Omnichannel Retail Analytics

Stop inventory from getting stuck in the wrong channel.

Connect inventory, listings, sales, fulfillment, returns, and channel costs across stores, ecommerce, marketplaces, and wholesale. Path Analytics shows where demand is forming, where inventory is sitting, and whether the next channel move supports sell-through and profitability before your team acts.

Inventory vs. demand by channel Store + ecommerce visibility Channel profitability Team-reviewed inventory moves
Cross-channel intelligence: connected data informs demand & margin context, with evidence and a recommended action for team review.
What Is Omnichannel Retail Analytics?

See each channel. Compare across channels. Coordinate the next move.

This is operational retail analytics across inventory, demand, sell-through, fulfillment, and profitability — not only marketing attribution or the customer journey. Store, ecommerce, inventory, and warehouse teams work from the same connected view.

Understand Each Channel

See inventory, sales, listings, sell-through, and demand within stores, owned ecommerce, marketplaces, and wholesale operations.

Compare Cross-Channel Demand

Compare expected and actual demand across channels, including online sales attributed to a specific store, to see where products are converting.

Match Inventory with Demand

Find where inventory is sitting, where demand is active, and which store, ecommerce, or marketplace channel may need the stock next.

Protect Channel Profitability

Compare margin, fees, fulfillment costs, return pressure, and store availability before recommending an inventory move.

Close the Operating Loop

Feed fulfillment, delivery, and return outcomes back into the next channel, listing, and inventory-placement decision.

Ask Across the Business

Ask in familiar retail language why a product sells in one channel but not another, what is driving the gap, and which action the team should review.

Bridge Decisions

Why is this SKU converting online but sitting idle in-store?

Channel teams see where demand is growing. Store, inventory, and warehouse teams see the stock, margin, fulfillment, and availability evidence behind the recommended move.

Store #22Inventory sittingSell-through below expected performance
Path AnalyticsCompare before movingDemand · margin · fees · fulfillment
MarketplaceDemand growingChannel profitability remains visible
Shared decisionChannel + Warehouse Operations review the move
01
Performance gap
Store #22

The SKU trails expected store sell-through while marketplace demand grows. Compare stock availability, listings, fulfillment, and returns to explain the gap.

02
Path Analytics recommendation
180 units

Review a transfer from Store #22 after checking store availability, channel margin, fees, and fulfillment costs.

03
Team review and checkpoint
Channel + Warehouse Operations

Warehouse Operations confirms available stock and fulfillment constraints. Channel Operations reviews and executes the move, then leadership checks sell-through, channel profitability, and store availability after 14 days.

How It Works

From cross-channel signal to a coordinated action.

Path Analytics compares channel performance and recommends the next move. Your team reviews and executes the action. Here's what powers the recommendation, what it improves, and how the AI stays grounded.

What data powers omnichannel retail analytics?Available POS, store-attributed online sales, ecommerce, marketplace, wholesale, inventory, listing, order, fulfillment, return, and channel-cost data from supported systems.
How is this different from marketing analytics?It connects customer and sales signals with inventory, sell-through, fulfillment, returns, and channel profitability so operating teams can decide what to do next.
What does it improve?Teams catch demand shifts, protect store availability, and review where inventory is most likely to sell profitably.
Who reviews the action?Store, ecommerce, channel, inventory, and warehouse teams review the evidence, decide whether to act, and check the outcome.
How does AI use omnichannel data?Ask about a channel gap in familiar retail language. Path Analytics explains what changed and why, then recommends an action with an owner and checkpoint.
Core + Extensible

One shared retail context for your teams and AI.

Build on your existing POS, ERP, and ecommerce systems. Path Analytics adds shared retail definitions, expected performance, and evidence so operators, leaders, and supported AI assistants can work from the same context. Use built-in AI today and extend to new agentic commerce workflows with fewer separate integrations and less duplicated business logic.

See how AI assistants connect to Path Analytics →
Omnichannel Teams

Bridge demand, inventory, and execution across channels.

See how Path Analytics helps store, ecommerce, inventory, and warehouse teams align stock with demand while protecting sell-through, availability, and channel profitability.

Request a demo

Leave your email. We’ll contact you to arrange a walkthrough.