The power of AI-ready retail data in Snowflake Intelligence

Retail data just got smarter: See how Crisp and Snowflake Intelligence are powering the next wave of AI-driven insights across retail and CPG teams.

Across digital and in-store shelves, there’s never been more rich, first-party sales and inventory data available to CPG teams. Increasingly, brands have realized that in order to leverage this data successfully, it needs to be clean and harmonized, so reporting is fast and actionable across channels. Yet achieving that level of data consistency is time-consuming and complex without the right solution. Crisp, the leading retail data company, features a Snowflake Marketplace integration, which brands are utilizing with great success to integrate a reliable flow of real-time retail data into their Snowflake instance; across major retailers and distributors including Target, Amazon, Dollar General, UNFI, and more. Snowflake serves as an ideal environment for this streamlined retail data, where it can be layered with additional data sets seamlessly.

The launch of Snowflake Intelligence – Snowflake’s AI-driven business intelligence tool – introduces next-level capabilities to organizations’ analysis of real-time retail data. What makes this pairing so powerful is Crisp’s embedded semantic layer built for the retail industry, which enriches the data sets with algorithmic models that define key metrics for CPGs and make them queryable with natural language in AI-powered LLMs. Together, the partnership empowers technical and non-technical teams across the retail and CPG sector with fast answers and revealing insights for optimal daily decision-making.

What makes this parntership so powerful is Crisp’s embedded semantic layer built for the retail industry, which enriches the data sets with algorithmic models that define key metrics for CPGs and make them queryable with natural language in AI-powered LLMs.

How AI revolutionizes retail data

Retail is one of the most complex industries undergoing digital transformation across brick-and-mortar, convenience, online, pick-up, and delivery, and more. For too long, retail supply chains have been limited by disconnected systems and inconsistent data, hindering decision-making and resulting in inefficiencies and missed opportunities. The implications of AI in retail are vast, with the potential to uncover critical insights, streamline operations, and keep the flow of goods and information running smoothly. This innovation comes at a crucial time, as the industry continues to navigate supply chain disruptions, shifting tariffs and regulations, and fierce competition across channels.

Crisp is uniquely positioned to deliver on AI’s promise in retail, with an infrastructure rooted in automated ingestion, normalization, and harmonization, providing critical structure across retail data sources. What’s more, our semantic layer built for the retail industry provides essential context and retail math to prevent AI pitfalls in retail data computation – including hallucinations, faulty calculations, and misreads of retailer-specific questions – making it an amazing contextual data stream for use in Snowflake Intelligence.

Some of the ways Crisp’s actionable data can be leveraged in Snowflake AI applications include:

• Conversational insights – Separating signals from noise in retail data can be a time-consuming and complex process. Large language model (LLM) analytics solutions like Snowflake Cortex allow users to query historical and real-time data using natural language (NLP), delivering instant insights down to the SKU and store level.

• Data science-ready AI Blueprints – For teams ready to take the next step in retail intelligence, Crisp AI Blueprints offer pre-built, data science–ready models that layer onto clean, harmonized retail data – and can be activated in Snowflake today.
  
  Notebooks include On-Shelf Availability, Store Clustering, Assortment Optimization, and a host of other models, which can quickly surface insights around retail’s most pressing challenges and accelerate AI adoption in organizations efficiently and reliably.

• AI Agents for Retail – Agentic AI introduces the next evolution of retail management. AI Agents can monitor live retail data streams, detect anomalies, and signal when it’s time to adjust plans or shipments. Planned for activation in Snowflake Intelligence, Crisp AI Agent Studio for Retail includes pre-trained AI Agents for retail-specific use cases like Monday Morning Reporting, promotion planning and execution, out-of-stock (OOS) root cause analysis, and supply chain monitoring with real-time alerts. The technology is currently deployed in Private Beta, with an available waitlist for Open Beta.

• AI-powered master data management (MDM) – Players across retail grapple with the same challenge of managing product data from dozens of sources with widely varying identifiers and detailed attributes. Reconciling product names, hierarchies, and descriptors across SKU portfolios has traditionally been a highly manual process known as master data management (MDM).
  
  AI has powerful potential to efficiently streamline and enrich MDM for cleaner, more accessible reporting across organizations than ever before. Crisp’s AI-powered MDM solution, currently in Private Beta, will be especially useful for teams leveraging retail data across the suite of Snowflake Intelligence tools. Stay tuned for more in 2026.

For teams ready to take the next step in retail intelligence, Crisp AI Blueprints offer pre-built, data science–ready models that layer onto clean, harmonized retail data – and can be activated in Snowflake today.

Proven wins with Crisp + Snowflake

Leading consumer goods companies are already seeing results with Crisp retail data in Snowflake. Global accessories manufacturer PopSockets, for example, integrates real-time omnichannel data across Target, Amazon, Best Buy, and other retailers into its Snowflake environment alongside ERP data, marketing analytics, and more. The centralized view enables teams to make daily, profit-boosting decisions across thousands of unique SKUs and has led to double-digit sales growth and 95%+ in-stock rates with key partners.

“With Crisp, we saw that we could not only save hours in managing data, but we could be faster and more nimble using real-time data,” explains Kyle Chu, Sr. Manager of BI and Financial Planning at PopSockets.

Similarly, Ritual Vitamins saved upwards of $250,000 in manual pipeline development by seamlessly integrating retail data into Snowflake with Crisp. Director of Analytics Brett Trani praises Crisp’s organized data schema and reliability, which made it an optimal choice for automation.

“It was a matter of a very quick data share, and we saw Crisp data in Snowflake within an hour or two,” Brett recalls. 

According to Kyle Chu of PopSockets, clean Crisp data in Snowflake provides the ideal foundation for AI innovation.

“The partnership with Crisp helps build that foundation that will empower our next step in our AI journey,” Chu shares.

“It was a matter of a very quick data share, and we saw Crisp data in Snowflake within an hour or two.”

_{Brett Trani, Director of Analytics, Ritual Vitamins}

Empowering teams across the CPG enterprise

AI-powered retail intelligence with Crisp and Snowflake democratizes advanced data insights across CPG organizations, helping every function – from analytics to supply chain – make faster, more informed decisions.

• IT and Analytics: Crisp eliminates the burden of manual pipeline maintenance, giving teams harmonized data ready for instant use in Snowflake. Analysts can automate insight generation and focus on strategic modeling rather than wrangling data.

• Supply Chain: Real-time, AI-ready data enables supply chain leaders to optimize resources and product flow. Using AI Blueprints such as On-Shelf Availability and agentic workflows, teams can anticipate disruptions, refine replenishment, and maintain ideal in-stock positions across channels.

• Category Management: Unified retailer and distributor data provides the foundation for smarter assortment and shelf strategies. With Store Clustering and Assortment Optimization AI Blueprints, category teams can identify regional growth opportunities and collaborate with retailers on data-backed decisions. Automated, customized reporting with AI Agents makes Monday morning reporting a breeze.

• Sales and Marketing: Clean, AI-enriched data in Snowflake unlocks real-time performance monitoring and what-if scenario modeling to present ROI-backed growth opportunities. Marketing teams can align campaigns with retail execution and measure their impact with precision.

AI-powered retail intelligence with Crisp and Snowflake democratizes advanced data insights across CPG organizations, helping every function – from analytics to supply chain – make faster, more informed decisions.

Get started today

Snowflake customers can begin utilizing Crisp retail data in their environment today with our Marketplace integration. AI Blueprints can also be leveraged – all you have to do is explore our catalog of offerings and download the data-science-ready notebooks for use in Snowflake. Finally, for those interested in unlocking the power of agentic AI, Crisp’s AI Agent Studio for Retail has a waitlist for Open Beta. Sign up to be the first to know and learn how to leverage the technology in Snowflake Intelligence.