AI Commerce Intelligence for Retail

Find the store-level actions that improve sell-through.

In-store analytics connects physical store, POS, inventory, and local demand data. Path Analytics compares store performance against expectations and explains where revenue is at risk.

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Store-level sell-through Store benchmarking Revenue-at-risk alerts

Store performance: connected data informs expected performance, with evidence and a recommended action for team review.

Store Operating Decisions

Turn store data into local actions.

AI-assisted decision support for store, district, and regional leaders managing performance, local demand, inventory movement, and field execution.

Spot Underperforming Stores

Help regional managers compare sell-through with expected performance for similar stores, regions, and categories. Investigate gaps that a chain average can hide.

Review Aging Inventory

Review inventory age alongside local demand. Decide which items to keep, transfer, or list online.

Understand Local Conversion

Where footfall data is connected, compare visits with POS conversion to investigate local demand and pricing gaps.

Find Customer Opportunities

Use basket patterns, customer behavior, and local assortment to review targeted upsell opportunities.

Compare Store and Online Demand

Connect store-specific online sales and consignment context to see where inventory can better serve demand.

Analyze Anything

Start with a store KPI, trend, or action. See what is working, what is not, and the recommended course of action.

For merchandising, planning, and allocation teams →

Store Performance in Context

Why is Store #114 missing demand while stock is available?

Analyze Anything: start with a KPI, trend, or action to understand what is working, what is not, and what to do next.

Performance gap

Store #114

Sell-through is below expected performance for comparable locations while local demand and stock are available.

Connected coverage: POS & store sales, local demand & inventory

Path Analytics recommendation

240 units

Review a DC transfer to Store #114 after checking DC availability and the needs of other stores.

Built-in AI: explains the store gap with expected performance & evidence

Team review and checkpoint

Store + Operations

Inventory Operations confirms availability. Store Operations executes the transfer, then leadership checks sell-through after 7 days.

Team decision: store + inventory operations, reviewed action & checkpoint

How It Works

From a store performance gap to a reviewed action.

Path Analytics surfaces the gap and recommends the next action. Your team decides, acts, and reviews.

Connect

Unify POS, inventory, ecommerce, and store sales data.

Detect

Find expected-versus-actual gaps using market and local demand context.

Recommend

Surface the best-supported actions and estimated opportunity.

Act & Review

Make the change, then review the observed impact at the agreed checkpoint.

In-depth store analytics, benchmarked against what the market supported. Drill from store performance into channels, categories, subcategories, products, and SKUs — with expected-versus-actual performance visible at every level.

Retail Teams

See the next action for your stores.

Walk through a store comparison, the inventory behind the gap, and a recommendation your team can review.

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