With traditional rules engines and event processing solutions, there is still a significant reliance on IT to implement changes, as the underlying rules engines are often static. Companies are now looking beyond legacy business rules management systems, to options that automatically detect and adjust to business events in data streams.
The following include a few use cases and examples of how organizations are implementing these Big Data-based rules authoring and event streaming solutions:
Customer Segmentation & Offers
Marketing teams can dynamically target messaging and adjust outreach frequency based on variable data. For example, retailers can create hyper targeted campaigns to users based on location and weather conditions. Marketers can quickly adjust these campaign parameters if a new line of apparel is released. Targeted discounts can arrive at key moments in the purchasing lifecycle, and to specific customer segments, to deepen brand relationships.
Beyond targeted offers and segmentation, marketing is also using these solutions to create a single, unified view of the customer to assist with omni-channel and seamless user experiences across channels. Rules authoring enhances a marketer’s ability to tailor communication on one platform based on a user’s engagement on another. Predictive marketing capabilities are also improved, since marketing departments can better predict customer lifetime value (CLV) based on a customer’s first purchased product or acquisition channel.
Compliance is a key business driver for security requirements in government and other industry domains with sensitive information. Security event detection and remediation is critical in finding “needles in a haystack,” where needles are significant security events. Rules authoring and event stream processing provides faster detection and remediation, quickly alerting an organization to significant security attacks. These solutions also help with proactively addressing threats through forensics analysis that reveals unknown vulnerabilities in an organization’s network or desktop security controls.
Banks and financial services organizations can better infer the likelihood of fraud based on flags in behavioral patterns from a variety of data sources and channels. Business users in the fraud department can adjust the rules behind detection as new information is available.
In general, Big Data-based rules authoring and event stream processing helps better manage numerous data elements that are not stored in a persistent database. The solution is also beneficial in managing synonyms or variations in definitions of the same term, enumerations of business terms, and semantic hierarchies.