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Using Big Data to Drive Customer 360

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Organizations across diverse industries are in pursuit of Customer 360, by integrating customer information across multiple channels, systems, devices and products. Having a 360-degree view of the customer enables enterprises to improve the interaction experience, drive customer loyalty and improve retention. However delivering a true Customer 360 can be very challenging.

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Using Big Data to Drive Customer 360

  1. 1. Using Big Data to Drive a True Customer 360 Capture Value from Big Data with an Enterprise Data Hub Vijay Raja - Solutions Marketing Manager Amy O’Connor - Big Data Evangelist
  2. 2. 2© Cloudera, Inc. All rights reserved. Agenda • Customer 360 - An Industry Perspective • Key Challenges in Driving a Customer 360 • Customer 360 - Why status quo won’t work • Driving Customer 360 with Hadoop • How to Iteratively build a true Customer 360? • Key Customer 360 use cases • Customer 360 case studies
  3. 3. 3© Cloudera, Inc. All rights reserved. Customer 360 – An Industry Perspective - What is Customer 360? A holistic real-time view of your individual customers Across all products, systems, devices and interaction channels In order to deliver a consistent, personalized, context specific and relevant experience
  4. 4. 4© Cloudera, Inc. All rights reserved. Customer 360: Experience Expectations Personalized to reflect preferences and aspirations Relevant in the moment to customer’s needs and expectations Consistent across all channels, brands, and devices Contextualized to present location and circumstances
  5. 5. 5© Cloudera, Inc. All rights reserved. Key Challenges in Driving a Customer 360 DATA SILOS DATA VOLUMES NEW DATA SOURCES COSTS OF DATA PROCESSING • Multiple Data Silos • Often store overlapping and conflicting info • Issue compounded with multiple business units Care Product Catalog CRM Ordering Billing Legacy Enterprise Inventory OSS Network Customer Care Product Catalog Ordering Billing CRM Legacy Enterprise Inventory Supply Chain PoS • Data growing at ~100% YoY • A typical mobile service provider generates approx. 5 – 30 Billion Call Detail Records (CDRs) every day Clickstream Location/ GPS Call center Records Social Media • Semi/ Un-Structured Data Sources • Streaming/ Real-time data • Critical for building a True 360 view • Cost prohibitive • $30,000 and $100,000 (USD) per TB – Cost of storing data in relational database systems per year
  6. 6. 6© Cloudera, Inc. All rights reserved. Polling Question What are some of the key challenges you face with respect to your Customer 360 journey? o Data Silos – Data spread across a number of silos o Data Volumes / Growth – High rate of data growth o New/ Unstructured Data Sources o Cost of Data Storage & Processing o All of the above
  7. 7. 7© Cloudera, Inc. All rights reserved. Consumer activity data sits in silos • Most organizations have a static version of the customer profile in their data warehouse • Mainly structured data • Only internal data • Only “important” data • Only limited history • Activity data – clickstream data, content preferences, customer care logs, is kept in BU silos or not kept at all Customer 360 view: Why status quo won’t work AnalystData Analyst Data Analyst DataAnalystData AnalystData
  8. 8. 8© Cloudera, Inc. All rights reserved. A New Way Forward…
  9. 9. 9© Cloudera, Inc. All rights reserved. Bridge Silos of Data to Drive A True Customer 360… Care CRM PoS Ordering Billing Billing Inventory Supply Chain Legacy Enterprise Structured Data Islands Clickstreams Social Media Machine Data Sensor Data Log Files Other Unstructured Sources Semi-Structured Data Islands OPERATIONS Cloudera Manager Cloudera Director DATA MANAGEMENT Cloudera Navigator Encrypt and KeyTrustee Optimizer BATCH Sqoop REAL-TIME Kafka, Flume PROCESS, ANALYZE, SERVE UNIFIED SERVICES RESOURCE MANAGEMENT YARN SECURITY Sentry, RecordService FILESYSTEM HDFS RELATIONAL Kudu NoSQL HBase STORE INTEGRATE BATCH Spark, Hive, Pig MapReduce STREAM Spark SQL Impala SEARCH Solr SDK Partners Enterprise Data Hub
  10. 10. 10© Cloudera, Inc. All rights reserved. EDH based Architecture for Effective Data Mgmt. Enterprise Data Warehouse Enterprise Data Hub Data Sources DataIngest– StreamingorBatch Business Intelligence/ Reporting Tools Network Usage CRM Inventory Clickstream Sensors Machine Logs Social Billing Ordering Structured Unstructured /Semi-Structured OPERATIONS Cloudera Manager Cloudera Director DATA MANAGEMENT Cloudera Navigator Encrypt and KeyTrustee Optimizer BATCH Sqoop REAL-TIME Kafka, Flume PROCESS, ANALYZE, SERVE UNIFIED SERVICES RESOURCE MANAGEMENT YARN SECURITY Sentry, RecordService FILESYSTEM HDFS RELATIONAL Kudu NoSQL HBase STORE INTEGRATE BATCH Spark, Hive, Pig MapReduce STREAM Spark SQL Impala SEARCH Solr SDK Partners
  11. 11. 11© Cloudera, Inc. All rights reserved. Customer 360 – Traditional Data Flow Diagram Location Social Clickstream ETL/Stored Procedures Enterprise Data Warehouse Segmentation & Churn Analysis BI Tools Marketing Offers Data Marts / Aggregations Billing/ Ordering CRM/ Profile Marketing Campaigns
  12. 12. 12© Cloudera, Inc. All rights reserved. Customer 360 – Traditional Data Flow Diagram Location Social Clickstream ETL/Stored Procedures Enterprise Data Warehouse Segmentation & Churn Analysis BI Tools Marketing Offers Data Marts / Aggregations Billing/ Ordering CRM/ Profile Marketing CampaignsOther/ New Data Sources – Mobile, Sensors, Apps, Network Logs, Files Does not model easily into traditional database schema Limited Processing Power Limited Processing Power Storage scaling very expensive. Not designed for ELT Loss in Fidelity Manual work. Few automated system feeds. Based on sample/ limited data
  13. 13. 13© Cloudera, Inc. All rights reserved. Customer 360 – Flow with EDH Location Social Clickstream BI Tools Online & Mobile Apps Billing/ Ordering CRM/ Profile Marketing Campaigns Sqoop or Native Connector Flume Secure Kafka Cluster Search EDW Sqoop or Native connector to Impala SQL via Impala Solr HBase N/W Logs Call Center Apps Network Other Structured Sources
  14. 14. 14© Cloudera, Inc. All rights reserved. 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? A Sample Customer 360° Profile
  15. 15. 15© Cloudera, Inc. All rights reserved. How to Iteratively Build a True Customer 360? Customer Data Source Start with ingesting the “best” version of your customer profile Find your common identifiers across datasets: customer name, number, IMEI, IMSI IMEI ChannelsPurchase History Add New Data SourceCommon IdentifierCurrent Source Enrich with additional demographic information (purchase history or channels) from other systems / sources Deliver A Use Case Deliver a specific use case based on the profile with new data sets: • Customer Lifetime value • Next Best offer • Omni Channel Enrich Your Profile • Enrich your customer profiles with purchase behavior • Continue to enhance with each new use case OPERATIONS Cloudera Manager Cloudera Director DATA MANAGEMENT Cloudera Navigator Encrypt and KeyTrustee Optimizer BATCH Sqoop REAL-TIME Kafka, Flume PROCESS, ANALYZE, SERVE UNIFIED SERVICES RESOURCE MANAGEMENT YARN SECURITY Sentry, RecordService FILESYSTEM HDFS RELATIONAL Kudu NoSQL HBase STORE INTEGRATE BATCH Spark, Hive, Pig MapReduce STREAM Spark SQL Impala SEARCH Solr SDK Partners
  16. 16. 16© Cloudera, Inc. All rights reserved. How to Iteratively Build a True Customer 360? Customer Data Source Start with ingesting the “best” version of your customer profile Find your common identifiers across datasets: customer name, number, IMEI, IMSI IMEI ChannelsPurchase History Add New Data SourceCommon IdentifierCurrent Source Enrich with additional demographic information (purchase history or channels) from other systems / sources Deliver A Use Case Deliver a specific use case based on the profile with new data sets: • Customer Lifetime value • Next Best offer • Omni Channel Enrich Your Profile • Enrich your customer profiles with purchase behavior • Continue to enhance with each new use case Location Clickstream Continue to add new data sources iteratively to enhance your customer profile with new use cases Call center Social Media Apps External Data New Data Sources OPERATIONS Cloudera Manager Cloudera Director DATA MANAGEMENT Cloudera Navigator Encrypt and KeyTrustee Optimizer BATCH Sqoop REAL-TIME Kafka, Flume PROCESS, ANALYZE, SERVE UNIFIED SERVICES RESOURCE MANAGEMENT YARN SECURITY Sentry, RecordService FILESYSTEM HDFS RELATIONAL Kudu NoSQL HBase STORE INTEGRATE BATCH Spark, Hive, Pig MapReduce STREAM Spark SQL Impala SEARCH Solr SDK Partners
  17. 17. 17© Cloudera, Inc. All rights reserved. From Static to Dynamic, Real-Time Micro-Segmentation… Traditional Segmentation • Age • Gender • Average Spend • Price Plans • Usage history • Data, Voice, Text • Billing history • Device Upgrade • Age • Gender • Average Spend • Price Plans • Usage history • Data, Voice, Text • Billing history • Device Upgrade • Location • Social Influence • Applications Used • Content Preferences • Usage Details • Roaming Analysis • Travel Patterns • Device History • Other products/ services • Bundling preferences • Offer history • Campaign Adoption History • Call center Tickets • QoS History • Household Analysis • Lifetime Value • Churn Score • Clickstream Info • Channel Preferences • Survey Real-Time Micro- Segmentation
  18. 18. 18© Cloudera, Inc. All rights reserved. Customer 360° - Key Use Cases
  19. 19. 19© Cloudera, Inc. All rights reserved. Customer 360 – Key Use Cases Churn Prevention & Customer Retention Targeted Marketing & Personalization Proactive Care • Churn Modeling & Prediction • Rotational/ Social Churn • Customer Lifetime Value • Sentiment Analytics • Price Elasticity Modeling • Customer micro-segmentation • Next Best Offer • Campaign Analytics • Geo-Location Analytics • Recommendation Models • Proactive Care Dashboard • Customer Lifetime Value • Subscriber Analytics • QoS Analytics • Real-Time Alerts
  20. 20. 20© Cloudera, Inc. All rights reserved. Targeted Marketing & Personalization Collate the Data Sources Micro-Segmentation Drive Personalized Campaigns Devise Micro- segments based on combining multiple factors: • Age • Location • Spending History • Channel Preferences • Content Preferences • Apps Usage • Social Influence • Churn Score • Lifetime Value • Usage Patterns • Data Usage Drive Personalized Campaigns for specific micro-segments Retention campaign for high value customers with iPhone who recently shared a negative social sentiment Upsell campaign for high-data users with family to move over to a family bundle Geo-Location based targeted advertising for specific customer micro- segments 1
  21. 21. 21© Cloudera, Inc. All rights reserved. Churn Prediction & Analytics Customer Data Account Activity Social Media Contact Status Voice Text Data Tweets Handles VisualizationVisualization Data Wrangling Usage/ Activity Analysis Sentiment Analysis QoS Issues/ Customer Care Tickets Targeted Retention Campaigns Churn Prediction & Modeling Big Data enabled Churn prediction models enable Telcos to identify “at-risk” customers and proactively target them with retention programs Churn Score 2
  22. 22. 22© Cloudera, Inc. All rights reserved. Proactive Customer Care Proactive Care Dashboard Customer Service Team Big Data enabled Churn prediction models enable Telcos to identify “at-risk” customers and by proactively target them with retention programs When a High Value Customer’s Quality of Service (QoS) or Experience Index falls below a certain threshold, an alert is sent to the Network and Customer Care team for appropriate resolution Enterprise Data Hub Security and Administration Unlimited Storage Process Discover Model Serve Customer Lifetime Value QoS Analytics Customer Experience Index EXPERIENCE INDEX for HIGH VALUE CUSTOMERS ALERTS Network Ops Team 3
  23. 23. 23© Cloudera, Inc. All rights reserved. 360° View To Optimize Customer Journey • Billions of events generated every day • Needed to bring together multi- structured data from new sources and multiple channels • Optimize customer journey • Centralized, real-time 360 degree customer view that spans many devices and data sources • Improved Data warehouse performance – Life extended up to 3X times CUSTOMER 360 TELECOMMUNICATIONS » CUSTOMER 360° » DATA INTEGRATION » BETTER CUSTOMER SERVICE » JOURNEY ANALYTICS
  24. 24. 24© Cloudera, Inc. All rights reserved. 360° View of Retail Customers / Behavior • Many different data sources integrated (click streams, in-store POS, online ordering, and social media) • Understanding of abandoned online shopping cart behavior • Optimized operational investments by attributing revenue to the appropriate channel • Increased customer insight informs supply chain plans • Improved ability to explain and predict returns CUSTOMER 360 RETAIL / ONLINE » CUSTOMER 360° » PROCESS IMPROVEMENT » BETTER CUSTOMER SERVICE » PREDICTIVE ANALYTICS
  25. 25. 25© Cloudera, Inc. All rights reserved. Delivering an Omni-Channel Customer Experience Challenge: • Gain 360⁰ view of data across mobile, web & retail channels • 29 tx/ min- high volumes of user, clickstream & mobile data Solution & Impact: • Single, integrated omni-channel Customer view across web, mobile or retail • “Send Again” capability for increased customer conversions. CUSTOMER 360 FINANCIAL SERVICES » CUSTOMER 360 » OMNI-CHANNEL » PERSONALIZATION
  26. 26. 26© Cloudera, Inc. All rights reserved. Improved segmentation & targeted marketing by leveraging new data sources Challenge: • Changing customer spending patterns and demographics • Increasing data from semi/un-structured data sources Solution & Impact: • Cloudera – Intel Solution: Enabled fine- grained segmentation to improve marketing results • Increased web-sales conversion CUSTOMER 360 ENTERTAINMENT » CUSTOMER 360 » IMPROVED SEGMENTATION » IMPROVED SECURITY
  27. 27. 27© Cloudera, Inc. All rights reserved. Learn More about our Industry Solutions http://www.cloudera.com/solutions
  28. 28. 28© Cloudera, Inc. All rights reserved. Thank you vijay.raja@cloudera.com aoconnor@cloudera.com
  29. 29. 29© Cloudera, Inc. All rights reserved. Customer 360: Reference Architecture 3rd party alerting Reports, dashboards, apps Near Real Time Event Processing Flume Spark Storage Solr Batch Event Processing Impala Spark Interactivity Impala Solr Ingest Sqoop Flume HDFS HDFS API HBase HBase

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