Gain visibility into pricing, assortment, and availability across every store and SKU - so you can respond faster, optimize smarter, and stay ahead of the competition
Shoppers move fluidly between online and offline channels, expecting seamless experiences and competitive pricing at every touchpoint.
Each store operates in a unique micro-market, where competitive dynamics shift based on regional demand, local pricing strategies, and competitor actions.
With inflation and price sensitivity shaping purchasing behavior, retailers need granular, store-level intelligence to optimize pricing, assortment, and inventory.
Monitor product availability, pricing, and assortment seamlessly across mobile apps, retail sites, delivery platforms, marketplaces, and physical stores for total visibility.
Capture pricing, assortment, and availability data for every SKU across competitor locations with 99%+ accuracy.
Gain location-specific analytics - whether for a single store, region, or entire market - to drive strategic, data-backed decisions. Track historical trends by location to build informed strategies grounded in market patterns.
Enhance pricing dynamically with store-level competitive data.
Adjust quickly to competitor shifts at each location.
Align pricing strategies with regional competitive conditions.
Leverage localized insights for better deals.
Identify market share growth opportunities with store-level data.
Tailor campaigns based on competitive activity at every store.
Hyperlocal analytics delivers granular insights into pricing, promotions, inventory, and assortment at the individual store level. By tracking localized fluctuations in real time, it enables retailers and brands to tailor strategies to specific geographies—helping improve demand forecasting, align with local competition, and maximize ROI on pricing and promotion decisions.
DataWeave aggregates product information from diverse sources—including store websites, mobile apps, third-party marketplaces, and delivery platforms—and unifies it into a normalized data model. This allows brands to track performance across both digital and physical channels at the SKU and store level, all in one view.
Key challenges include fragmented data sources, inconsistent product identifiers, dynamic pricing and inventory, and technical blockers like bot protection. DataWeave overcomes these using resilient crawling infrastructure, automated data normalization, and continuous quality validation—ensuring reliable store- and SKU-level insights at scale.
We employ a distributed crawling infrastructure, advanced machine learning models, and rigorous data validation to deliver accurate insights across millions of SKUs and thousands of stores. This scalable architecture ensures real-time visibility into market dynamics—from store-level assortment to regional pricing trends.
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