---
title: "Retail"
description: "2 posts about Retail, summarised, each linking to the original."
---

# Retail
> 2 posts about Retail, summarised, each linking to the original.

## Articles

### [How Databricks Genie improves retail personalization](https://yomu.fyi/post/how-databricks-genie-improves-retail-personalization.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Sarah Duffy
- Published: May 20, 2026

Retail personalization often stalls when CX leaders must wait for analysts to answer questions about segment behavior, loyalty performance, channel preference, or churn risk, narrowing the window for action. Databricks Genie addresses this access gap by letting business users query unified structured and unstructured enterprise data in plain English instead of SQL. Its retail differentiators include identity-resolved queries across channels and devices, lifecycle-stage awareness, campaign response and control-group data integration, and privacy controls enforced through Unity Catalog. The source says Genie reduces routine analyst requests rather than replacing data science teams, while enabling merchandisers, category managers, loyalty marketers, and CX leaders to self-serve operational questions. It cites 7-Eleven’s use of Databricks SQL, Unity Catalog, and AI/BI Genie to launch, refine, and measure personalized offers within a secure, unified platform.


### [Retail markdown optimization: from reactive markdowns to proactive](https://yomu.fyi/post/retail-markdown-optimization-from-reactive-markdowns-to-proactive.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Sarah Duffy
- Published: May 11, 2026

Retail markdown optimization addresses the gap between changing demand signals and delayed merchandising action. The post defines it as strategically reducing prices on slow-moving or end-of-life inventory, using demand forecasts, sell-through rates, weeks of supply, and price-elasticity models to choose which SKUs to mark down, when to start, how deep to discount, and where to act. It presents Databricks Genie as a natural-language interface across e-commerce, store, and wholesale data, with supplier, margin, and historical-pattern context; one example is Coop’s Microsoft Teams assistant, AskCap, which reported a 30% retention rate among internal users. Earlier detection of sell-through deceleration can give merchants more time to protect margin, adjust open-to-buy, and reallocate capital, while Genie supports decisions rather than making them.