5 popular use cases for streaming data in E-commerce and Retail
Staying competitive in retail and e-commerce hinges on collecting and analyzing up-to-the-minute information about everything from stock levels to fashion trends. To stay agile in this fast-paced industry, businesses increasingly rely on streaming data — a method of continuously processing and analyzing data as soon as it’s generated.
Streaming data touches every aspect of retail and e-commerce operations, from the logistics of shipping products to customer support. In this blog, we’ll explore five impactful use cases where it helps e-commerce and retail companies become faster, more efficient, and customer-focused.
#1: Real-Time Inventory Management
Managing inventory effectively is a constant struggle in e-commerce and retail. Stockouts lead to lost sales and dissatisfied customers, while overstocking results in increased storage costs and markdowns.
In addition, online shoppers expect up-to-the-minute accuracy in product listings. No one wants to buy an item, only to discover it was out of stock. So, retailers must sync inventory data across warehouses, e-commerce portals, and retail stores in real time — a tall order with legacy data infrastructure.
How Streaming Data Fits
Streaming data infrastructure can ingest and analyze real-time data from point-of-sale systems, warehouse sensors, and supply chain platforms to track inventory levels as they fluctuate in the moment. Retailers can use the resulting insights to optimize orders and ensure e-commerce apps and sites stay up to date.
Benefits of Streaming Data
By leveraging streaming data for inventory management, retailers can reduce stockouts and overstocks, leading to better inventory turnover and reduced carrying costs. Moreover, real-time insights enhance supply chain efficiency, ensuring that products are in the right place at the right time.
Streaming Data Example
Amazon uses real-time data streaming to monitor its vast inventory across multiple warehouses. This capability allows them to automatically reroute stock and replenish items to meet fluctuating demand, minimizing stockouts and ensuring products are available to customers promptly.
#2: Dynamic Pricing Strategies
In the highly competitive e-commerce landscape, the right pricing can make or break a sale — or a company’s profit margins. E-commerce companies need to offer dynamic pricing that adapts automatically to optimize offerings.
How Streaming Data Fits
Streaming data enables dynamic pricing by allowing businesses to monitor relevant factors like competitor pricing, customer demand, and market conditions in real time. Retailers can adjust prices instantly to maximize profitability, match competitors, or offer timely discounts that attract more customers.
Benefits of Streaming Data
With real-time pricing adjustments, companies can boost revenue by capitalizing on demand surges, helping maintain optimized profit margins. They can also increase competitiveness by staying ahead of market trends or matching (or undercutting) competitors’ pricing.
Streaming Data Example
Online travel agencies like Expedia use streaming data to dynamically adjust hotel and flight prices in real time. For example, if the announcement of a major event in a particular city suddenly spikes demand for flights and hotels, Expedia can adjust pricing upwards to maximize profit during a period of high demand.
#3: Personalized Customer Experience
Customers expect a tailored shopping experience that reflects their preferences and behavior. Retail and e-commerce companies must respond instantaneously to inputs and deliver personalized, relevant content.
How Streaming Data Fits
Streaming data allows retailers to gather and analyze data on customer behavior as it happens. By cross-referencing this real-time data with other information like past purchase history, companies can deliver personalized product recommendations, offers, and experiences that match their preferences in the moment.
Benefits of Streaming Data
This real-time personalization leads to increased customer engagement, higher conversion rates, and enhanced loyalty. Customers feel understood and valued, which drives repeat purchases and builds long-term relationships.
Streaming Data Example
Customers give retail brands feedback in various forms across many platforms, from social media to reviews sites. By leveraging Redpanda and Clickhouse, an open-source data management system (DBMS), a brand can build a real-time sentiment analysis solution that collects feedback and yields actionable insights brands can use to address problems in the moment and stay ahead of market trends.
#4: Fraud Detection and Prevention
Fraud hurts retail and e-commerce companies’ bottom lines and erodes customer trust. Organizations need tools to fight back and respond to suspicious activity in the moment, before fraudsters can do damage.
How Streaming Data Fits
By utilizing streaming data, retailers can monitor transactions and user activity as they happen. Advanced algorithms analyze data for suspicious patterns and anomalies, allowing businesses to identify potential fraud in real time and take immediate action to mitigate risks.
Benefits of Streaming Data
Streaming data helps reduce fraud by allowing proactive detection, which improves security and customer trust. Real-time detection also reduces financial losses and reputational damage for the business.
Streaming Data Example
By comparing real-time transaction data against historical patterns, a fraud prevention system can instantly flag anomalies. For example, if a user on an e-commerce site suddenly changes their default shipping address, password, and phone number for two-factor authentication all at once, that could be a sign a bad actor has taken over the account. The system can flag this anomaly for immediate review, enabling the company to intervene before new, potentially fraudulent purchases are made.
#5: Real-Time Customer Support
Responsive customer support is a crucial factor in maintaining customer satisfaction in the retail space. Poor experiences can lead to bad reviews and negative word of mouth, harming overall brand sentiment and possibly depressing future sales.
How Streaming Data Fits
Real-time clickstream data — information about how a user interacts with an app or website — is vital for customer support. Analyzing it in real time can help retailers and e-commerce companies head off potential issues before they cause a serious problem for customers.
Benefits of Streaming Data
By leveraging streaming data for customer support, businesses can reduce customer support requests, leading to higher customer satisfaction. It also allows customer support teams to focus on complex issues while automated systems handle simpler tasks in real time.
Streaming Data Example
Clicking the same button over and over again or refreshing a page repeatedly can be a sign that a customer is experiencing a bug, slow load times, or another issue. An e-commerce company could build a clickstream processing pipeline to flag these behaviors for customer service, then automatically open a chatbot window to field the user’s feedback.
Final thoughts
Streaming data has a transformative effect on e-commerce and retail by enabling real-time decision-making across various aspects of business operations. From inventory management and pricing to personalized customer experiences and fraud prevention, these use cases highlight the value of immediate data insights in today’s competitive landscape.
As streaming data technology advances, retailers that adopt it will continue to benefit from increased efficiency, reduced costs, and stronger customer relationships. If you’re interested in learning how streaming data can be integrated into your retail strategies, consider exploring Redpanda — a powerful platform designed to help businesses unlock the full potential of real-time analytics.
For step-by-step tutorials on how to implement the examples mentioned in this post, check out the Redpanda Blog.
