RETAIL AND E-COMMERCE

Use Fast Data for Sustainable Competitive Advantage

RESHAPE YOUR BUSINESS WITH          REAL-TIME OPERATIONAL INTELLIGENCE 

Digital disruption has put pressures on retail businesses to manage the store operations efficiently and build online sales strategies to grow revenue. At the same time, e-commerce companies have to up their game with digital innovation to make online shopping fun and convenient, and convert browsers to buyers. Striim delivers real-time integration and streaming analytics using customer behavior, sales, inventory, and other operational data to detect and notify of time-sensitive buyer opportunities and operational risks. It enables you to make automated decisions with deeper and timely customer insight while bringing operational efficiencies that raise profitability.

  • Use real-time data from all corners of the business, including sensors, for operational reporting and analytics
  • Identify and receive alerts on sources for shrinkage by analyzing inventory and POS data in real time
  • Create personalized offers based on customers’ location and most recent behavior across channels
  • Maximize revenue via dynamic pricing based on real-time demand and inventory data
  • Predict customers’ propensity to purchase in real time
  • Monitor store or online sales, campaign success, and customer behavior continuously
  • Protect customer data security against internal and external threats

WHY STRIIM FOR RETAIL AND E-COMMERCE

Striim captures real-time change data non-intrusively from enterprise databases and integrates with machine and sensor data for a comprehensive view of operations. It enables you to work with a smart data architecture by filtering, aggregating, transforming, enriching, and analyzing sensor data at the edge.  By analyzing data-in-motion, it allows you to respond to time-sensitive operational events, such as a loyal customer arriving at a location near your store, immediately.

Striim’s advanced features such as predictive analytics and ability to embed machine learning algorithms allow you to make accurate and timely decisions with deep customer insight and operational context. With built-in, real-time dashboards you can visualize streaming operational data and track different key metrics to respond to emerging trends proactively.

IMPROVE CUSTOMER EXPERIENCE
Use real-time customer behavior and operational data to make personalized offers and deliver an excellent shopping experience
REDUCE THEFT AND SHRINKAGE
Continuously monitor POS and inventory data, and use predictive analytics to identify shrinkage sources immediately
INCREASE OPERATIONAL EFFICIENCY
Prevent out-of-stock issues, have an end-to-end, real-time visibility into the supply chain, and allocate staff based on real-time demand
Customer Use Cases

ONLINE RETAILER FOR HEALTH AND BEAUTY PRODUCTS

The leading consumer health, beauty, and home-care online retailer wanted to ensure outstanding customer experience by analyzing real-time customer behavior on the website and track orders continuously. The company chose Striim for real-time data integration into Kafka, streaming analytics, and data visualization, delivered in a single enterprise-grade software platform.

Striim collects website log data, enriches with customer data from transactional databases in real time via log-based change data capture, and analyzes the streaming data to detect any patterns and anomalies. It delivers insights via real-time dashboards and allows real-time monitoring of key metrics. It can also predict any website performance issues to prevent impact on customer experience.


Prevents website performance issues via real-time, predictive analytics


Eliminated the performance impact of running ad-hoc queries on the production OLTP systems


Offers targeted products to buyers based on real-time, and deeper customer insight

Use Case Examples

MAKE YOUR FAST DATA WORK BETTER FOR YOU

Striim supports retail and e-commerce companies with a variety of use cases including:

  • Real-time data integration for cloud, Big Data, and Kafka
  • Fraud/theft detection and prevention
  • Dynamic pricing based on inventory
  • Personalized, in-store offers
  • Geo-targeted mobile marketing
  • Real-time POS monitoring
  • Supply chain optimization
  • Workforce optimization
  • Regulatory compliance such as GDPR

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