From ingestion to attribution to analytics, Crisp helps CPGs unlock the value of retail data across their organization.

Automate the collection of sales, inventory, and supply chain data from retailers, distributors, and marketplaces.

• Streamline data retrieval from retailer portals, APIs, and third-party platforms
• Ensure frequent data updates without manual intervention
• Maintain a scalable and secure architecture without the need for in-house built pipelines

Standardize and centralize retailer data to ensure accuracy and consistency.

• Identify and resolve inconsistencies, missing values, and duplicates
• Align metrics and definitions across Walmart, Target, Amazon, and other major retailers
• Maintain a uniform data structure for seamless cross-retailer analysis

Enhance datasets with additional context and attributes to support deeper analysis.

• Align product, store, and category definitions across retailers and internal systems
• Integrate third-party data sources such as weather, demographics, and competitive insights
• Map custom attributes to align with internal reporting structures and business processes

Translate complex, disparate data sources into a structured format that aligns with business needs.

• Standardize sales, inventory, and supply chain metrics across retailers and distributors
• Convert raw point-of-sale and inventory data into a structured, analytical format
• Enable self-service analytics so teams can access insights without engineering support

Ensure accurate, up-to-date data is automatically delivered where it’s needed.

• Direct integrations with Databricks, Snowflake, BigQuery, and other cloud platforms
• Automated data synchronization to ensure internal systems receive the latest retailer and distributor data
• Flexible delivery options, including dashboards, data lakes, and direct system integrations

Generate insights that drive strategic and operational improvements across sales, inventory, and supply chain management.

• Identify sales trends and demand shifts to optimize replenishment and forecasting
• Surface anomalies in sales and inventory to address issues before they impact performance
• Use machine learning models to improve store clustering, lost sales estimation, and promotional effectiveness

Make data available across teams, systems, and workflows to support better decision-making and execution.

• Power sales, supply chain, and category management with automated workflows
• Enable seamless data sharing across internal teams and external partners
• Deliver insights directly into business intelligence tools and operational systems