> ## Documentation Index
> Fetch the complete documentation index at: https://docs.wayak.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Retail

> Optimize inventory, measure promotions, and benchmark store performance with AI agents

Retail teams need real-time visibility into stock levels, sales trends, and promotion performance across locations and channels. But the data lives in separate systems — POS, inventory management, supplier portals, and merchandising platforms — making it slow and painful to answer basic questions like "what should we reorder today" or "did that promotion actually work."

Wayak connects your retail data sources, layers business logic through a semantic layer, and deploys agents that monitor inventory, analyze promotions, and benchmark performance automatically. Playbooks handle the daily and weekly analysis that used to require a dedicated analyst pulling reports from three different systems.

## Use cases

<CardGroup cols={2}>
  <Card title="Restock recommendations" icon="boxes-stacked" href="/use-cases/retail/restock-recommendations">
    Monitor stock levels daily, calculate days of supply, and generate reorder suggestions before stockouts happen.
  </Card>

  <Card title="Promotion performance" icon="tag" href="/use-cases/retail/promotion-performance">
    Measure revenue lift, margin impact, and cannibalization after every promotion to learn what actually drives incremental sales.
  </Card>

  <Card title="Product assortment optimization" icon="magnifying-glass" href="/use-cases/retail/product-assortment-optimization">
    Identify top-performing and underperforming SKUs across categories to guide buying decisions and markdown strategy.
  </Card>

  <Card title="Price elasticity monitoring" icon="chart-line" href="/use-cases/retail/price-elasticity-monitoring">
    Track how price changes affect unit volume and margin so you can set prices that maximize revenue without killing demand.
  </Card>

  <Card title="Store benchmarking" icon="gauge" href="/use-cases/retail/store-benchmarking">
    Compare locations against each other on sales, conversion, inventory turns, and labor productivity with scheduled reports.
  </Card>
</CardGroup>

## Platform capabilities used

| Capability       | How it's used                                                                                                                                                                                                                           |
| ---------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Data sources     | POS database (transactions, line items, tenders), inventory management system (stock levels, receipts, transfers), supplier portal or ERP (purchase orders, lead times, costs), promotions database (campaigns, discounts, date ranges) |
| Knowledge spaces | Merchandising guidelines, vendor agreements, markdown policies, seasonal planning calendars                                                                                                                                             |
| Semantic layer   | Objects for SKUs, stores, suppliers, and promotions. Metrics for sell-through rate, days of supply, gross margin, and revenue per square foot. Dimensions for category, brand, store region, and promotion type                         |
| Agents           | Inventory Analyst for stock monitoring and reorder recommendations. Merchandising Assistant for product performance and assortment analysis                                                                                             |
| Playbooks        | Daily restock scans, post-promotion performance reports, weekly product rankings, monthly store benchmarking summaries, price change impact alerts                                                                                      |