracking
ASP, margin, markdown timing, recovered revenue, and sell-through lift.
Built-in AI finds these actions today.
Built-in retail AI. Shared context for supported assistants and workflows.
Give operators clear actions they can perform and measure.
One platform for forecasting, pricing, inventory placement, and plain-English retail guidance.