cmo-intelligence

You can build a digital-shelf intelligence app in Snowflake by conversationally provisioning a Streamlit cockpit, a Cortex agent, and analytics views using live web data ingested through the Nimble integration.

Digital-shelf intelligence monitors retail brands by ingesting live web data on pricing, availability, and sentiment across retailers. It uses a Cortex agent and analytics views to analyze SERP and PDP data for specific categories.

Yes, you need the Nimble and Snowflake integration to ingest live web data. The workflow uses the NIMBLE_AGENT_RUN UDTF to collect SERP and PDP data for monitoring retail pricing and product availability.

Yes, you can use Cortex Code and Streamlit-in-Snowflake to analyze retail brand sentiment. The automated setup provisions a branded Streamlit cockpit and a Cortex agent for in-depth analysis of live web data.

To set up retail category monitoring for specific brands, run the skill with your desired category and brand parameters. This provisions an app that tracks pricing and availability across retailers like Amazon, Walmart, and Target.

Using Streamlit-in-Snowflake for digital-shelf analytics requires Cortex Code and the Nimble integration for data ingestion. The analytics app depends on these native Snowflake components to function properly for retail intelligence workflows.