Retail Tech Processes 1M+ Data Points With Data Warehouse

Transformed real-time transactions into performance data for 12,000 stores

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12,000

Retail stores covered across the US alone.

80%

Reduction in checkout time.

100x

Supported 100s of white-labeled solutions.

Client overview

Our client is a retail technology company that puts checkout in shoppers’ hands with a mobile self-scan app. Customers build and share lists in real time, see exact pricing and deals while scanning, and skip lines with convenient mobile checkout.

For retailers, the platform integrates with existing systems to digitize deals, enable in-store scanning, and support simultaneous checkout. Analytics track engagement and redemptions, while an influence engine recommends targeted products to grow basket size and drive foot traffic.

Challenges

Inconsistent data pipelines, fragmented POS systems, and rigid platform architecture made it difficult to provide tailored retail experiences at scale.

Slow checkout process

Retailers struggled with long checkout lines and latency in legacy POS systems, reducing transaction speed and frustrating in-store customers.

Fragmented retail data

Customer and inventory data was distributed across systems, making it difficult to generate unified insights or support seamless shopping experiences.

Customization constraints

Retailers needed brand-specific interfaces and workflows, but the platform couldn’t accommodate full theming or feature flexibility per deployment.

Solution

We re-architected the platform for scale, speed, and adaptability for real-time experiences and personalized solutions across hundreds of retail locations.

Frictionless checkout

Built a seamless scan-to-pay experience that lets users scan barcodes, create carts, and complete payments instantly, which reduced in-store wait times and streamlined checkout.

Unified data framework

Developed a centralized data framework with real-time syncing across inventory, sales, and behavior channels to ensure accurate, timely analytics for all retail environments.

Modular architecture

Transformed the backend into loosely coupled services, enabling rapid feature releases, faster onboarding of new partners, and improved scalability across retail locations.

Customizable interfaces

Created dynamic frontend templates and adaptable backend logic to support retailer-specific workflows, branding, and loyalty programs without impacting platform stability.

Business impact

The redesigned platform improved checkout speed, data intelligence, and operational flexibility, improving shopper experiences across retail locations.

Actionable retail insights

Unified data pipelines gave retail partners access to accurate performance metrics, enabling better planning and campaign-level decision-making.

Improved platform agility

Modular architecture allowed faster onboarding, brand customization, and scaling across partners with fewer deployment delays.

Revenue per store growth

Enhanced customer experience and frictionless checkout contributed to measurable increases in daily transactions and per-store revenue performance.

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