Consumer Analytics Blueprint for Auto Industry, powered by pm square

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The Automotive industry is very competitive and winning the hearts and minds of consumers is critical. PMSquare's Consumer Analytics Blueprint for the Automotive industry creates the platform for competitive differentiation within this space and leverages IBM technologies

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  • Current State Pain Points Xx Xx Xx Xx Xx Long-Term Expansion Options Xx Xx Xx Xx Xx
  • Current State Pain Points Xx Xx Xx Xx Xx Long-Term Expansion Options Xx Xx Xx Xx Xx
  • Current State Pain Points Xx Xx Xx Xx Xx Long-Term Expansion Options Xx Xx Xx Xx Xx
  • Current State Pain Points Xx Xx Xx Xx Xx Long-Term Expansion Options Xx Xx Xx Xx Xx
  • Current State Pain Points Xx Xx Xx Xx Xx Long-Term Expansion Options Xx Xx Xx Xx Xx
  • Current State Pain Points Xx Xx Xx Xx Xx Long-Term Expansion Options Xx Xx Xx Xx Xx
  • Current State Pain Points Xx Xx Xx Xx Xx Long-Term Expansion Options Xx Xx Xx Xx Xx
  • Current State Pain Points Xx Xx Xx Xx Xx Long-Term Expansion Options Xx Xx Xx Xx Xx
  • Current State Pain Points Xx Xx Xx Xx Xx Long-Term Expansion Options Xx Xx Xx Xx Xx
  • Current State Pain Points Xx Xx Xx Xx Xx Long-Term Expansion Options Xx Xx Xx Xx Xx
  • Current State Pain Points Xx Xx Xx Xx Xx Long-Term Expansion Options Xx Xx Xx Xx Xx
  • Current State Pain Points Xx Xx Xx Xx Xx Long-Term Expansion Options Xx Xx Xx Xx Xx
  • Current State Pain Points Xx Xx Xx Xx Xx Long-Term Expansion Options Xx Xx Xx Xx Xx
  • Current State Pain Points Xx Xx Xx Xx Xx Long-Term Expansion Options Xx Xx Xx Xx Xx
  • Current State Pain Points Xx Xx Xx Xx Xx Long-Term Expansion Options Xx Xx Xx Xx Xx
  • Consumer Analytics Blueprint for Auto Industry, powered by pm square

    1. 1. Automotive Industry Consumer Intelligence Blueprint powered by PMSquareConsumer Analytics to Drive Business Results
    2. 2. PMSquare Provides Consulting Services & solutions with detailed practical experience across all industriesC o n s u lt in g S e r v ic e s Focus Areas:• C u s t o m e r A n a ly t ic s & R e p o r t in g : Helping businesses stay focused on their customers with innovative and effective approaches to Telco & Financial Healthcare Consumer Automotive marketing, sales and customer service. High Tech Services Products• F in a n c e & P e r f o r m a n c e M a n a g e m e n t : Exploring the relationship between finance mastery and achieving high performance, and delivers experience and assets that can help businesses and governments master their Financial Performance Management finances with comprehensive approaches backed by -Budgeting, Forecasting & Planning proven assets. -Risk Management• Ta l e n t & O r g a n i z a t i o n Business Intelligence P e r f o r m a n c e : Guiding companies toward strategic ways of elevating an organization’s -Analytics, Reporting, Scorecards & Dashboards performance with services in change management, -ETL & Data-warehousing human capital and organization effectiveness, -Predictive Analytics• O p e r a t io n s & S u p p ly C h a in Productivity Improvement Solutions P e r f o r m a n c e : Improving visibility of operational performance, turning insights into action -Improve administration & mainteance that drive performance.
    3. 3. Business Value AchievedA f e w IB M c o g n o s c u s t o m e r s t h a t h a v e t a k e no u r a d v ic e :
    4. 4. Automotive Consumer Intelligence BlueprintBusinessPriorities Revenue Protection Profitable Growth Replace Organic DemandApproach Design Consumer Experience & Value Understand Consumer Propensities Deliver Branded Consumer Experience Proposition • Purchase • Brand/model research • Dealership • Defect • Purchase/financing • Web • Repurchase • Ownership/OnStar • Contact center • Recommend • Warranty/Service • Brand advertising Opportunity Segments Core Enterprise Segments Demographic SegmentsIllustrative Discontinued Brands Most Valuable Brand Advocates GeographicConsumerSegments Competitor Defectors Highest Potential Highest Risk Lifestage/Lifestyle Analytics & Propensity Reporting Marketing Automation Consumer Centric KPIsKeyEnablers Integrated View of the Organization Marketing Processes Consumer Research Consumer
    5. 5. three themes emerged as operational priorities Operational Priorities Data Foundation Advanced Analytics Marketing Programs Simplify, integrate and make data Develop and deliver timely, Enable faster, more effective accessible for efficient and effective relevant, actionable insights to drive responses to changing market analysis business decisions conditions and consumer needs What We Heard“There’s a mentality that more [data] is “We want to be able to see results in “We conduct a number of marketingbetter, but not everything is valuable. “ easy formats…including what worked, activities, but we don’t know what what didn’t and why” drives which behavior.”“A lot of things already in our DW arenot used” Most of the current [reports and “What intrigues me is knowing what dashboards] are measuring effort, not levers to pull with fence sitters”“We need to get analytics and insights results”quicker…there’s a lot of help needed “We do everything in such bigon the analytic setup.” “We need to be able to understand numbers that we don’t have time [to the customer in a cohesive and be proactive] because the next wave“Operationally, analytics are painful.” integrated manner.” is coming.”“There is too much data; we are lost in “We need to understand how the “We are struggling to get out what wethe noise.” information will be used to drive are getting out.” decision making”“It has been nobody’s job to bring all “There is no time to just “step backthis information together. ” “I need help prioritizing and digesting and think” the volumes of data that already exist”“The governance issue is the hardest… “We have a lot of capabilities; we justWe have a culture where we say ‘Play “We need…information that will help don’t have the time”nice, but do it my way’.” drive actions. ”
    6. 6. Recommended “Consumer Analytics Strategic Roadmap” Data SimplificationDataFoundation Consumer Info Governance 360° View of the Customer BI Dashboards (in waves)AdvancedAnalytics Make/Model Propensity Propensity for Car Service Defection Probability Consumer Segmentation Free Agent Contact Strategies Next Best Product & Service Call Center: Next Best ActionMarketingPrograms Vehicle Service History Optimize Contact Strategies Regional Web Marketing Consumer Insights Sharing Near Term - 180 Days Longer Term Capability Building
    7. 7. Consumer Intelligence Architecture Dealer Online Customer Access CARS Services Owner Centre BI Portal Industry Info Web Sites Service Integrated Sales, Data Mining, Event Detection & Customer Analysis & Service, Marketing & Clustering, Communication Pattern Recognition Portfolio Test Cell Discovery Management Reporting & Analytical Modelling Management Next Best Action Optimization DevelopmentInformation Services Master Data Data Lifecycle Hierarchy Event Transport and Collaboration Information Integrity Management Services Management Management Security and Privacy Information Contact Data Metadata Scheduler Customer ETL Survivorship Integration Hygiene Services Agent Recognition Source Sales Leads, Service, RO, Customer Data (CDR, CUV) Handraisers CARS Parts Warranty Cust Service Other Satisfaction Interactive Data Campaign Analytic Reporting Quick Count, Data Repositories Mart Mart Digital E-Data Store Mart Mart OLAP Mart (ODS) Systems and Systems Management Network & Middleware Complex Event Hardware & Software Infrastructure & Administration Processing
    8. 8. Solution Initiatives Page 8
    9. 9. Defection Probability and PredictionLeverage data and analytical tools to identify orphaned or disenfranchised consumers and drivers of high defection probability DESCRIPTION: Defection probability analytic used to Dashboard determine customer level of risk and prime Element of drivers for defection based upon existing Customer Profile consumer data. Customer The output of the analytics will drive Pay for Customer Customer defection-aversion marketing campaigns, Repairs Data Satisfaction Analytics Marketing Initiative provide customer knowledge dashboard Credit Drivers Card elements, and provide insight into sales Warranty Dealer Information Call forecast fluctuations. Center Data Prod/Ops Data Systems InputBUSINESS VALUE: Mitigate risk of defection by allowing for a pre-emptive, targeted marketing and/or DEPENDENCIES: incentive response to at-risk, in-market • Technology/Data: Minimal data integration consumers based upon consumer Data Analytics Programs preferences, perceptions, and sensitivities to increase accuracy and completeness of and prime drivers for defection. This would analytics • Process: Campaign management process RESULTS & OUTPUTS: potentially reduce cost for high-return, • Defection probability by consumer that can focused campaigns. should incorporate the output of the model be analyzed by dimensions such as • People/Organization: N/A geography, segment, brand, defection driver, demographic • Prescriptive analytics on next steps based 180 days 12mo 24 mo 36mo on consumer demographics and behavior DATA ELEMENTS: • Visual risk spectrum (green, yellow, red) • Consumer demographic, behavioral, imbedded in the customer profile. CONSIDERATION: historical, marketing survey data, consumer • Delineators indicate trigger points for • Marketing needs to incorporate high-risk service interaction, CARS interaction incentive program eligibility. consumers in targeted campaigns • Analytics database to support probability • Recommend continuous improvement algorithm calculations training and update key performance indicators (KPI’s) • Recommend posting to IR services
    10. 10. Make and Model Propensity MappingApplication of vehicle preference to key populations for precision targeting DESCRIPTION: Predictive algorithm deployed against all consumers to identify make and model Dashboard propensity. Element of Customer Profile This model can be used solo or in concert Customer Pay for Customer with other indicators such as orphans/free Customer Satisfaction Marketing Initiative agents brand correlations or defection Repairs Data Analytics Drivers indicator to trigger an outbound offer for Credit Card retention. Call Warranty Dealer Information Center Data Prod/Ops DataBUSINESS VALUE: Systems Input Increase probability of sales byallowing for a pre-emptive, targeted marketingand/or incentive response to in-marketconsumers based upon predictive consumer DEPENDENCIES:preferences, perceptions, and sensitivities andprime drivers for purchase. This would • Technology/Data: Minimal data integrationpotentially reduce cost for high-return, focused to increase accuracy and completeness of Data Analytics Programscampaigns. analytics • Process: Campaign management process RESULTS & OUTPUTS: should incorporate the output of the model • Production algorithm to identify brand and • People/Organization: Will require cross make propensities 180 days 12mo 24 mo 36mo brand collaboration • Summary of propensities tied to in market indicators for immediate targeting of those consumers with interest in corresponding CONSIDERATION: DATA ELEMENTS: offer • On some makes/models, 90% of • Scoring of inbound leads to create greater • Consumer demographic, behavioral, customers will defect after name plate is intelligence for dealers in prospecting psychographic data eliminated • Make and model mapping can be • Historical, regional, territory sales • Recommend continuous improvement constrained by channel or demographics training and update key performance • Consumer-level historical data for smarter target marketing (e.g. Under 35 indicators (KPI’s) • Customer communication preferences market)
    11. 11. Free Agent Contact StrategiesRelevant and timely offers and messages for at-risk and orphaned customers DESCRIPTION: Construction and execution of treatment At Risk – plans and strategies to retain free agents and Contact Filtered other at-risk owners. Rules Stream Performance Contact ReportingBUSINESS VALUE: Universe At RiskFocus on the most effective cadence of Scores No Riskcommunications to decrease out of pocket Standardcosts and improve total ROI. Stream DEPENDENCIES: • Technology/Data: Leverage data from other Data Analytics Programs initiatives 180 days 12mo 24 mo 36mo • Process: Develop a contact management strategy by treatment plan RESULTS & OUTPUTS: CONSIDERATION: • People/Organization: Will require cross • Periodic identification of at risk owners for • Leverage data from unstructured target treatment plans brand collaboration communications. • Identification of foundational metrics to • Information feeding the treatment plans and baseline customer interaction strategies would support proactive contact • Reduction of non-targeted market spend strategies to acquire customers. • Tailoring contacts to free agents and DATA ELEMENTS: orphaned consumers will enhance overall • Consumer demographic, behavioral, experience and messaging, and reinforce psychographic data the ‘they know me, they get what I need” • Campaign history across all channels and perception lines of business: • Unica campaign management can be used • Campaign history to provide automation • Card member services 11
    12. 12. Consumertrends such as household, consumer valueAn integrated view of key performance factors and Centric BI DashboardsDESCRIPTION:Visualization portal providing access to keyprospect and customer metrics and trends atcampaign, corporate, dealer or consumersegment levels. Offering parameters forpredictive inquiries, and predicated by theassessment of customer value andengagement metricsBUSINESS VALUE:Ability to analyse underlying performancedrivers (positive/negative) to take advantage ofmarketing opportunities and corrective action DEPENDENCIES:on underperformance. • Technology/Data: Leverage data from otherCentralization, consolidation and prioritization initiatives, centralized dashboard portal. Data Analytics Programsof dashboard and information there in. KPIs need to be defined and agreed on“Subtract as we add”- Assess existing • Process: Adoption of Voluntary analytics to RESULTS & OUTPUTS:dashboards to remove clutter as we drive decision making • Strategic, Tactical and Operationaladd new focused dashboards. • People/Organization: Cultural shift to dashboard that enables scenario consumer orientation planning / decision making. E.g. • Current and predictive customer 180 days 12mo 24 mo 36mo value by key customer segments DATA ELEMENTS: and divisions, displayed in • Service, Sales and lead data dashboard format, coupled withCONSIDERATION: • Consumer demographic, behavioral,• Technology can be scaled to accommodate customer engagement metrics and psychographic data trends, and associative activity additional or complementary analytics and • CSAT Engagement Indices visuals i.e. media/channel spend • Current and forecasted campaign • Call Center history/flags response metrics, drillable by• Dashboards should serve different needs • Brand health metrics consumer, offer, regional attributes from strategic to tactical to operational• Advanced marketing science needs to be applied for advanced analytics
    13. 13. Online Vehicle Service HistoryEnabling better customer service with more complete vehicle service histories DESCRIPTION: Presentation of vehicle service records into an integrated vehicle service history view on the online owner centre; also available via 6/8/2008 Upgrade Accessory web service to customer service centres, and Consumer dealers. Login to 12/1/2007 Warranty Repair Service Web Portal 10/1/2005 Oil & Filter ChangeBUSINESS VALUE: 12/1/2005 Warranty Repair ServiceIncrease customer satisfaction and retention by 8/1/2004 Oil & Filter Changeproviding better ownership experience. Enablecontact points to better serve consumers anddriving traffic to websites. DEPENDENCIES: • Technology/Data: Comprehensive dealerTIMING: service data Data Analytics Programs • Process: Contact point training • People/Organization: Collaborate with RESULTS & OUTPUTS: 180 days 12mo 24 mo 36mo service channels to develop standard • Standardized interface to populate interfaces and gain buy-in to maximize integrated service history view into various speed to market customer service applications and portals CONSIDERATIONS: • Instructions, technical guidelines, and • Motivating dealers to share vehicle service terms and conditions for use of integrated data is a critical first step toward delivering service history data a consistent branded consumer experience DATA ELEMENTS: • Vehicle service records • It is important to keep the interface simple and easy to use for service representatives • Owner identification and consumers • Potential to provide service history by VIN on demand to consumers
    14. 14. Regional Web MarketingEnable to identify and act on the regional characteristics of anonymous consumers on its websites DESCRIPTION: This effort would allow customer to identify the country and/or region of users accessing its websites. P2 R 2 Technology to enable customer to display P3 regional and/or country-specific website advertising using a rules-based engine and Car.com R1 R3 P4 product mapping for each region / country. P4 R 4 P4BUSINESS VALUE: Dynamic ad display based on region/country source of web surferIncrease leads by providing relevant content onwebsites DEPENDENCIES: • Technology/Data: Rules-based product and/or service advertisement mapping Data Analytics Programs based on regional and/or country identification to enable packet-specific RESULTS & OUTPUTS: advertisement pops. Dynamic website • Deterministic traceback services to enable messaging technology region / country identification of website • Process: browsers • People/Organization: Legal review for identification considerations in each country 180 days 12mo 24 mo 36mo conducts business CONSIDERATION: DATA ELEMENTS: • Government entities have upheld the right • Consumer IP address for individual anonymity on the web • Creative content • Deterministic traceback software provide identification at the packet (region or country) level.
    15. 15. Consumer Information GovernanceDefine consumer metrics and establish governance around consumer information Information Governance Levels DESCRIPTION: Sophisticated 14% Processes and management 42% Establish governance for customer systems that are strong with some supporting automation in place information including definitions, 32% 3X metrics/KPI’s, usage rules, business ownership, and where applicable systems of Competitive Defined processes and management record. 25% systems that are understood and adopted by most people 54% 33% Rudimentary A few basic processes and the beginnings of a management system Lower performers Top performers (i.e., 4th and 5th quintiles relative (i.e., 1st quintile relative to to industry peers) Source: Breaking Away with Business Analytics industry peers)BUSINESS VALUE: and Optimization: New intelligence meets enterprise operations at www.ibm.com /gbs/intelligent-enterprise.Will promote cross brand collaboration bypropagating single source of truth. Will DEPENDENCIES:establish common metrics used to run/assessbusiness performance, speed analysis and • Technology/Data: N/A • Process: Business participation and Data Analytics Programsaction/reaction time to events. Reduce cost ofmanaging data and effective marketing/spend. adoption • People/Organization: Data stewardship, RESULTS & OUTPUTS: Change Management Office establishment • Documented list of consumer metrics/KPIs • Defined governance and ownership model for consumer data attributes • Common definitions for all relevant 180 days 12mo 24 mo 36mo consumer attributes • Establish and document business usage rules for relevant consumer attributes CONSIDERATION: DATA ELEMENTS: • Define system of record for relevant • Requires coordination with MDM initiative. • All consumer attributes • Must be accomplished with business involvement
    16. 16. Propensity to bring a vehicle in for service to DealerUnderstanding what drives consumers to bring their vehicles in for branded service DESCRIPTION: Statistical modeling to identify the most predictive and actionable variables indicating Dashboard whether or not a consumer will bring a vehicle Element of in to a dealer for service/maintenance. Customer Profile Customer Pay for Customer Customer Repairs Data Satisfaction Analytics Marketing InitiativeBUSINESS VALUE: Credit DriversIncreased customer retention through an Card Warranty Dealerincrease in service visits to dealers. Allows Call Center Data Informationcustomer to establish relationships with used- Prod/Ops Datacar owners to keep brand top of mind. Systems Input DEPENDENCIES: • Technology/Data: Minimal data integration Data Analytics ProgramsTIMING: to increase accuracy and completeness of analytics • Process: Campaign management process RESULTS & OUTPUTS: 180 days 12mo 24 mo 36mo should incorporate the output of the model • Development of service propensity-based • People/Organization: Will require cross customer segments, and assignment of organization collaboration (e.g. service and vehicle owners to those segments CONSIDERATIONS: sales) • List of actions that can be taken by and/or • Several business stakeholders commented dealers to increase the percent of owners during interviews that they felt this was the who bring their vehicles in for service single most important gap in actionable DATA ELEMENTS: customer intelligence with respect to • Owner purchase history customer retention • Demographic/psychographic profiles • High value for customer relationship over • Service data the long term • Warranty data • Call Center data
    17. 17. Consumer SegmentationUnderstanding the unique characteristics among consumers for differentiated treatments Identify Segments DESCRIPTION: 1 Production-level algorithms to enable Identify Insights consumer clustering based on variables to 3 group customers into logical segments. Initial models will focus on behavioral Recommend Treatments characteristic clustering and value-based clustering and progress to incorporate 4 Cluster Segments consumer research attitudes. 2BUSINESS VALUE:The customer will deepen its understanding ofits consumers, their behaviours and their valuedrivers. This knowledge can then be applied to DEPENDENCIES:increase its consumer relationships across all • Technology/Data: Minimal data integrationaspects of the business including direct Data Analytics Programsmarketing, sales, service, dealer relations, to increase accuracy and completeness ofadvertising and call centre operations. analytics • Process: Targeted consumer strategies RESULTS & OUTPUTS: should incorporate the output of the model • Production-level segmentation algorithm • People/Organization: Cultural • Availability of segments to multiple lines of transformation from product to consumer business focused segments • Training and guidelines for use of 180 days 12mo 24 mo 36mo segmentation DATA ELEMENTS: • Enablement of segmented consumer KPIs CONSIDERATION: • Consumer demographic, behavioral, • Business users must determine the psychographic data appropriate actions to be taken based on • Consumer-level accounting aggregation each insight including historical data • Segmentation should be an iterative process that is recalculated both periodically and with new data sources
    18. 18. 360° View of the CustomerMaster Data Management approach to create a comprehensive source of truth for consumer information DESCRIPTION: A set of processes and tools that consistently defines and manages consumer data entities with the objective of providing processes for Operational collecting, aggregating, matching, Customer Multiform Master Data Management Data Systems consolidating, auditing, persisting and Pay for Customer Customer Satisfaction distributing such data throughout the Repairs Data WH Analytical customer organisation to ensure consistency Collaborate Operationalize Analyze Data Systems Credit CARS and control. Card Dealer Warranty Information Security Call Metadata Center Database Multi Channel Data Governance Data SystemsBUSINESS VALUE:Business agility and scalability resulting inbetter consumer Intelligence. DEPENDENCIES:Standardization of infrastructure, data • Technology/Data: Appropriate customerarchitecture and platform resulting in cost Data Analytics Programsreduction. MDM platformIncreases speed to market for new systems • Process: Business participation andthat use consumer data adoption RESULTS & OUTPUTS: • People/Organization: Data stewardship, • Provides common/synchronized definition, Change Management Office establishment value and usage of a consumer attribute across disparate systems using consumer data • Standardized data access, storage, audit, 180 days 12mo 24 mo 36mo traceability and provisioning processes DATA ELEMENTS: • Consumer data continuously synchronized • Golden attributes from all systems of record for to provide a single 360° view of the CONSIDERATION: consumer data consumer • Organization - Design an organization to • Efficient data integration platform that applies maintain the data data governance and enterprise business rules to • Ownership - Identify ownership of data vs. customer master attributes data management process • Platform to acquire, retain, enhance, provision customer master attributes to all channels and downstream systems
    19. 19. Consumer Insight Sharing with DealersStreamline delivery of this project to improve quality and consistency of consumer experience at branded dealers DESCRIPTION: Identify which insights are most relevant to the dealer experience, and share those insights with dealers on a regular basis in a simple and automated way that maximizes dealer adoption and effectivenessBUSINESS VALUE:Increased customer satisfaction and retentionvia better customer experience. Increase inRevenue per Household via selling morevehicles to existing households. Reducedselling cost via more effective for leadmanagement DEPENDENCIES:TIMING: • Technology/Data: Appropriate technical Data Analytics Programs platform 180 days 12mo 24 mo 36mo • Process: Business participation and adoption RESULTS & OUTPUTS: • People/Organization: Training & change • Standardized interface to populate CONSIDERATIONS: management for dealers and support customer insights/treatments into various • Build on the trust and value created via personnel. customer service applications and portals Integrated Service History (ISH) to recruit • Instructions, technical guidelines, and partners to participate in delivering a terms and conditions for use of data consistent branded consumer experience DATA ELEMENTS: • Suggested consumer treatments for top • Develop interface and implement pilot in opportunity and risk area • Specific KPIs and dealer relevant data to first year, with a few dealers begin rolling drive better consumer experience out to additional dealers in second year and beyond • Dealer cooperation and partnership is paramount
    20. 20. Data SimplificationRe-engineering of data preparation, migration and storage processes DESCRIPTION: Analytical Data Mart Simplification of the overall data management processes from the source systems to the consolidated data warehouse and the GM Credit Card Dealer Information ODS downstream data marts to make it more Everest Customer flexible and scalable. Pay for Call Center Repairs Modeling Integration Governance Security Infrastructure and Metadata BUSINESS VALUE: Decrease the cost to prepare data for business consumption. Reduce the DEPENDENCIES: maintenance and storage costs. • Technology/Data: N/A • Process: N/A Data Analytics Programs • People/Organization: N/A RESULTS & OUTPUTS: • Elimination of the data redundancies and low value processes • Data storage and architecture • Streamlined architecture 180 days 12mo 24 mo 36mo • Business appropriate data model DATA ELEMENTS: • Improved data quality • Exhaustive review of all data repositories • Increased traceability CONSIDERATION: and integration processes • Requires coordination with MDM initiative. • No adverse impact to business users
    21. 21. Call Centre: Next Best ActionEnable “Smart” decision making at the Call Centre Operator level, real-time, and accurately. DESCRIPTION: Customer Support decision engine used by Call Centre Operator to drive “smart” decision navigation from the Call Centre, enabled by Everest current issue, customer experience, historical Customer and preference data. Pay for Repairs Customer Customer Satisfaction “Smart” Pop-up Data WH Navigation at Call CARS Analytics Ctr. Screen Credit CARD Card Dealer Warranty Information Call Center Database Call Centre DBBUSINESS VALUE: Feedback Loop Retain and reactivate customers by properly addressing pain points with current, relative DEPENDENCIES: information through CARS. Provide “next • Technology/Data: Customer segmentation best decision” direction to call centre Data Analytics Programs operators to resolve client issue. and analytics. Access to promotional data • Process: Training and documentation for call centre RESULTS & OUTPUTS: • People/Organization: N/A • Next Best Action issue navigation tool and option recommendations via screen pops at operator terminal • Customer information and communication history on operator screen to facilitate 180 days 12mo 24 mo 36mo communication interaction DATA ELEMENTS: • Navigation path feedback loop to CARS DB • CARS, analytic algorithm and feedback to update “next best decision” algorithm CONSIDERATION: infrastructure • Customer service training is imperative • Service repair order data • Unstructured data capture and analysis for • Voice/Chat/TTL communication enabled real-time and future analysis • Operator terminal with screen pop enabled • Navigation decision path capture for refining algorithm and updating decision tree
    22. 22. Product & Service Add-on propensityIdentify most appropriate product and service extension offers for current owners DESCRIPTION: Predictive algorithm deployed against all Dashboard consumers to identify product and service Element of add on propensity. Customer Profile Customer Customer This model can be used solo or in concert Pay for Customer with other indicators such as customer Repairs Data Satisfaction Analytics Marketing Initiative segments or make/model propensity to Credit Drivers Card trigger an outbound offer. Warranty Dealer Call Information Center Data Prod/Ops Data Systems InputBUSINESS VALUE:Increase probability of sales by allowing for apre-emptive, targeted marketing and/or DEPENDENCIES:incentive response to owners based uponpredictive consumer preferences, perceptions, • Technology/Data: Minimal data integration to increase accuracy and completeness of Data Analytics Programsand sensitivities and prime drivers forpurchase. This would potentially reduce cost analyticsfor high-return, focused campaigns. • Process: Campaign management process RESULTS & OUTPUTS: should incorporate the output of the model • Production algorithm to identify service and • People/Organization: Will require cross product propensities brand collaboration • Summary of propensities tied to in market indicators for immediate targeting of those consumers with interest in corresponding 180 days 12mo 24 mo 36mo DATA ELEMENTS: offer • Consumer demographic, behavioral, • Identification of consumers with next best CONSIDERATION: psychographic data product and service fits • Recommend continuous improvement • Historical, regional, territory sales • Targeted consumer messaging guidelines training and update key performance • Consumer-level historical data indicators (KPI’s) • Ensure insight is adequately communicated • Customer communication preferences to improve sales and marketing strategy • Current service offering data
    23. 23. Optimize Contact StrategiesRelevant and timely offers and messages to maximize consumer interaction and optimize consumer experience DESCRIPTION: Construction and execution of treatment At Risk – plans and strategies to maximize consumer Contact Filtered interaction and impact of direct marketing Rules Stream Performance Contact Reporting BUSINESS VALUE: Universe At Risk Focus on the most effective cadence of Scores No Risk communications to decrease out of pocket Standard costs and improve total ROI. Stream DEPENDENCIES: • Technology/Data: Leverage data from other Data Analytics Programs initiatives 180 days 12mo 24 mo 36mo • Process: Develop a contact management strategy by treatment plan RESULTS & OUTPUTS: CONSIDERATION: • People/Organization: Will require cross • Periodic identification of consumer • Leverage data from unstructured segments for target treatment plans brand/organization prioritization of communications. • Identification of foundational metrics to campaigns and consumer contacts. • Unica campaign management can be used baseline customer interaction to provide automation • Reduction of non-targeted market spend • This should be an iterative process DATA ELEMENTS: • Ability to isolate and accommodate specific • Consumer demographic, behavioral, messaging based on situational factors. psychographic data E.g. competitor recalls, wind down • Campaign history across all channels and dealerships lines of business: • Campaign history • Card member services

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