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RADAR - CVO as a Service.pptx
This document discusses customer value optimization, which involves identifying a company's most valuable customers, getting more value from them, and acquiring more customers like them. It outlines several key concepts for achieving this, including measuring customer lifetime value, balancing new and existing customer growth, boosting customer engagement through personalization and experiences, and leveraging customer data. The full customer value optimization framework includes developing a customer-centric culture, adopting a company-wide approach, using CLV-based measurement, implementing a data strategy and customer profiling, conducting value-based segmentation, and delivering customized experiences.
RADAR - CVO as a Service.pptx
- 1. Customer Value Optimization Alexandre Chaves May/2022UNLOCKING THE VALUE OF YOUR BEST CUSTOMERS RADAR
- 2. Maximizing the totalcustomer value of a business, by: Identifying and the most valuable customers, Getting more value from them, Acquiring more like them. CUSTOMER LIFETIME VALUE How to measure the future value of customers? Customer Lifetime Value (CLV) allows companies to predict the future value of their customers and thus identify the most profitable ones based on past behavior. LONG-TERM PROFITABILITY How do companies achieve sustainable growth? Balancing their goals between acquiring new, high-value customers and developing long-time relationships with their most valuable existing customers. CUSTOMERS ENGAGEMENT What is the driver of Customer Lifetime Value? Customers that have an emotional relationship with a brand have a Customer Lifetime Value 306% higher than average. HYPER-PERSONALIZATION How to improve Customer Experiences? Hyper-personalization is the most advanced way in which brands can adapt their targeting strategies to customer groups. CUSTOMER EXPERIENCE How to boost customer engagement? Companies cannot determine the behavior of their customers, but they can influence it by creating memorable experiences for their best customers. CUSTOMER FIRST-DATA How to know your customers? The richer your data, the better your will understand your audience and the better the segmentation and personalization based on this data. What is Customer Value Optimization?
- 3. COMPANY VISION The BuildingBlocks ofCustomerValue Optimization CUSTOMER CENTRIC CULTURE COMPANY-WIDE ADOPTION CLV-BASED MEASUREMENT DATA STRATEGY CUSTOMER FIRST DATA ACTIONABLE CUSTOMER PROFILING VALUE-BASED CUSTOMER SEGMENTATION CUSTOM- TAILORED EXPERIENCES PRODUCTS COMMUNICATIO NS
- 4. CUSTOMER CENTRIC CULTURE WHAT OUR CUSTOMERS NEED TO GET DONE NOW AND HOW CAN WE HELP? WHAT RELATIONSHIPS DO OUR CUSTOMERS EXPECT US TO ESTABLISH WITH THEM? WHAT VALUE DO OUR CUSTOMERS NEED TO SEE BEFORE THEY ARE WILLING TO PAY? MEASURE SUCCESS BY CUSTOMER LIFETIME VALUE PRODUCT CENTRIC CULTURE WHAT PRODUCTS/SERVICES CAN WE SELL TO OUR CUSTOMERS? WHAT RELATIONSHIPS DO WE NEED TO ESTABLISH WITH OUR CUSTOMERS? HOW CAN WE MAKE MONEY WITH OUR CUSTOMERS? MEASURE SUCCESS BY PRODUCT REVENUE/PROFITABILITY Customer centricity Is a way of doing business with consumers in a way that provides a positive customer experience before and after the sale in order to drive repeat business, customer loyalty and profits. I N S I D E - O U T O U T S I D E - I N Customer centricityx Product centricity
- 5. SWOT Analysisof CustomerCentricity Opportunities The costs of attracting a new customer are accelerating; 41% of an e-commerce revenue is created by just 8% of its customers; Only 27% of new customers return; 50% of customers will switch to a competitor after a bad experience. Strengths Long-term customer retention and loyalty; New customers tend to trust the experience of other customers; Brand reputation; Reduction of marketing costs; Competitive advantage. Weaknesses Product-centric culture; Limited and isolated customer data; It's hard to hire marketing analytics experts; Marketing to a generic customer. Threats End of third-party cookies; Customers have more information and purchase options available than ever before and expect personalized and relevant experiences; The acceleration of online shopping generated by COVID-19 has created new markets and changed existing ones, increasing competition.
- 6. With individual levelwe can … • … identify future top customers. • … identify possibly profitable, but inactive customers. • … minimize spending for unprofitable customers. • … optimize acquisition channel. • … optimize and benchmark customer development. With aggregated level we can … • … value a company by forecasting current and future customer behavior. • … benchmark the value of the customer base over time. • … Improve financial valuation of companies (due diligence) Why is Customer LifetimeValue relevant?
- 7. How to haverelevant conversations with them? Answer: Hyper-Personalization Who are my most profitable customers? Answer: Customer Lifetime Value Why do they need my products or services? Answer: Jobs to be Done Why would they buy from me again, not a competitor? Answer: Customer Experience What do you need to know aboutyour Customers?
- 8. Answering your BusinessQuestionsthroughData CLV - Customer Lifetime Value Who are the most valuable customers? Profiling / Clustering What are the ideal customers profiles? RAD Segmentation What marketing tactic should I apply to these customers? Churn Propensity Which customers are likely to leave? Recommendation What products might they be interested in? Affinity / Conjoint Analysis Which product features meet their needs or preferences? Price sensitivity How much are they willing to pay for these products? Uplift analysis Which customers are more likely to buy if they receive a specific treatment? Attribution What are the most efficient channels to engage these customers? Sentiment Analysis / Topic modeling What do customers think about my business or products? BUSINESS QUESTIONS ANALYTICS TECHNIQUE
- 9. Segmentation Personalization Targeting Automation PositioningIntegration Lifetime Value Jobs to be Done Buying Behavior Business Understanding Qualitative Research Data Collection Customer Understanding Marketing Strategy Marketing Mix Data Strategy Data Activation Data Enrichment Customer Experience Measurement Experimentation Product Place Promotion Price Data-Driven Marketing Framework
- 10. Our customers’ imperatives Our end-to-end services Delivering a completeframework that enables companies to achieve sustainable growth by maximizing the value of its customers. Our purpose Our differentiated strategy Human-based relationship model Efficient, flexible and affordable Continuous innovation in AI & CVO To be the leading provider of end-to-end modular CVO solutions. RADAR strategy – Bringing itall together Customer First-Data Tailored to business needs Knowledge of the region 360-Degree Customer Profiling Dynamic Segmentation Predictive Targeting Affinity-based Recommendati on Smart Data Activation Identify the “best customers” Create memorable experiences Acquire more like them Get more value out of them Pay-as-you- grow CUSTOMER UNDERSTANDING CONTEXTUALIZED & RELEVANT CONVERSATIONS
- 11. PREDICTIVE TARGETING CUSTOMER-FIRST DATABASE DYNAMIC SEGMENTATION 360-DEGREE CUSTOMER PROFILING SMARTDATA ACTIVATION AFFINITY-BASED PERSONALIZATION Unlocking the Power of Customer-First Data COLLECT, TRANSFORM AND ENRICH YOUR CUSTOMER DATA. CREATE A PORTRAIT OF YOUR CUSTOMERS DYNAMICALLY GROUP CUSTOMERS WITH SIMILAR PATTERNS TOGETHER DISCOVER WHICH SEGMENTS IT MAKES SENSE TO FOCUS EFFORTS AND RESOURCES BASED.ON EXPECTED FUTURE RESULTS. SEND HIGHLY CONTEXTUALIZED AND RELEVANT COMMUNICATIONS TO THE BEST CUSTOMERS AT THE RIGHT PLACE, TIME AND CHANNEL TAILOR OFFERS AND PROMOTIONS FOR YOUR BEST CUSTOMERS, RECOMMENDING PRODUCTS AND CONTENT THAT ARE RELEVANT TO THEM. INTERNAL EXTERNAL STRUCTURED UNSTRUCTURED DATA SOURCES
- 12. CUSTOMER-FIRST DATA Calculations Machine LearningBusiness Rules Natural Language Processing Identity Management Purchases, Payments, Returns, Refunds Surveys, Chats, Posts, Forms Website, Email, Apps, Messages, IoT Attributes, Financial, Services, Loyalty Business Understanding What are the Value Propositions? Qualitative Research What data is needed? Data Acquisition Plan How to get the missing data? Data Assessment What data is available? DATA ENRICHMENT DATA TRANSFORMATION DATA COLLECTION DATA STRATEGY Transaction History Customers Feedbacks Customers Engagement Customer Records INTERNAL EXTERNAL Data Cleaning Data Normalization Data Aggregation Unify customer IDs Standardize data Summarize data Organize data Regressions, Classifications, Correlations Metrics, KPIs, Scores Sentiment, Topics Tags, Attributes Creating a Customer-First Database
- 13. Customer Profile BUYING BEHAVIOR HOWdo they buy? • Frequency • Status • Spending • Basket size • Habits • Products Reviews • Metrics • Sentiment • Topics • Touchpoints • Demographics • Firmographics • Geographics • Psychographics • Lifestyle PERSONA WHO are they? JOBS TO BE DONE WHY do they buy? EXPERIENCES HOW do they feel? • Goals • Needs • Wants • Interests • Pain points 360-Degree Customer Profiling
- 14. Tactic Target GoalMetrics Retention High-value frequent customers Keep them coming CLV (Customer Lifetime Value) 5 MARKETING TACTICS TO INCREASE CUSTOMER LIFETIME VALUE R.A.D.A.R. Framework Acquisition Unknown customers with a suitable profile to the business value proposition Identify and engage ICP (Ideal Customer Profile) similarity Development New customers with growth potential Increase orders frequency and value WS (White Space) Activation High-engaged prospects Convert first transaction ES (Engagement Score) Reactivation Inactive customers with high potential value Win-back PCLV (Potential CLV)
- 15. Metric Definition Calculation LifetimeValue (CLV - $) An estimation of the amount of Revenue / Margin a customer will generate over the course of next x months, based on the past purchases. Individually -> Using the purchase history data Profile - Calculating the average CLV of the customers in the profile Potential CLV(PCLV - $) An estimation of the CLV of a customer if a new purchase takes place. Simulating a new purchase based on customer AOV. Share of Wallet (SOW - %) The percentage of a customer’s PCLV covered by the customer's CLV. CLV / PCLV * 100 Whitespace (WS - $) The difference between customer’s PCLV and CLV. PCLV - CLV Value-basedPredictive Metrics
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- 18. Our machine learning-poweredrecommendation engine, optimized by your business rules, puts your data to work and provides the opportunity for your marketers to engage customers in a personalized way, deepening existing relationships and building new ones and improving the customer experience. Message Subject Product Offer Channel Content Format SKU , collection, brand Color, size, price Promotions Time Discounts RECOMMENDATION ENGINE Basket Analysis Customer Profile Product Reviews Surveys Behavioral Data Business Rules Affinity-basedPersonalization
- 19. Smart Data Activation Whatbrands SAY What brands SELL What brands DO HYPER-PERSONALIZATION Message Content Channel Promotion Value Proposition Price Journeys Service Level Benefits What can be personalized? How to create memorable customer experiences? MARKETING PRODUCTS SERVICES Turning your customer data into action
Editor's Notes
- #2 For questions contact jeff_s_johnson@dell.com or joe_pollock@dell.com. COMMON CUSTOMER CHALLENGES: Organizations face common macro-level, external challenges, including disruptive technology trends, changing business models, and shifting work paradigms. In addition, organizations face a wide range of common internal IT challenges when evolving to meet changing demands: Siloed IT environment: Highly fragmented, heterogeneous infrastructures are extremely difficult to manage and support. Costly legacy systems: Outdated mainframe and proprietary UNIX platforms are often too expensive to operate and maintain. Underperforming workloads: New computing trends—cloud, mobility, big data—expose the limitations of outdated applications. Scalability constraints: Rigid architectures are not equipped to handle new performance demands and the rapid growth of data. Low budgets: Budgets are not growing fast enough—or not growing all—to satisfy new requirements using old methods. Limited skillsets: Lack of expertise leads to slower technology adoption, as well as potential implementation risks. In the course of this presentation, I’d like to show you how Dell addresses these challenges not only through the capabilities we bring to market, but also in how we approach the design and development of our products, services, and solutions in ways that are truly unique and better.