IoT Analytics for Retail and Proximity Marketing

RetailTech

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The Client

Favendo RTLS is a complete real-time location system and localizes people & assets using a BLE IoT iBeacon infrastructure and corresponding software. The localization software can be integrated into existing system environments and apps. Favendo’s Commander RTLS platform enables indoor navigation, proximity marketing, indoor asset, and person tracking. We can track smartphones as well as sensor tags/wearable.

Business Challenges

Favendo wanted to build a Retail-Tech Real-time Location Service (RTLS) based on their BLE iBeacon IoT hardware. The goal was to develop an MVP on Microsoft Azure as a cloud-native analytics application. This platform aimed to serve retail stores and malls for proximity marketing purposes by analyzing the foot traffic of consumers and offering in-app promotions.

Business impacts/key results achieved

Zymr built a cloud-native analytics platform that provisioned, gathered, and analyzed real-time location data from iBeacon BLE sensors and iOS and Android apps. This Azure-based cloud-native analytics application collects real-time data. Data visualization gives insights about number of customers, customer flow, and length of stay. It engages customers through personalized content and increases conversion rates. The platform improved the shopping experience with indoor navigation and other services. It helps the beacon network digitally and leases access to brands or partner apps for new revenue sources. We developed an independent reporting portal called Neptune to enable merchants and their marketing apps to analyze consumer foot traffic by brands, stores, times, and other custom filters.

Zymr's

Strategy and Solution

Zymr developed Azure-based node.js microservices for various services – registration of beacon IoT devices, multi-tenancy, analytics, and other administrative services. Extensive REST-APIs were developed to enable merchants to integrate with Favendo’s core platform, especially for real-time marketing campaigns to consumers in shopping malls and retail stores. We built an analytics tier using Azure streaming analytics and AI/ML models to process real-time logs from various BLE sensors and corresponding mobile apps of consumers visiting retail stores. We developed a Python-based IoT simulator to generate random location-aware logs.

Using a Python-based test automation framework, we successfully scaled the analytics engine to 1000+ stores with 100K BLE sensors.

Zymr was chosen as the sole developer of Favendo’s Azure cloud-native analytics platform for the retail industry. This platform tracks visitors in malls and stores, and integrates the real-time analytics with merchant’s proximity marketing applications. We brought its IoT expertise and leveraged Favendo’s IoT BLE and iBeacon sensors that were provisioned from the cloud. Merchant-specific iOS and Android applications used these sensors automatically to track their movement in stores. Our teams developed a merchant-side admin portal for Shopping Mall or Retail Outlet to provide rich location-based visualization of foot traffic, dwell-times, and demographics for proximity marketing. Our client’s retail customers leverage this real-time Location Service, a BLE IoT solution, to create a powerful proximity marketing platform to assist retailers in tailoring their product placement and developing digital marketing and retail promotional programs.