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Driving Better Products with Customer Intelligence


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In today’s fast moving world, the ability to capture and process massive amounts of data and make valuable insights is key to gaining a competitive advantage. For RingCentral, a leader in Unified Communications, this is very true since they work with over 350,000 organizations worldwide. With such scale, it can be difficult to address quality issues when they appear while supporting additional calls.

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Driving Better Products with Customer Intelligence


  1. 1. 1© Cloudera, Inc. All rights reserved. Driving Better Products with Customer Intelligence August 2, 2017
  2. 2. 2© Cloudera, Inc. All rights reserved. Your Speakers for Today… Amy O’Connor Big Data Evangelist Clarke Patterson Head of Product Marketing Mike Becker Sr Manager of Big Data
  3. 3. 3© Cloudera, Inc. All rights reserved. Polling Question How would you want to interact with your phone/internet service provider? • distinct touch points (one service at a time) • holistic relationship (a relationship over multiple engagements)
  4. 4. 4© Cloudera, Inc. All rights reserved. CUSTOMER & CHANNEL DATA-DRIVEN PRODUCTS SECURITY, RISK & COMPLIANCE Data is driving business transformation
  5. 5. 5© Cloudera, Inc. All rights reserved. Potential Data Sources are Everywhere Digital/Mobile Digital Media • Teradata Aprimo • IBM Unica • Oracle Eloqua • X+1 Web Logs • Microsoft IIS • Apache • nginx • Google GWS Clickstream/UX • Adobe Omniture • IBM Coremetrics • IBM Tealeaf • Google Analytics Premium • Webtrends Mobile Application SMS Transaction CRM/Call Center Demographics Loyalty/Retentio n Social Retail Mobile Web Channel Distributor Bot Call Center Indirect Kiosk Embedded Commerce Service Billing Customer Lifecycle • Acquisition • Churn • Cross-Sell • Upsell CRM • MS Dynamics • Oracle/Siebel • Salesforce • SAP Online Chat • Oracle RightNow • Moxie Live Chat • LivePerson • Instant Service • Oracle Live Help • BoldChat • Zendesk Zopim • Kana Live Chat IVR • Avaya • Cisco • Nortel • Nuance Data Broker / Syndicate • Acxiom • CoreLogic • Datalogix • eBureau • ID Analytics • Intelius • PeekYou • Rapleaf • Recorded Future • IHS Polk • Nielsen • InfoScout • Symphony IRI • Gfk Behavior Loyalty • Aimia • Brierley+Partners • Comarch • Epsilon • Kobie • ICF Olson 1to1 • Merkle • Clutch • CrowdTwist • DataCandy • Deluxe • Inte Q • ICLP Survey • ABA • Medallia • Forsee • Allegiance • Walker Information Direct • Twitter • Facebook • Bazaarvoice Listening/Manageme nt • Sprinklr • Crimson Hexagon • Radian6 • Lithium • Simply Measured • Curalate • Datasift Voice of the Community • CSAT • NPS
  6. 6. 6© Cloudera, Inc. All rights reserved. The Data Journey 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
  7. 7. 7© 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 Source Common Identifier Current 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
  8. 8. 8© Cloudera, Inc. All rights reserved. Cloudera Enterprise – The Platform for Customer 360 Location Social Clickstream BI Tools Online & Mobile Apps Billing/ Orderin g CRM/ Profile Marketing Campaigns Search EDW N/W Logs Call Center Apps Networ k Other Structured Sources Internal Systems External Sources BI Solutions Real-Time AppsSearch Data Science Workbench SQL Machine Learning Systems Data 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
  9. 9. Managing dataflows can be a daunting task Build Development processes are far more complex and drawn out than they need to be Execute The economics of data have changed, giving way to a choice of executing and deployment options Evolve Architectures are constantly changing and have more stringent SLA’s
  10. 10. Build Not all developers are created equally >_ Integrations are abundant and unnecessarily rigid Build-to-deploy takes far longer than necessary
  11. 11. Execute Multiple deployment options exist yet constraints limit making use of them Mixed workloads are the norm, must handle both batch and streaming 11001001001001101001 00101010010010010010 10100100100101010101 01001001001010100100 11010001110010100100 10010010100101110101 Scalability is a must, both today and into the future
  12. 12. Operate Increasingly, the business expects SLA’s on the quality and timeliness of data Architectures are constantly evolving, with new versions or new projects regularly being added Data, and it’s structure, will inevitably change, causing wide spread impact
  13. 13. StreamSets Data Operations Platform EFFICIENCY Intent Driven Flows Batch & Streaming Ingest In-stream Sanitization MASTER Availability & Accuracy Proactive Remediation MEASURE Any Path Any Time MAP Dataflow Lineage Live Data Architecture CONTROL Drift Handling Stage & Flow Metrics Lineage & Impact Analysis AGILITY Flexible deployment Exception Handling Seamless Evolution EVOLVE (Proactive) REMEDIATE (Reactive) DEVELOP OPERATE CloudClusterStandalone StreamSets Data Collector Dataflow Performance Manager Edge
  14. 14. 14© Cloudera, Inc. All rights reserved. Polling Question What are your current challenges when building and maintaining data pipelines? 1. We have too many pipelines to manage. 2. Data sources (data or app version) are constantly changing, requiring frequent updates to pipelines 3. We don't have an effective way to blend batch and streaming workloads 4. It's difficult to gain visibility into the performance of our dataflow pipelines
  15. 15. 15 | © 2016 RingCentral, Inc. All rights reserved. Driving Better Products with Customer Intelligence
  16. 16. 16 | © 2016 RingCentral, Inc. All rights reserved. Worldwide Leader in Cloud Communications & Collaboration 12+ Years of Innovation 18% Revenue committee to R&D 2,200+ Team Members (67% Customer-Facing) 80+ Countries Global Coverage 350K+ Business Customers Magic Quadrant Worldwide Leader 12+ Years of Innovation 18% Revenue committed to R&D 2,200+ Team Members (67% Customer-Facing) 80+ Countries Global Coverage 350K+ Business Customers Magic Quadrant Worldwide Leader
  17. 17. 17 | © 2016 RingCentral, Inc. All rights reserved. Big Data Org  Big Data Applications and Infrastructure  Four Teams: • Big Data Development • Data Operations • Reporting • Advanced Analytics (Data Science)
  18. 18. 18 | © 2016 RingCentral, Inc. All rights reserved. Before Cloudera  Oracle Data Warehouse • Continue to use Data Warehouse extensively • Became expensive as our data Volume grew • New data sources wouldn’t work easily with Unstructured Data (Variety)  Began using Cloudera in 2013
  19. 19. 19 | © 2016 RingCentral, Inc. All rights reserved. RingCentral Analytics Use Cases Using Hadoop  Product Usage Analytics  Marketing Analytics  Quality of Service (QOS)  Carrier Cost Optimizations  Fraud Analytics  Universal Service Fund – Taxes
  20. 20. 20 | © 2016 RingCentral, Inc. All rights reserved. Product Usage Analytics
  21. 21. 21 | © 2016 RingCentral, Inc. All rights reserved. Background 21  All Departments need Product Usage Data  There are Multiple Data Pipelines that deliver data to multiple separate reports  No consistent way of retrieving all product usage for a given account  Requires many man hours to create a report for customers or segments
  22. 22. 22 | © 2016 RingCentral, Inc. All rights reserved. Department Use Cases  Product • General Usage for Capacity Planning • Feature Usage  Product Marketing • Adoption Metrics  Finance • Financial Analysis • Billing  Sales • Sales Reps for Customer Discussions • Churn Prediction  GCC • Customer Support
  23. 23. 23 | © 2016 RingCentral, Inc. All rights reserved. Approach Create a single data base which tracks all product usage and ties the information to a single user • Track daily activity per user per day • Provides ability to roll up product usage for any product by account and segment • Gives RC ability to quickly determine usage by many different dimensions • Multiple Metrics per product: • Glip • Telephone • API Platform • Contact Center • Ring Central Conferening • RC Meetings • Others 23
  24. 24. 24 | © 2016 RingCentral, Inc. All rights reserved.
  25. 25. 25 | © 2016 RingCentral, Inc. All rights reserved. Example Glip VOIP SMS RC Integrations Date Company User Active Posts Attachments Minutes of use Total Calls Incoming Outgoing RingOut Incoming Outgoing SalesForce Google 6/1/17 ACME John Doe Yes 16 2 45 10 4 6 0 2 0 0 3
  26. 26. 26 | © 2016 RingCentral, Inc. All rights reserved. Example Glip VOIP SMS RC Integrations Date Company User Active Posts Attachments Minutes of use Total Calls Incoming Outgoing RingOut Incoming Outgoing SalesForce Google 6/1/17 ACME John Doe Yes 16 2 45 10 4 6 0 2 0 0 3 GLIP Usage Only
  27. 27. 27 | © 2016 RingCentral, Inc. All rights reserved. Advantages  Single Place to retrieve Product Usage  Can Roll up information based on Use Case  Control what information is available to user based on Need to Know  Simplifies consolidation of usage for various use cases
  28. 28. 28 | © 2016 RingCentral, Inc. All rights reserved. Marketing Analytics
  29. 29. 29 | © 2016 RingCentral, Inc. All rights reserved. What is 4D? • The Digital Data Discovery Digest (4D) provides a Single Source of Truth (SSOT) and a 360 degree view of our prospects & customers enabling interdepartmental alignment on source data for KPIs. • Additionally 360 degree data and predictive modeling enable more targeted Marketing spend. • 4D links all digital behavior (for converted leads – i.e. users that fill out a web form) to in funnel data (i.e. Marketing Automation, CRM, product usage data, etc.) • 4D enables associations of all people data to a company leveraging RingCentral’s Total Addressable Market (TAM) DB. • 4D provides complete flexibility and is vendor agnostic in its design enabling future customization and changes in definition, classifications, etc. with minimal effort. RingCentral 4D Project Overview
  30. 30. 30 | © 2016 RingCentral, Inc. All rights reserved. Core Design Objectives: Data is aggregated in a data pool where it can be standardized, unified, enriched and transformed providing a common data set following MDM best practices. All departments can then utilize summary tables and data cubes for reporting while maintaining alignment on the core data used for all measurements. 4D Reporting Architecture
  31. 31. 31 | © 2016 RingCentral, Inc. All rights reserved. Closed Loop Feedback: Data is fed back into the digital tech stack enabling improved digital segmentation and omnichannel tactical communication improvements. For example: Automagically recommend the next best action for prospects based upon their digital behavior and engagement behavior in various channels and/or with various RingCentral departments. 4D Production Value
  32. 32. 32 | © 2016 RingCentral, Inc. All rights reserved. QOS
  33. 33. 33 | © 2016 RingCentral, Inc. All rights reserved. QOS Analytics  Measure Quality of Our Calls  Need to Measure Quality across Multiple Systems • SONUS – Carrier Gateway • ACME – Internet Gateway • RTCPXR – IOT from VOIP Phone
  34. 34. 34 | © 2016 RingCentral, Inc. All rights reserved. SONUS/ACME QOS Architecture SONUSRC Media Server ACMERingCentral VOIP Carrier Core External Carrier Network Customer’s ISP Provider ACME ACME SONUS {} ACME SONUS SONUS RTCPXR {}
  35. 35. 35 | © 2016 RingCentral, Inc. All rights reserved. QOS Call Record Correlation Indexed CDR with Common Key Loaded Directly into Hbase and Vertica with Multiple CDRs Correlated QOS Record with Meta Data for Call Generated after 12 Hours written to HDFS and Vertica
  36. 36. 36 | © 2016 RingCentral, Inc. All rights reserved. Convert from Indexed Format to Consolidated Record Date Time Company ID Source RCSessionID SONUS Carrier SONUS MOS Score ACME Location ACME MOS Score RTCPXR Location RTCPXR MOS Score 6/1/17 20:15 12345 SONUS qwerty Carrier_ID 4.5 6/1/17 20:15 12345 ACME qwerty New York 4.2 6/1/17 20:15 12345 RTCPXR qwerty New York 4.2 SONUS ACME RTCPXR Date Company ID Time RCSessionID Carrier MOS other Location MOS ISP Location MOS Other 6/1/17 12345 20:15 qwerty US Based Carrier 4.5 New York 4.2 ACME New York 4.2 Indexed UCDR Correlated UCDR
  37. 37. 37 | © 2016 RingCentral, Inc. All rights reserved. Carrier Cost Optimizations
  38. 38. 38 | © 2016 RingCentral, Inc. All rights reserved. Carrier Cost Optimization  SONUS is source system  Correlate Carrier Legs of Call to Trunk  Trunk corresponds to Carrier  Carrier Rates are uploaded and applied to SONUS  Generate Reports for Carrier Costs
  39. 39. 39 | © 2016 RingCentral, Inc. All rights reserved. Call Rating Logic
  40. 40. 40 | © 2016 RingCentral, Inc. All rights reserved. Carrier Cost Optimizations
  41. 41. 41 | © 2016 RingCentral, Inc. All rights reserved. Rated Calls Rolled up by Carrier Partner
  42. 42. 42 | © 2016 RingCentral, Inc. All rights reserved. Fraud Analytics
  43. 43. 43 | © 2016 RingCentral, Inc. All rights reserved. Business Problem Overview Use Customer Traffic To Determine Abuse o Fraudulent users send telephone traffic to high cost areas – we have to watch for it o The quicker this usage is detected and investigated the quicker it can be stopped
  44. 44. 44 | © 2016 RingCentral, Inc. All rights reserved. Network Terminating Costs by Day Fraudulent traffic started on Friday and was stopped on Monday (Dark Green)
  45. 45. 45 | © 2016 RingCentral, Inc. All rights reserved. Vendor Costs and Minutes vendor daily cost dollars increased dramatically vendor daily minutes increased as well
  46. 46. 46 | © 2016 RingCentral, Inc. All rights reserved. Finance Federal Universal Service Fund (USF)
  47. 47. 47 | © 2016 RingCentral, Inc. All rights reserved. USF – source wiki The Universal Service Fund (USF) is a system of telecommunications subsidies and fees managed by the United States Federal Communications Commission (FCC) intended to promote universal access to telecommunications services in the United States. The FCC established the fund in 1997 in compliance with the Telecommunications Act of 1996. The fund reported a total of $7.82 billion in disbursements in 2014,[1] divided among its four programs. The fund is supported by charging telecommunications companies a fee which is set quarterly. As of the third quarter of 2016, the rate is 17.9% of a telecom company's interstate and international end-user revenues.
  48. 48. 48 | © 2016 RingCentral, Inc. All rights reserved. USF  Fee is passed onto Customer  Only Call’s that terminate or originate in the US • Determine US State of Origin of Call • Determine US State of Termination of Call  Categorize calls into: • Intrastate • Interstate • International  Calculate volume that is International or Interstate as percent of total
  49. 49. 49 | © 2016 RingCentral, Inc. All rights reserved. USF – Terminate on RC Network
  50. 50. 50 | © 2016 RingCentral, Inc. All rights reserved. USF – Terminate on RC Network
  51. 51. 51 | © 2016 RingCentral, Inc. All rights reserved. USF – Originate on RC Network
  52. 52. 52 | © 2016 RingCentral, Inc. All rights reserved. RingCentral Analytics Use Cases Using Hadoop  Product Usage Analytics  Marketing Analytics  Quality of Service (QOS)  Carrier Cost Optimizations  Fraud Analytics  Universal Service Fund – Taxes
  53. 53. 53© Cloudera, Inc. All rights reserved. Q&A
  54. 54. 54© Cloudera, Inc. All rights reserved. Q&A Session Amy O’Connor Big Data Evangelist Clarke Patterson Head of Product Marketing Mike Becker Sr Manager of Big Data
  55. 55. 55© Cloudera, Inc. All rights reserved. Thank you

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