Predictive Customer Intelligence

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1 Sogeti 2015 Damiaan Zwietering Predictive Customer Intelligence

2 Customer expectations are driving companies towards being customer centric Find me Using visualization and analytics to discover new customer segments Ask me Consulting customers on products, services, and social issues Educate me Bringing expertise to every customer interaction Let me choose Offer new products and services based on understanding my wants, needs Options vs. prerequisites, roadmaps vs. checkboxes Unexpected services at unexpected moments 2 Sharing data, location, and new ideas in return for better products and value Know me Excite me 2 Trade with me Grow with me Data and insight connecting the lives of customers, households

3 Organizational capabilities have been a hindrance to customer centricity Inability to gather and synthesize insights to customer behavior, needs and preferences from analysis of multiple data sources Challenged in using analytics to add short-term value or enhance long-term strategy Lack of channel integration and Difficult to deliver omni-channel customer analytics solution able to analyze, score and determine most appropriate action with individual customer Only historical view of customer, resulting in inappropriate or incomplete offers or communications at the time of interaction 3 3 siloed lines of business, causing inconsistent or tactical customer interactions Inconsistent service delivery and weak customer relationships, resulting in low retention Focus on uncoordinated marketing offers - one-hit selling, as opposed to lifetime value

4 The optimized customer insight and engagement process Data Real time or historical Predictive customer insight Enterprise marketing Multi-channel customer interactions Interactive voice response Web Acquisition models Campaigns Campaign response models Offers Churn models Messaging Customer lifetime value Lead management Price sensitivity Cross channel campaign management Product affinity models Segmentation models Real time marketing Sentiment models Marketing event detection Up-sell / Cross-sell models Digital marketing Mobile Short Message Service Chat Social media Customer services Voice 4

5 Organizations can Acquire, Grow and Retain customers by harnessing all customer data to improve customer interactions and relationships RETENTION PERSONALIZATION GROWTH ACQUISITION 5 5

6 Predictive Customer Intelligence key capabilities ANALYZE data to gain critical insights DEPLOY to real-time channels for point-of-impact action ACCELERATE time to value with focused solutions 6 6

7 Many, many rich modeling techniques Demographic Segmentation Churn Modeling, Next Best Offer Real-time Decision Management Social Network Analysis 7 Campaign Management Loyalty Segmentation Customer Value Calculation

8 Real-time decision loop allows predictive models to get even smarter ① An activity occurs that calls for a decision. 3 Facts, recent events, options ② The context from the activity is passed to the decision process. ③ The decision process augments the context with stored information and runs the decision model. ④ One or more actions are recommended to the activity. ⑤ The activity feeds back the results to help tune the model over time. 8 Decision input, actions and outcomes 5 Information 3 Decision 2 Feedback Context Action 4 1 Activity

9 Built-in Connectors provide enhanced functionalities InfoSphere Streams Quickly ingest, analyze and correlate large data sets from real-time sources and interact with individual customers at scale. IBM Interact Allow the power of the deep algorithms to be introduced at the moment of impact, including the inclusion of contextual data IBM Customer Intelligence Optimizer, Lifetime Value Maximizer Optimize customer-specific actions/ offers to maximize long term customer value by moving customers to a higher value state IBM BigInsights Pull together large volumes of all different types of data including social/unstructured information and structured data like transaction details for enhanced discovery (and other Hadoop Distribution) 9

10 Industry accelerators 10

11 Intermediary Policy admin Marketin g Customer Service Advice from Agent Amend Policy Comparison website Complaint Response Second payment Online quote Underwriting Policy paperwork First Claim Terms & Conditions fine print Product development (Adapted) 11 First Payment Billing dept. Finance Cross-sell Campaign Claims management Marketing

12 Acquisition Channel 22% 55% Customer Track (Nature of Interactions) 6% Quality of Claim 81% 32% Claim only 82% Positive 6% Claim & Service 55% 75% Neutral 34% Phone 66% Neutral Very High Positive High Neutral Negative Service only Medium 50% 13% 54% Aggregator Positive 72% 72% 23% Renewal Rate Negative Web 55% Quality of Service 72% 60% Negative No Contact Positive Neutral Low Negative 12 Percentage of customers Renewal rate

13 The retention offer decision depends on the combination of these three factors: Likelihood of Cancellation Future Lifetime Value Loss Ratio Prediction Recommended Action: Service Offer Get ready for summer with a free airco check Recommended Action: Targeted Retention Offer 10% discount with 2 year fixed price guarantee and lower deductible Recommended Action: Targeted Retention Offer 10% discount and lower deductible Recommended Action: Targeted Retention Offer 10% discount with 2 year fixed price guarantee 13

14 Data Sources Predictive Customer Intelligence Architecture Overview GBS Lifetime Value Maximizer Call Center Transactional Data External data - social, blog Customer Demographic Data Segmentation Sentiment Model Analysis Churn Model Up-sell / Cross-sell Model Acquisition Model Campaign Response Model Big Insights Explore new customer insights from all data MDM Trusted customer data Reporting Lifetime Value Maximizer Model (GBS) Real-time Scoring Data Repository for Real Time Analytics SMS Direct Mail Chat Call Center Social Inbound Interactions Customer Interaction History Deep customer analytics Actionable customer data (Industry-specific) Campaign Interact SMS PureData for Analytics Model Repository Marketing execution & recommendation engine Web Unstructured Structured Mobile Apps Predictive Modeling and Optimization WAS / IBM Integration Bus Customer Lifetime Value & Segment Migration Outbound Interactions IBM Predictive Customer Intelligence 3rd party marketing application Chat Points of Interaction Mobile Apps Web SMS 14

15 Behavior-Based Customer Insight Solution for Insurance Generates advanced segmentation and individual insight based on behavior Integration into Marketing & Distribution Dashboards Identifies key target customers to retain Proactively identify "at-risk" customers early Enables channels to act Behavior-based Segmentation Analysis Retention Monitor Behaviorbased Segmentation Segmentation Analysis drilldown Retention Reports 15

16 The IBM difference 16

17 17

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