Analytics Community Reaping Financial Rewards With Big Data Finally! Niren Sirohi, Ph.D. Partner, Data Science & Consulting iknowtion We will be starting at the top of the hour. You will not hear anything until we start.
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Today s Presenter Niren leads iknowtion s Global Data Science Practice and Customer Insight Center Niren Sirohi, Ph.D. Partner, Data Science & Consulting iknowtion 4
iknowtion Overview We apply advanced analytic techniques to help our clients uncover often-hidden insights that solve business problems and drive results Leverage a wide variety of data assets and analytics to improve decision making and drive business value Extensive expertise in: Customer/Marketing/ Product analytics Big Data analytics CX management Omni-channel interaction Voice of customer analytics Highly experienced global staff of 100+ associates with expertise across many vertical industries; focus on driving sizable and enduring business value through customized and automated processes for the Fortune 1000 5
Customer Insights Solutions Customer Value Management Connected Customer Insight CX Optimization Omni-Channel Interaction Management 6
Solutions Powered by Customer Insight Center State of the art analytics expertise, ready to use cloud infrastructure, and proven tools and analytic assets, available as a service Big Data Lab to accelerate identification of practical applications of Big Data and advanced analytics Best of breed tools and techniques to integrate, visualize, and assess the value of digital (social, mobile, voice, text, web) and offline data Custom built predictive and prescriptive self-learning algorithms for key business KPIs Analytic platform enables high volume data ingestion, real-time insights / scoring and work flow orchestration
Big Data is Everywhere 8 Every 2 days we create as much information as we did from the beginning of time until 2003 - Eric Schmidt The boom of IoT means that the amount of devices connected to the internet will rise from about 13 billion today to 50 billion by 2020 - Cisco Every minute we sent 204 million emails, generate 1.8 million Facebook likes, send 278,000 Tweets, and up-load 200,000 photos to Facebook Today's data centers occupy an area of land equal in size to almost 6,000 football fields Source: Advanced Performance Institute, Gartner
ROI? 55% of organizations identify determining how to get value from big data as among the top 3 hurdles Gartner 15 9
Big Data Applications Show Promise Analysis of employee data including that collected with smart badges to improve performance. Bank of America reportedly improved performance metrics by 23% and decreased stress levels by 19%, simply by allowing more staff to take their breaks together. Predictive analytics system deployed on Hadoop to analyze operational data in real-time to detect network issues before they occur 20,000 variables and 50,000 constraints analyzed to determine the optimized game schedule to maximize profit The algorithm analyzes 2400 factors from 330,000 commercial and public buildings to determine a fire risk score. Has attained 70% success in proactively identifying fire hazards in buildings 10 Source: Advanced Performance Institute, Gartner, itnews
11 Big Data Landscape is Overwhelming!
12 Where does one begin?
Effectively Acting on Big Data is a Multi-step Journey Develop Strategy and Prove the Value Identify a few big ideas and use cases for leveraging big data Design the pilots focused on clear business goals and outcomes Develop roadmap and strategy Build Capabilities and Implement Collect requirements from different stakeholders who would value from Big Data insights Develop capabilities (people, process and infrastructure) to collect, analyze, share, respond and act on Big Data Accelerate Impact On-Going Identify test and learn opportunities Launch, measure and refine Big Data programs Add additional data sources and stakeholders Refine capabilities 13
Set up a Big Data Lab in Step 1 of the Journey Run outcomes focused pilots that deliver Quick Wins to demonstrate the value of Big Data technologies, analytics, and strategy from both an IT and business perspective Create Proofs-of-Concept that shows how Big Data thinking can be integrated into the existing enterprise, both from an IT architecture and business process perspective Serve as a Big Data Innovation Center within the company for Big Data and analytics skillbuilding, and for testing new technologies and Big Data applications Cost Effective, Low Risk approach to evaluating Big Data and their applications Rapid prototyping enables incremental payoffs and continuous learning 14
15 Investments Required
People Skills Required Ask good questions Decision makers C suite access and influence Focus on strategic objectives Business High performance computing Open source experts Hadoop and Spark expertise AWS expertise Technology Advanced Analytics Machine Learning Statistical Analysis Algorithm design at scale Feature engineering Breadth and depth of analytic tool knowledge 16
Representative Tech Stack CUSTOMER TOUCHPOINTS ENTERPRISE APPS Call center CRM ebiz Real-time / Batch Via Web services Custom SI Business Systems Action Orchestration Reporting and Visualization BizTalk(MS) Tableau, DataMeer Scoring Event Processing Zementis Predictive & Prescriptive Analytic Engines Exploratory Data Analytics Data processing, Data and signal storage Data ingestion, cleansing, clustering, enrichment Custom Tableau, DataMeer Mongo, Infochimps, Hadoop Infochimps, Clarabridge, Nexidia CUSTOMER TOUCHPOINTS ENTERPRISE APPS Call center CRM ebiz Real-time / Batch Via Web services Custom SI 17
Design Pilots with Increasing Levels of Maturity Analytics Prescriptive Predictive Descriptive Batch, offline Near time Real time Big Data Application Maturity Structured Semi-Structured Un-structured Decisions Data 18
Example: Incorporate Unstructured Data Unstructured data drives more meaningful insights and explains why customers have certain attitudes / perceptions about your brand Depth of Insight Unstructured (Qualitative) Structured (Quantitative) Customer-Initiated Company-Initiated Representativeness of Feedback 19
Domain knowledge and Machine Learning for multi-level models transforms unstructured data into structured insights Illustrative Customer Service Problem Resolution Customer Support Rep Accessibility / Reaching Rep Phone Experience Branches (19) Knowledge / Helpfulness Troubleshooting Communication Skills Transfer / Hold Runaround Attitude Multiple Attempts Follow up Quality of Service Language Barrier Listening Reaching Right Person IVR Hold Time Transfers Leaves (111) Tier 2 Escalation Refunds / Discounts Speed of service Business Hours Real Person 20
Analysis of Unstructured Data Involves Text, Speech, and Contextual Data Across Channels Phone Speech Keywords and Topics Talk Over Analysis Emotion Detection Call Flow Analysis Misinformed Frustrating This is the 2 nd time I m calling Chat Email Social Media Text Keywords and Topics Sentiment Analysis Chat Response Time Social Buzz Dear DirectCom Online Service, I have a question about my most recent bill. l. I paid So the confusing full balance online in the amount of 47.61$ on February 16th. When I checked back the payment didn t t show up, and I was charged 50$ fee on top of that. This is not acceptable! The online ne payment confirmation number back the payment didn t dn t show up, and I was charged 50 and I was charged 50 and I was $ fee on top of that. This is not is 49733. Please verify and make sure I get the fee back to my account. This is not Sick the first and time tired I have a problem with the online payment. Best regards, Gina Lowell. Desktop Analytics Phone Survey Web Context Customer Demographics Interaction History Customer Feedback 21
Automotive CX Drivers A significant improvement in NPS (-29 to +70) is possible by making customer experience improvements Incremental NPS Changes by Making Driver Improvements 80 Structured 60 Unstructured 11 7 6 1 40 20 15 13 10 70 0 17-20 -29 19-40 Current NPS Problem Providing Best Hold Time Personal Resolution Help Effort Dealer Resolution Attempt Listening Courtesy Automated # of Consumer Final NPS Phone Ease of Affair contacts Use 22
Insights can be Incorporated into Predictive Models Unstructured data helps explain more of the observed variation when developing predictive customer behavioral models Observed Benefit by Model Deciles Illustrative Model Performance Variation explained by structured data only Variation explained by both structured and unstructured data Structured plus unstructured Structured only 1 2 3 4 5 6 7 8 9 10 23
Example Big Data Application Execute trades Positive comment on Facebook Adds money to brokerage account Story begins A week ago, high value customer Jack tried to watch a video on our website that failed to load Yesterday, Jack made a negative comment about our fund platform on our Facebook page 3:50 pm Jack placed a large sell order today that did not execute Real Time Listening Big Data Lab Jack is a high value, high risk customer who should get a call from his advisor: Acknowledge issues Offer free trades Ask for recommendation if satisfied Real Time Decisions ALERT! Wealth Management Advisor CRM Web Interactions...... Phone Call 4:00 pm...happy Ending 24
Summary It is more important to create value from Big Data, not just do Big Data Analytics Invest in a Big Data Lab before investing in large scale multi million $ Big Data tech platforms Create Big Data strategy around use cases that are business outcome driven Increase level of analytic maturity over time 25
Thank You Niren Sirohi, Ph.D. Partner, Data Science & Consulting nsirohi@iknowtion.com 781-494-9989 x201 https://www.linkedin.com/iknowtion https://twitter.com/iknowtion Revisit presentation highlights: #BigDataSuccess 26
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