AnswersRetail
In short
Retailers use AI across the chain from merchandising to the store: forecasts and inventory placed by location, prices that follow demand, product content written at scale in the brand's voice, staff scheduled to real traffic, and customers and store teams answered in seconds. Merchants and store managers approve the decisions, on one model of products, stores and customers.
| Area | What AI does | See it running |
|---|---|---|
| Demand and inventory | Forecasts by store and item and moves stock before it runs short. | Inventory rebalancing |
| Pricing | Recommends prices and markdowns from demand, stock and competition. | Dynamic pricing for retail |
| Product content | Writes and updates product pages and campaigns in the brand's voice. | Marketing campaign optimization |
| Store workforce | Schedules staff to forecast traffic and tasks. | Retail workforce planning and scheduling |
| Customer service | Answers order, return and product questions across channels. | Customer service engine |
| Frontline support | Gives store teams answers on procedures and stock by voice or chat. | Field workforce assistant |
Purchase history, loyalty and service records are a retailer's own advantage. Keeping them in the retailer's environment, with access controlled and every action recorded, lets agents use that history without handing it to a supplier. Fig runs on CosmOS in the retailer's own cloud or Fig's, connected to commerce, inventory and loyalty systems in place.
Pick one decision with a clear number, such as stockouts, markdown rate or labor as a share of sales, build it on the shared model of products and stores, and expand from there.
Agents recommend prices and markdowns within rules the merchants set, and changes above set limits go through approval.
It answers procedure and stock questions by voice or chat, builds schedules around traffic and logs tasks as they are done.
Stockouts, inventory turns, markdown rate, conversion and labor as a share of sales, each against a baseline.
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