Active Insight Overview
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The document provides an overview of real-time event stream processing, highlighting its significance in various industries, including online marketing, gaming, and finance. It discusses the challenges and technological needs associated with processing vast amounts of data while ensuring performance and availability, along with the unique value of integrating real-time analytics into existing infrastructures. Use cases demonstrate applications like fraud detection, customer retention strategies, and improving conversion rates through actionable insights.
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Active Insight Overview
- 2. Real-time Event Stream Processing General Overview ACTIVE INSIGHT
- 3. Background - Events are All Around Us Traditional Systems Orders Inquiries Airline Reservations ATM Transactions Insurance Claims Transactional Systems Telecom CDR’s Financial trade “ticks” News feeds Credit card transactions Micro payments Sensor Systems RFID Wireless location services (LBS) Satellite, GPS RFID Bar-code feeds Factory floor WEB Gambling Gaming ecommerce Click stream RSS ATOM Email Multiple Event Streams and Sources
- 4. Background – Business is Changing The world is becoming digital Extreme Transaction Computing changes the stock market Large web site traffic reaches extreme transaction rates Online interaction grows but conversion rates remain low Cloud computing and Online Gaming accelerate the online channel Numerous use-cases emerge for real-time pattern based processing, detection and reaction: Online Marketing, Sales and Self-Service Online Gaming & Gambling Brokerage & Algo-Trading
- 5. Food for Thought “ Subscriber information owned and continuously gathered by service providers offers unprecedented insights into the behaviors of consumer and business customers . This information represents the crown jewels, or treasure, of the telecommunications service providers. However, the volume of data involved is increasing exponentially due to the expansion of services and handsets. The pain involved with the new volumes of data, as well as the number of systems associated with the data, has spurred a new wave of initiatives…” IDC June 2009
- 6. ActiveInsight.org Distributed Event Stream Processing Framework Real-time event processing Multi-source event streams Event correlation and aggregation Pattern matching Integrated data caching Embeddable framework Scalable, elastic cloud run-time
- 7. The Business Need Typical HPC (High-Performance Computing) needs Online Gaming : Real-time BI, money laundering, local compliance, application offload Algo-Trading : performance/availability improvements and HW cost reduction Online Advertisement: Behavioral targeting, multiple site click-stream correlation SaaS deployments: Off-loading core applications, offering value added services Electrical smart-grid: Detecting misuse, mal-functions, on-demand supply Typical E-marketing needs Ecommerce : Identifying a customer interested in additional services or products, Improving conversion rates, anonymous user hooking, campaign management Self-Service : Identifying potential customer turnover or dissatisfaction, Monitor user experience and assist in transaction completion Typical Compliance/Regulation needs Auditing: Feeding “Who” did “What” and “When” to auditing and SIEM systems Fraud detection: Fraudulent behavior pattern detection, Bot detection, alongside fraud detection systems
- 8. Main Technological Challenges Detecting relevant events and behavior in real-time , out of millions of events, without harming application performance and availability Reacting to relevant events by feeding various backend applications (CRM, BI, Security, etc.) and/or interacting directly with the user Providing a simple, flexible and embeddable solution that can be deployed with existing infrastructure and applications De-coupling runtime processing for flexibility and scalability
- 9. Unique Value Proposition Embeddable, Real-time data stream processing Flexible and dynamic pattern definition/detection SpringSource development platform interoperability Real-time, pattern-based logic invocation Business driven behavior detection User-centric actionable events Real-time, value-based event feeds & user interactions Non-intrusive deployment Support for extreme transaction rates “ With ActiveInsight organizations can identify up-sell and cross-sell opportunities, react to potential customer churn in time to prevent it, improve online self-service to customers and detect potential fraudulent activity in real-time “
- 10. Example Use Cases Finance Customer searches for savings account, compares mortgage types, checks cash-out options, tries to make a deposit or buy stocks... -See more Telecom Customer checks phone price and features, compares international rates, tries to opt-in for a service... -See more Gaming Customer fails to cash-in, plays less then X minutes, loses more then $X, must be reported to regulatory application... -See more E-Commerce Improve conversion rates by actively funneling users, detecting hesitation or potential cart abandonment, optimize coupon usage to high potential customers Tourism Customer plans expensive multi-stop trip, Anonymous customer checks out ticket prices, tries to make a reservation or stops at phase X... -See more
- 11. Use Cases: Financial Up-sell/Cross-sell- Identify customer interest in additional products and services : Customer checks current investment status > Is he interested in an updated investment plan ? John Smith, 10/08/2008, interested in long term savings, customer type: 3 Offer additional services: Savings plans, investment plans, mortgages, loans… Hook new customers Contact anonymous surfers, showing high potential behavior, using dynamic content Customer retention: React to potential customer desertion Customer checks savings withdrawal amount > Is he in financial trouble? Does he need a loan ? Customer produces specific financial reports > Is he undergoing some kind of financial planning? Is he on his way out? Improve transaction completion rates Identify problem and offer immediate assistance to stop revenue loss Customer fails buying stock Customer Fails in a money transfer or a foreign exchange transaction Real time customer experience management Non-intrusive auditing for security and compliance Real time pattern detection to feed Fraud systems and react
- 12. Use Cases: Telecom Up-sell/Cross-sell- Identify customer interest in additional products and services : Customer browses new phone models: offer coupons, tie to content package Customer checks additional service plans and opt-in options – offer focused packages Customer downloads themes, ringtones, etc – offer related content Hook new customers Contact anonymous surfers, showing high potential behavior: “Click here to get the new mobile with a free web package” Customer retention: React to potential customer desertion Customer checks his monthly balance too often > Is he comparing prices Customer checks license agreement Improve service consumption rates and self-service Customer fails to configure account for international usage > offer immediate assistance to stop revenue loss Pre-paid customer fails buying air-time Customer fails downloading themes, ringtones, movie-clips Real time customer experience management Non-intrusive auditing for security and compliance
- 13. Q&A Thank you! http://www. activeinsight .net [email_address]
Editor's Notes
- #7: ActiveInsight can also be used for security applications as well such as assistance in Online Fraud Detection and Security Events and Information Management