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Turning Big Data into More Effective Customer Experiences
The document discusses the need for companies to leverage big data to enhance customer experiences through personalization, highlighting barriers such as technology limitations and ineffective customer insights. It proposes a solution called 'Lily' that enables real-time personalization by combining various data sources to create a comprehensive customer profile. The aim is to transform customer interactions and improve marketing strategies through actionable insights derived from continuous data analysis.
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Turning Big Data into More Effective Customer Experiences
- 1. Turning Big Datainto More Effective Customer Experiences Experience the Difference with Lily
- 2. New channels adoptedby the Customer Years until mass adoption 68 years 50 years 38 years 22 years 14 years 7 years 3 years 2 years Airplane Telephone Radio Television PC Internet iPod Facebook Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 2
- 3. New channels adoptedby the Customer 3,000,000,000 2,500,000,000 2,000,000,000 1,500,000,000 1,000,000,000 500,000,000 0 We are here Tablets Smartphones Personal Computers Global Internet Device Sales 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012e 2013e 2014e 2015e 2016e Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 3
- 4. And it’s gettingworse… How to deal with all this data? What value is in there? Internet of THINGS provides more information than ever before Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 4
- 5. The Value ofData 94% of those surveyed believe that "personalization is critical to our current and future success” Source: Econsultancy, Digital Marketing Exchange However, few companies have been able to implement Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 5
- 6. Connecting with theCustomer Preferences Context Affinities Behavior Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 6
- 7. Barriers to CustomerExperience Management 84% regard IT roadblocks and lack of technology as barriers to adopting or improving personalization Source: Econsultancy, Digital Marketing Exchange No Solutions – No Automation – Manual Work – Low ROI Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 7
- 8. Customer Experience CustomerSpamming is doing more damage than good Relevance? Awareness? Value? Timing? Clarity? Customer insight is limited to a subset of available data - Limiting relevance and timeliness of offers Social Data Company Customer Network Data Usage QoS Call Details Mail SMS Customer Data Customer CRM Systems direct mail shop web agent, IVR email mobile chat Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 8
- 9. Answering the ToughQuestions… Which top hundred customers are likely to buy my product X today? I have a customer - what are the top 3 products he is likely to buy? What is the best channel to connect with my customer, and when? Can I turn around my most valuable potential churners? Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 9
- 10. The Personalization CustomerExperience “I have a customer – what does that customer need most?” Excellent! Fun! Great! Relaxed! Safe! Company’s KPI’s improve: Customer Satisfaction & Advocacy / Retention / Profitability shop QoS Network Data Call Details Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 10
- 11. Towards a newarchitecture One single customer view App Phone Mobile www STB Network Shop Call Centre CDR POS Personalization Acquisition Journey ARPU / CLTV Marketing Advertising Churn Fraud App Phone Mobile www STB Network Shop Call Centre POS CDR Personalization Acquisition Journey ARPU / CLTV Marketing Advertising Churn Fraud Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 11
- 12. Overcome “Analysis Paralysis” Proactively Engage with Customers Transactional Cope with plethora of data Engagement Content Offers Location Socio-Demographic Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 12
- 13. DNA: Understand Lifestyleand predict behaviour Many think that ‘Life stage’ is sufficient to capture and understand underlying ‘Needs’ • Born in 1948 • Grew up in Great Britain • Married, w/ children • Successful, wealthy, celebrity • Loves dogs and the alps • Born in 1948 • Grew up in Great Britain • Married, w/ children • Successful, wealthy, celebrity • Loves dogs and the alps Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 13
- 14. Current Reality NoSolutions – No Automation – Manual Work – Low ROI Customer Back Office Systems Call Details Network Data Customer ERP/CRM Data Customer Interactions External Data 3rd Party Reference Data External Systems 3rd Party Master Data Reporting / Analytics Enterprise BI and reporting Applications Social Data Company and Customer activity Customer Web and Mobile Customer Website And Online Apps Mobile App Server Customer Channel Campaigns Mail SMS Print POS Marketing Campaign Mgt Customer Service Desk Customer CRM systems 3rd Party Operational Data Enterprise Analytics Applications Sample data sets – File extractions – Files ? Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 14
- 15. Lily Real TimePersonalization Within the Current Enterprise Architecture – Improving existing BI landscape Reporting / Analytics Enterprise BI and reporting Applications Enterprise Analytics Applications Lily Enterprise Interaction Database Single View DNA Targeting Customer Back Office Systems Call Details Network Data Customer ERP/CRM Data Customer Interactions External Data 3rd Party Reference Data External Systems 3rd Party Master Data Social Data Company and Customer activity Customer Web and Mobile Customer Website And Online Apps Mobile App Server Customer Channel Campaigns Mail SMS Print POS Marketing Campaign Mgt Customer Service Desk Customer CRM systems 3rd Party Operational Data Lily Enterprise Connector – ETL Tools Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 15
- 16. Lily Listen –Learn: Know Your Customer From siloed channel interactions into ONE customer “DNA” Lily Learn: Lily Listen: Channel all sources of customer interactions into one data model Lily Customer Matching – VCE Interaction DB Lily Listen Lily Learn Lily Customer DNA Debit & Credit Card Transactions CDR Data Call Data Online Data Network Information CRM and Demographic Location Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 16
- 17. Lily Delivers NextGeneration Personalization From Raw Data to Individual Preferences Fully Automated Product Preference Learning Transactional Engagement Content Offers Location Socio-Demographic Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 17
- 18. Turning Data intoValuable Customer DNA Identify unique customer behaviors and preferences in real time View thousands of metrics for each customer Continuously monitor customers’ evolving preferences to identify opportunities Bring Analytics to the data – Open towards DW/BI Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 18
- 19. Lily Customer DNA- Value • Bigger: Scale trumps Smarter and Better • Results Driven: Actionable DNA • “AND” not “OR”: Co-existing with DW/BI • Prescriptive: Trends better than Values • Big Data Governance • Continuous learning • Objective: Facts on everyone’s desk • Architecture: One Single View Discover the Unknown Unknowns with a single view of your customers always available… Analytics Transactions Strategic Machine Learning Bigger is Better Current BI Solutions Prescriptive Customer DNA Results-Driven Genius of “AND” Maximize Architecture Objectivity Governance Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 19
- 20. From Data toDNA Lily Common Customer DNA Industry DNA Extensions variable calculation engine Lily Data Model for Telco Model Specific DNA Customer Item Interaction QoS Other map / load / transform: interactions with context & customer source records data sources Custom DNA extensions e.g. analytical data sets Context customers, products, subscriptions, contracts, transactions, interactions, market & social data Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 20
- 21. Copyright 2014 NGDATA®,Inc. Confidential – Distribution prohibited without permission 21
- 22. Lily Enterprise FromData to DNA – 1000s of metrics determine individual DNA See everything together – comparisons with a Set defined by you, and evolving trend scores for each customer Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 22
- 23. Lily Enterprise Dynamically created Sets defined by your own rules More effective Alerts based on real-time customer metrics Models available, or easily and dynamically add new models from all available metrics Manage Big Data - Breaking down data silos to gain insights on all customer interactions in one place With Lily’s Customer DNA and Machine Learning Engine, individual product Preferences are available each moment Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 23
- 24. What’s different? “Mytraditional BI environment will give the answers tomorrow of yesterday’s problem” CIO leading US Bank Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 24
- 25. Key Value Proposition– result in < 90 days Single View of the Customer Customer DNA Standard Data Model & DNA Machine Learning • Ingest from any data source: batch, streaming, trickle-feed and ODI • Expose through REST/Java/SQL for marketing execution, BI and Analytics • Customer-centric data organization • 1000s of built-in customer metrics • Automatically calculated based on factual & interaction data • Tracks metrics over time for trend analysis & alerts • Standard customer-centric data model for finance, retail, telco and media, with support for behavior data • Default DNA categories e.g. Socio-demo, Life Time Events, Mobility, Affluence, Social, Affinity, Lifestyle, Competitor, Segment, Communication Preferences, Communication History, .... • Extensible/customizable • Broad range of built-in techniques e.g. Collaborative filtering, clustering, classification, RF, logit, rule-based • Support business use cases e.g. Recommendations Xhurn prevention Xustomer acquisition Aegment of one Targeted marketing Personalized service Real-time updates Online, continuous learning Automated metrics calculation Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 25
- 26. Use Cases forTelecommunications
- 27. 1-2-1 Marketing andMicro Campaigns Telecom “ With the international expertise of NGDATA, our CRM department now exists at the center of all our inbound and outbound customer interactions, sharing real, actionable business intelligence and insights, executing hundreds of targeted campaigns on a yearly basis.” Result Director of CRM and consumer Intelligence, major telco Individual Product and Content Preferences – Marketing campaigns with higher Frequency (> x10), higher Response rate (x4) and reduced Budget (< ½) Objectives • Improve ROI (conversion ratio) of Marketing Campaigns by targeting individual customers Solution • Real-time ingest of CDRs • DNA with focus on usage, network, context based interactions and product preferences • Learned preferences to feed event-based marketing actions & send SMS offer to stimulate subscription renewal • Personalized video Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 27
- 28. Churn Prevention Telecom “ To gain maximum profit from retaining customers, companies should consider not only the churn probability of customers, but also how to mitigate that risk, the likelihood that they will respond to the right retention offer, and the cost of the offer itself.” Result Director of CRM and consumer Intelligence, major telco Real Time Churn Propensity – Being prescriptive on Churn and reduced attrition with more than 20%. Objectives • Improve customer retention and loyalty through prescriptive churn scoring Solution • Real-time ingest of CDRs • Customer DNA with focus on usage, payment status, claims, helpdesk calls,... • Detect trends and trigger alerts to inform call center agents in real time and to feed marketing actions to stimulate subscription renewal and upselling Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 28
- 29. Experience the Differencewith Lily Listen Bigger. VOLUME Learn Faster. Volumes of Data Availability Questions Answered SPEED Execute Smarter. QUESTIONS Unknown Unknowns Known Unknowns DW/BI Known Knowns Start working with Lily to discover Day 1 results Zettabytes Exaabytes Petabytes Terabytes Gigabytes DW/BI Seconds Minutes Hours Days Weeks DW/BI Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 29
- 30. Copyright 2014 NGDATA®,Inc. Confidential – Distribution prohibited without permission 30
Editor's Notes
- #3 Years till mass adoption