Customer Event Hub - the modern Customer 360° view
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Today, companies are using various channels to communicate with their customers. As a consequence, a lot of data is created, more and more also outside of the traditional IT infrastructure of an enterprise. This data often does not have a common format and they are continuously created with ever increasing volume. With Internet of Things (IoT) and their sensors, the volume as well as the velocity of data just gets more extreme. To achieve a complete and consistent view of a customer, all these customer-related information has to be included in a 360 degree view in a real-time or near-real-time fashion. By that, the Customer Hub will become the Customer Event Hub. It constantly shows the actual view of a customer over all his interaction channels and provides an enterprise the basis for a substantial and effective customer relation. In this presentation the value of such a platform is shown and how it can be implemented.
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Customer Event Hub - the modern Customer 360° view
- 1. BÂLE BERNE BRUGG DUSSELDORF FRANCFORT S.M. FRIBOURG E.BR. GENÈVE HAMBOURG COPENHAGUE LAUSANNE MUNICH STUTTGART VIENNE ZURICH #SDF16 Customer Event Hub The modern Customer 360° View Guido Schmutz guido.schmutz@trivadis.com #SDF16
- 2. #SDF16 Guido Schmutz Working for Trivadis for more than 19 years Oracle ACE Director for Fusion Middleware and SOA Consultant, Trainer, Software Architect for Java, SOA & Big Data / Fast Data Member of Trivadis Architecture Board Technology Manager @ Trivadis More than 25 years of software development experience Contact: guido.schmutz@trivadis.com Blog: http://guidoschmutz.wordpress.com Slideshare: http://www.slideshare.net/gschmutz Twitter: gschmutz
- 3. #SDF16 Agenda 1. Customer 360° View - Introduction 2. Customer 360° View - Challenges 3. Customer 360° View - Big Data Platform to the Rescue? 4. Our Offering
- 4. #SDF16 Customer 360° View - Introduction
- 5. #SDF16 Why Customer 360° View? “Get closer than ever to your customers. So close that you tell them what they need well before they realize it themselves.” Steve Jobs, Apple
- 6. #SDF16 Why Customer 360° View? – Key Use Cases • Customer micro segmentation • Next Best Offer • Campaign Analytics • Geo-Location Analytics • Recommendation Models • Churn Modeling & Prediction • Rotational / Social Churn • Customer Lifetime Value • Sentiment Analytics • Price Elasticity Modeling • Proactive Care Dashboard • Customer Lifetime Value • Subscriber Analytics • QoS Analytics • Real-Time Alerts Target Marketing & Personalization Churn Prevention & Customer Retention Proactive Care
- 7. Customer 360°: Experience Expectations
- 8. #SDF16 Customer 360°: Experience Expectations Consistent Across all channels, brands and devices Personalized To reflect preferences and aspiration Relevant In the moment to customer’s needs and expectations Contextualized To present location and circumstances
- 9. #SDF16 A Sample Customer 360° Profile Who are you? Where are you? What have you purchased? What content do you prefer? Who do you know? What can you afford? What is your value to the business? How / why have you contacted us?
- 10. #SDF16 From Static to Dynamic, Real-Time Micro-Segmentation Age Gender Average Spend Price Plans Usage History Data, Voice, Text Billing History Device Upgrade Traditional Segmentation Age Gender Average Spend Price Plans Usage History Data, Voice, Text Billing History Device Upgrade Device History Other products / services Bundling preferences Offer History Campaign Adoption History Call Center Tickets Location Social Influence Applications Used Content Preferences Usage Details Roaming Analysis Travel Patterns QoS History Household Analysis Lifetime Value Churn Score Clickstream Info Channel Preferences Survey Real-Time Micro- Segmentation
- 11. #SDF16 Customer 360° View: Know your Customer
- 12. #SDF16 Customer 360° Screen Mocks Source: Canopy Labs Source: Adacta Group Source: Oracle
- 13. #SDF16 Customer 360° View - Challenges
- 14. Key Challenges in Driving a Customer 360° View Data Silos New Data Sources Costs of Data Processing Data Volumes • Multiple Data Silos • Often store overlapping and conflicting information • Data growing rapidly • Internet of Things will add to that substantially • Semi/Un-Structured Data Sources • Streaming / Real-time data • Critical for building a true 360° view • Cost prohibitive • Cost of storing data in relational database systems per year Clickstream Location/GPS Call center Records Social Media
- 15. Customer 360° View - Traditional Flow Diagram Enterprise Data Warehouse ETL / Stored Procedures Data Marts / Aggregations Location Social Clickstream Segmentation & Churn Analysis BI Tools Marketing Offers Billing & Ordering CRM / Profile Marketing Campaigns
- 16. Customer 360° View - Traditional Flow Diagram Enterprise Data Warehouse ETL / Stored Procedures Data Marts / Aggregations Location Social Clickstream Segmentation & Churn Analysis BI Tools Marketing Offers Billing & Ordering CRM / Profile Marketing Campaigns Limited Processing Power Does not model easily to traditional database schema Limited Processing Power Storage Scaling very expensive Based on sample / limited data Loss in Fidelity Other / New Data Sources High Voume and Velocity
- 17. #SDF16 Customer 360° View: Why status quo won’t work? • Most organizations have a static version of the customer profile in their DWH • Mainly structured data • Only internal data • Only “important” data • Only limited history • Activity data – clickstream data, content preferences, customer care logs are kept in siloes or not kept at all Data Analyst Data Analyst Data Analyst Data Analyst Data Analyst Detailed Customer Activity Data sits in silos!
- 18. #SDF16 Customer 360° View – Big Data Platform to the Rescue?
- 19. Event Hub Event Hub Hadoop Clusterd Hadoop Cluster Hadoop Cluster Customer 360° View – Flow with Big Data Hub BI Tools Enterprise Data Warehouse Location Social Click stream Sensor Data Billing & Ordering CRM / Profile Marketing Campaigns Event Hub Call Center Weather Data Mobile Apps SQL Search Online & Mobile Apps Search Data Flow NoSQL Parallel Processing Distributed Filesystem • Machine Learning • Graph Algorithms • Natural Language Processing
- 20. Hadoop Clusterd Hadoop Cluster Hadoop Cluster Customer Event Hub – taking Velocity into account Location Social Click stream Sensor Data Billing & Ordering CRM / Profile Marketing Campaigns Call Center Mobile Apps Batch Analytics Streaming Analytics Event Hub Event Hub Event Hub NoSQL Parallel Processing Distributed Filesystem Stream Analytics NoSQL Reference / Models SQL Search Dashboard BI Tools Enterprise Data Warehouse Search Online & Mobile Apps File Import / SQL Import Weather Data
- 21. #SDF16 Enabling Continuous Data(Event) Ingestion SQL Polling Change Data Capture (CDC) Sensor Stream File Stream (File Tailing) File Stream (Streaming Appender)
- 22. #SDF16 Big Data Ecosystem – Lot’s of choices ?
- 23. #SDF16 Big Data Ecosystem – Sorted J
- 24. Weather Data SQL Import Hadoop Clusterd Hadoop Cluster Hadoop Cluster Location Social Click stream Sensor Data Billing & Ordering CRM / Profile Marketing Campaigns Call Center Mobile Apps Batch Analytics Streaming Analytics Event Hub Event Hub Event Hub NoSQL Parallel Processing Distributed Filesystem Stream Analytics NoSQL Reference / Models SQL Search Dashboard BI Tools Enterprise Data Warehouse Search Online & Mobile Apps Customer Event Hub – Technologies Mapping
- 25. #SDF16 Various forms of 360° Views qAccount 360 qSupplier 360 qConsumer 360 qProduct 360 qAsset / IP 360 qSpend 360 qKey Opinion Leader 360 qSensor / Device 360
- 26. #SDF16 A Spectrum of Big Data Use Cases OptimizeTransform Business Impact Use Case Complexity Entry Advanced Streamline Data Refinery Customer 360 Degree View Data Warehouse Optimization Monetize My Data Harnessing Machine & Sensor Data Big Data Predictive Analytics Next Generation Applications Big Data Exploration On Demand Big Data Blending
- 28. #SDF16 Big Data Roadmap BDS-INTRO - Introduction into BigData, IoT & Data Science 26.05.2 016 Orientation Workshop Potential Analysis Strategy- Roadmap Implemen. Services Big Data Introduction Business/ Use-Case Big Data Productive Technical Starter KitTools and Methods Evaluation Tools/Methods Choose Technology Big Data Mainten. & Operation SLA Services Know How Training Tools Methods Reference-implementation + setup & config Test VMs + Services + Examples Workshop(s), Analyis and Interviews Workshop(s) with individual Content Project Project Training PoC, Eval AMS & IMS Services Initial Workshop
- 29. 360° Customer View – Trivadis Portfolio Customer Event Hub § IT Strategy & Architectures § Advanced Analytics § Visualization Method & Technology Trainings Consulting & Managed Services Data & Process Integration § Real-Time Data Ingestion § Data Virtualization & Federation § Streaming Analytics § Customer Event Hub Use Case Support § Requirements Analysis § Workshops, Coaching, Interviews Application Development Technology Evaluation § Proof-of-Concept § Functional & Load Testing