Supercharge your BI & analytics with real-time point-of-sale data
Integrate Retail POS Data into Power BI, Tableau, Looker, ThoughtSpot and Other BI / Analytics Apps
As a consumer brand selling through retail, bringing your internal data (shipments, warehouse inventory) and external data (retail sales, channel inventory, distributor data) together into a single-source of truth can be challenging. Each partner delivers data in different portals, formats and frequencies. Once you’ve solved the problem of ingesting data, normalizing it into a single unified format is highly manual and time consuming. You end up spending more time wrangling POS data than actually using it.
Alloy.ai lets CPGs bring connect, ingest and normalize data from 100s of retailer portals, distributors directly into PowerBI, Tableau, Looker, ThoughtSpot, Excel and many other business intelligence and analytics applications.
Benefits of Integrating POS Data into Your BI App With Alloy.ai
- Pre-built connectors to 100s of retailers and partners - Pipe in sell-through and inventory data from all of your retail, ecommerce and supply chain partners directly into your BI app — or into your data warehouse or data lake — to help you create a single source of truth for partner data.
- Improve your sell-through analytics with a complete, cross-retailer view of your partners in one place - Use Alloy.ai's analytics or easily bring this data into your Power BI, Tableau, ThoughtSpot or your analytics application of choice to ensure your teams are always making decisions based on the latest, most accurate data.
- Automatically normalize data by time, currency, units of measure, location and product- The normalization layer of the Alloy.ai data platform automatically translates disparate data sources and types into a single, unified representation of your business.
- We maintain the data pipeline, so you can focus on what matters - The Alloy.ai engineering team has deep expertise managing CPG data and helping consumer brands move POS data to power their analytics, planning and other business decisions. When retailer portals push changes to the way data is delivered, we handle the changes, saving you the work of troubleshooting your data sources.
- Always up-to-date - When new partner data is available, your data will update in minutes with all of your — fully normalized, at any scale.
Questions CPG brands can answer with the Alloy.ai data platform
- How can I bring POS sell-through data into PowerBI, Tableau, ThoughtSpot, Looker, Excel or another BI tool?
- How can I save time by automating data normalization?
- How can I automate getting the most recent sales and inventory data from all of my retail partners?
- As a CPG brand how can I get cross-retailer visibility into sales and inventory?
Bosch’s sales strategy with POS data
Explore Bosch’s best practices for building a successful sales strategy with POS data — gathered from across ecommerce and retail customers.
Matthew Bergum, Country Business Director
Trusted by 100s of Consumer Brands
Instant sales and inventory insights at your fingertips.
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Frequently Asked Questions
Alloy.ai provides pre-built connectors to hundreds of retailers and partners, allowing brands to seamlessly pipe in sell-through and inventory data from all retail, e-commerce, and supply chain partners directly into BI applications such as Power BI, Tableau, Looker, and ThoughtSpot. This integration helps create a single source of truth for partner data, enhancing analytics capabilities.
Integrating POS data into BI applications enables brands to easily fit Alloy.ai data into their existing analytics stack, so they can get started quickly. Consumer brands use integrated data from Alloy into BI or analytics platforms to improve sell-through analytics with a complete, cross-retailer view of their partners in one place. It ensures that teams are always making decisions based on the latest, most accurate data, leading to better-informed strategies and actions.
Alloy.ai’s data platform includes a normalization layer that automatically translates disparate data sources and types into a single, unified representation of the business. This process involves normalizing data by time, currency, units of measure, location, and product, ensuring consistency and accuracy across all integrated data.