Marketing CRM Course Notes PDF

Chapter 1 Customer Relationship Management (CRM ), Database Marketing and Customer Value Marketing Definition and Evolution Definition: "Marketing is an organizational function and a set of processes for creating and delivering va...

Chapter 1 Customer Relationship Management (CRM ), Database Marketing and Customer Value Marketing Definition and Evolution Definition: "Marketing is an organizational function and a set of processes for creating and delivering value to customers and managing customer relationships to benefit the organization" (American Marketing Association, 2009). Evolution: From mass marketing to customerization, with shifts towards: ○ Relationship Marketing: Emphasis on customer satisfaction and retention. ( 1990-2010) ○ Customization: Moving from broad segments to personalized, one-on-one engagement. (2010) Relationship Marketing and CRM Relationship Marketing: Involves building, maintaining, and enhancing relationships with customers and stakeholders. CRM : A business strategy focused on maximizing customer value by putting the customer at the center of all firm activities. Components of CRM: - Data collection and segmentation for targeted marketing. - Creating and maintaining profitable relationships with high-value customers. - Managing unprofitable customers effectively. CRM and Customer Value CRM leverages database marketing and communication technology to maximize the lifetime value of individual customers.  Benefits: ○ Reduced costs ○ Increased profitability ○ Acquisition and retention of profitable customers ○ Reactivation of dormant customers ○ Termination of unprofitable customer relationships Conceptualization Levels of CRM Functional Level: Focuses on technology to automate tasks (e.g., salesforce automation, personalized campaigns). Strategic Level: Aligns with customer-centricity, leveraging CRM data across all functions (marketing, sales, production) for targeted offerings and customer satisfaction. CRM Analytics: Customer knowledge used to refine segmentation and target individual customers, enhancing customer equity and shareholder value. Relevance of CRM in Today’s Market Response to Market Changes - Technology: Advances in IT and data analytics improve customer behavior insights. - Consumer Dynamics: Diverse, informed consumers with high expectations. - Market Competition: Rising competition with limited product differentiation, prompting a shift to relationship-focused strategies. Data-Based Customer Value Management Benefits: Integrates customer data to enhance understanding of customer preferences. Enables product and service personalization. Focuses on customer-centric strategies to address customer heterogeneity. Focus on customer-centric instead of product-centric strategies  Establishment of a relationship (relationship marketing) Lifetime value with different life cycles : - Discovery (Acquisition) - Exploration - Development - Defection Every client is an asset Customer lifetime value (CLV) - Acquisition costs - Loyalty & Retention costs Beneficial strategies for profit maximization from current customer base. - Cross selling: new, related or even unrelated products are offered to the customer. - Up-selling :promotion of more expensive products or services over the product or service originally discussed or purchased. Customer Lifetime Value (CLV) : Total customer value as the sum of past and expected future profit. Total CLV = Acquisition Value (advertising, recruitment cost, etc…) + Σ(Profits-Costs) Application: Useful for segmentation and resource allocation in budget planning. Implications: Concentrating on maximizing CLV through personalized marketing and relationship-building. CRM Strategy Comparison: Mass Marketing vs. Relationship Marketing Mass Marketing: ○ Short-term focus, transaction-based. ○ Prioritizes customer acquisition. ○ Key Metric: Market Share. Relationship Marketing: ○ Long-term, relationship-driven. ○ Prioritizes customer retention and loyalty. ○ Key Metrics: Customer Satisfaction, Customer Share, CLV. Summary : From a strategic perspective, CRM is the process of selecting the customers a firm can most profitably serve and shaping the interactions between a company and these individual customers. Assessing Customer Value is critical to CRM. Rapid changes are taking place in the environment in which firms operate with respect to customers, market places, technology, and marketing functions. These changes have driven the marketplace to become relationship-based and customer-centric. CRM’s goal is to optimize the current and future value of the customers for the company.  Chapter 2 Implementing the CRM Strategy CRM Applications Strategic or Analytical CRM : Marketing & Marketing Research - Use of data warehousing and data mining to capture, organize, and analyze customer data. - Allows businesses to understand customers, predict behavior, calculate CLV, and allocate resources effectively. - Enables behavior tracking, market segmentation, and personalized communication and offers. Operational CRM : Sales Management - Manages day-to-day customer interactions and supports direct functions like customer service. - Contact management, account management Interaction of sales force with clients & prospect, turning prospect into customer, maintaining mutually profitable relationships. - Sales force automation through platforms, chat-rooms (Chatbots, Voice bots). - Multi/omni-channel/ Omni-Channel campaign management to ensure consistent customer engagement across platforms. Customer service - Complaint management: Incident assignment, problem management, resolution, and warranty management involve handling real-time customer issues to improve satisfaction and loyalty. - Key to a company’s ability to maintain proactive relations with customers and hence retain satisfied loyal customers. Costs of CRM Implementation IT Costs: Includes infrastructure, database development, and software for managing sales, call centers, marketing, and customer service automation, knowledge management, e-commerce functions. People Costs: Recruitment, redeployment, and training to equip employees with CRM skills. Process Costs: Costs associated with market segmentation, sales processes, campaign management. Loyalty programs costs The Customer-Centric Firm Concept: ○ A customer-centric firm places the customer at the heart of its business strategy and culture, aiming to provide superior value, enhance customer well-being, and build long-term loyalty. ○ Studies show that customer-centric companies are 60% more profitable than those that are not (Deloitte, 2017). ○ Human Interaction: Despite digital transformations, 82% of consumers still seek more human interaction (PwC , 2020). Customer-Centricity and CLV : ○ Customer-centricity involves focusing on the lifetime value of customers (CLV) and aligning resources with the most valuable customer segments (value alignment ). ○ Prioritizing high-CLV customers optimizes profit by concentrating on segments that provide the greatest long-term value. ○ Alignment and resources allocation optimization. CRM Strategy Components Effective CRM implementation relies on four essential building blocks: - Strategy/Strategic CRM : Develops customer-centric policies that align with long-term business goals. - Analytical CRM : Leverages customer data to make informed decisions and target specific customer needs. - Operational CRM : Manages interactions at touchpoints to ensure seamless customer experiences. - Information Technology, Human Resources, and Organizational Structure: Supports CRM by integrating necessary technological, personnel, and structural components. Key CRM Goals - Identify the economic value of each customer (CLV) to focus on high-value customer segments. - Offer personalized products and services to meet specific customer needs. - Systematically manage and retain customers by providing services that match their needs and profitability. - Continuously improve offerings by learning from customer feedback and data. Integrating CRM into Organizational Strategy CRM must be a core, customer-oriented strategy that supports deep understanding of customer needs and profitability. Aligns processes, technology, and interactions for competitive advantage. CRM affects both internal processes and customer-facing interactions, requiring alignment across strategy, organization, processes, and infrastructure. Summary : The key elements of CRM are touchpoints and CRM applications that span sales, marketing and service functions. CRM ROI: Calculating the return on investment (ROI) for CRM initiatives is essential to ensure that resources are effectively spent on CRM and individual customer management. Comprehensive Customer Database: A successful analytical CRM strategy depends on building a database that consolidates relevant customer information from all departments and external sources.  Chapter 3 CRM Databases Definition of a Customer Database or Data Warehouse A customer database is a collection of customer names with systematically added information, essential for CRM and interactive marketing activities. Purpose: To build strong relationships and improve customer retention by tracking, storing, and analyzing customer transactions and interactions. Types of Databases Customer Database: - Contains data on active and inactive customers. - Data Types: Basic contact information (e.g., name, address, phone number) Demographic information (e.g., age, gender, marital status) Transaction history (e.g., purchase frequency, amount, recency, and responses to promotions) Behavioral data (e.g., loyalty, satisfaction, customer lifetime value) - Data Sources: Contact forms, surveys, loyalty programs, and cookies. - Data from customers: - H ow were they acquired ? - H ow long have the customers been (in)active ? - What is their purchasing pattern ? H ow much did they spend ? RFM - Why are they inactive ? What signs of defection were shown before becoming inactive ? (decrease satisfaction, purchase frequency/amount )  Prospect Database: - Contains data on non-customers who match the profile of existing customers. - Purpose: H elps identify potential customers with similar characteristics to current customers. Example Sources: Acxiom (covers 85% of the French population), Kompass for B2B data, social network campaigns. Enhancement Database: - Adds additional data to existing customer and prospect information to improve insights and loyalty. - Data Types: Demographics, psychographics, updated contact information, and purchase trends. Example Sources: Acxiom for SMS and email, La Poste for demographic updates. Database Management Passive Marketing Database: - Functions as a basic mailing list that passively stores information about acquired customers. - Used primarily for targeting existing customers in future marketing efforts. - Active learning marketing database. Structure: The database supports a continuous feedback loop, where data from customer interactions is updated and analyzed to refine future marketing strategies. Uses of Marketing Databases Customer Relationship Benefits: ○ Enables profitable segmentation to allocate marketing resources effectively. ○ Identifies high-value customers (using CLV) and improves promotional targeting. ○ H elps in creating long-term relationships through personalized messages and offers. ○ Supports post-purchase follow-ups, cross-selling, and personalized service. ○ Improves customer lifecycle management, ensuring satisfaction and retention. Operational Benefits: ○ Enhances product and market research, leading to improved marketing effectiveness. ○ Improves brand equity, distribution channels, and pricing by measuring efficiency across marketing programs. Performing Database Analytics Data Mining: - Utilizes statistical and mathematical techniques to extract insights from customer data. - H elps identify valuable customers through CLV, predict customer behavior, and tailor offerings to individual needs and predict future behavior. - Essential for customer segmentation and targeting strategies, enabling companies to maximize CRM effectiveness. Summary : Effective Database analysis is important for successful CRM. Data from active and inactive customers are important to ensure efficient marketing function. Marketing databases allow marketers to analyze customers and classify/segment them into different groups to implement different marketing programs effectively. Databases also enable marketers to determine critical factors influencing customer satisfaction and take measures to retain existing customers at lowest cost. Marketing CRM Chapter 4 Customer Based Marketing Metrics for Segmentation and Resource Allocation Market Segmentation : Division of large, heterogeneous markets into smaller segments, groups, categories, that can be reached more efficiently and effectively with products and services that match their unique needs. Target marketing : select the most profitable customer to focus on. Geographic segmentation : division of the market into different geographical units such as nations, regions, states, cities. Demographic segmentation : division of the market into groups based on variables (age, gender, family size, lifecycle, income, occupation, education, religion, nationality). Behavioral Segmentation : division of the market into groups based on :. purchase frequency. purchase amount. purchase recency. loyalty status/CLV Traditional and Customer Based Marketing Metrics : Marketing Metrics : measurable values used by marketers to track the effectiveness of marketing efforts and campaigns. These metrics help businesses understand how well their marketing strategies are performing, enabling them to make data-driven decisions to improve results. Traditional marketing metrics : Market share, Sales growth Behavioral customer based metrics for segmentation :  - Customer acquisition - Customer activity (retention, lifetime duration) - Customer value (Share of Wallet, RFM value, Customer lifetime Value, Customer Equity) Measurements : - Customer Acquisition Acquisition : first purchase in the first predefined period Acquisition rate (%) = N of prospects acquired / N of prospects targeted*100 Information source : - Numerator : from internal database records - Denominator : from prospect database and/or market research data Acquisition cost ($) = Acquisition spending ($)/ N of prospects acquired Information source : - Numerator : from internal database records - Denominator : from internal records - Lifetime Duration and Type of Relationships Lifetime duration : time from start until the end of the relationship with a customer. Type of Customer relationships : - Contractual (“lost for good”) : the first and last purchases are known and whether a customer is active at a given point is known (ex : mobile phone, internet contract ) - Non-contractual (“always a share”) : the first and last purchases are unknown and whether a customer is active at a given point in time is unknown (ex : grocery purchase).  - Customer Activity Average Interpurchase Time of a customer = measured in time periods (days, weeks, months). Retention rate (%) = N customers in cohort buying in (t )/ N customers in cohort buying in (t-1)*100 Average Defection/Churn rate (%) = 1 - Retention rate Information source : Internal database records - Customer Value Where S = sales to the focal customer , j = firm J ∑ = summation value of sales S made by all the J firms that sell a category of products to a buyer. j=1 Individual Share-of -Wallet of firm to customer (%) = Sj /∑ Sj Information source : - Numerator : internal records - Denominator : primary market research (surveys, panel data) collected for a representative sample and then extrapolated to the entire buyer base - Customer value - RFM Recency coding : how long has it been since the customer last purchased with the company ? - customers sorted in an ascending order based on the criterion of ‘most recent purchase date’. - most recent purchasers are listed on the top and the oldest are listed at the bottom. - sorted data is divided into 3 equal groups (33% in each group). - top group is assigned a recency code of 1, the next group a code of 2, until the bottom group is assigned a code of 3. Frequency coding: how often a customer buys from the company in a certain defined period ? - customers sorted in a descending order based on the criterion of ‘most important purchase frequency’. - most frequent purchasers are listed on the top and the less frequent are listed at the bottom. - sorted data is divided into 3 equal groups (33% in each group). - top group is assigned a frequency code of 1 and the next group a code of 2, until the bottom group is assigned a code of 3. Monetary coding: the amount that a customer spends on an average transaction. - Customers sorted in a descending order based on the criteria of ‘most important purchase amount’. - most important amount purchasers are listed on the top and the least are listed at the bottom. - sorted data is divided into three equal groups (33% in each group). - top group is assigned a Monetary code of 1 and the next group a code of 2, until the bottom most group is assigned a code of 3. Final Analysis - Customers now have aRecency code (1-3), Frequency code(1-3), and Monetary code (1-3), and are sorted in a descending order based on those criterions. - The best purchasers are those who have the code 111, the worst are those with the code 333. - Segmentation and resource allocation according to those codes.  - Customer Lifetime Value (CLV) Customer’s cumulated past & future profits in the firm = ( ∑ Past Revenues + ∑ Future Revenues) - (∑ Acquisition Costs + ∑ Past Retention Costs + ∑ Future Retention Costs). Past and actual Revenues. Past and Actual Profit. Lifetime Profit. Past and Actual Costs. Lifetime of a customer. Lifetime Profit CLV CE (loyalty products, com). Survival Retention Rate (%). Acquisition Cost Loyal clients through long time relationships : (Acquisition costs), Basic Profit, Profit through cost reduction of sales administration, Profit through increased purchase intensity, Profit through WOM , Profit through reduced price sensibility. The reasons why Loyal customers Generate More Profits : - Increase their spending over time - Cost less to serve than new customers - Generate word-of -mouth advertising or referrals - Are less price sensitive than new customers - Pay a premium price when compared to that paid by short-term customers Customer Equity measurement : Sum of all CLV of the firm: Indicator of how much the firm is worth at a particular point in time as a result of the firm’s customer management efforts. CLV/CE Targets Optimizing customer portfolio : the acquisition, retention, and cross selling processes balance the acquisition of new customers with the retention of existing ones. Segmentation & allocation of marketing spending for long-term profit. Summary : Segmentation involves dividing heterogeneous markets into smaller segments that can be reached more efficiently with products/services that match their unique needs. It results in resource allocation optimisation. Acquisition & retention measurement metrics measure the customer level success of marketing efforts to acquire new and retain old customers. Customer activity metrics track customer activities after the acquisition stage. Firms use different measures of customer value (SOW, RFM , CLV) to prioritize their customers and to differentially invest in them and for optimal allocation of resources.  Chapter 5 Customer Portfolio Management Definition : Customer portfolio management - Allocate resources based on customer value, and a deep understanding of their needs. - The results are deeper, richer customer interactions driven by more personalized and targeted value propositions that better meet customer expectations. Product portfolio management : - strategic process of managing a company's collection of products to maximize profitability, market share, and alignment with business goals. - involves evaluating and optimizing the range of products a company offers across different markets and segments to ensure that resources are allocated efficiently, product lifecycles are managed effectively, and product performance is aligned with the company's overall strategy. Product Portfolio analysis The collection of businesses and products that make up the company. Portfolio analysis: Example Boston Consulting Group (BCG) Grid - Step 1: Analyse the current product portfolio/SBUs in terms of actual market share value and future market growth. - Step 2: Shape the future product portfolio (develop stars and question marks, harvest cash cows, divest dogs). Customer Portfolio analysis The customer portfolio: collection and analyses of clients that make up the company’s portfolio. Questions of Portfolio analysis: - H ow to maximize profits across various customer segments ? - H ow to optimise customer acquisition and retention ?  Step 1: Analyse/Segment the current customer portfolio. Step 2: Shape the future customer portfolio (acquisition valuable customers, development of good clients and clients with potential, abandon bad clients). Customer analyses based on contribution and potential CLV : The matrix classifies a company's products or business units into four categories based on two key factors: market growth rate and relative market share. This framework allows businesses to make informed decisions about where to invest, which products to develop, or which ones to phase out. The BCG Matrix consists of four quadrants: 1. Stars: - High market share in a high-growth market. - Products in this quadrant are often leaders in fast-growing markets. They require significant investment to sustain their growth but can generate substantial returns. If managed well, stars can become cash cows as the market matures.  2. Cash Cows: - High market share in a low-growth market. - These products are well-established and generate steady cash flow with minimal investment. The company should use profits from cash cows to support stars and question marks. They are the backbone of a business’s profitability. 3. Question Marks: - Low market share in a high-growth market. - These products have potential but require investment to increase market share. H owever, their future is uncertain. If they can grow into stars, they are worth the investment, but if not, they might need to be divested. 4. Dogs: - Low market share in a low-growth market. - These products have limited growth potential and generate little profit. Companies often decide to divest or discontinue dogs to free up resources for more promising opportunities. Strategic Implications: Stars need investment to maintain their leading position. Cash cows should be maintained to generate consistent revenue. Question marks require careful evaluation to determine if they’re worth investing in or phasing out. Dogs should generally be divested unless they serve a strategic purpose. Linking Customer Acquisition, Relationship Duration, and Customer Profitability Customer Portfolio Analysis and Strategies Allocate resources between existing and new customer - Retention Strategy : - Acquisition Strategy Keep existing customers Attract new customers - Market decisions: - Market decisions Segment customers by CLV Target customers based on the model of Retain best customers existing best customers, scoring - Product/Service decisions: - Products decisions : Develop relationship marketing Highlight price/ product offer Retain clients with superior quality service Develop attractive branding Develop tailor-made products/service Give incentives/promotions to add initial cross-sell and up-sell value to the new customer Importance of balancing between Acquisition and Retention Offensive marketing - - - - - - for Customer Acquisition Customer base Defensive marketing - - - - - - for Customer Retention Customer portfolio analyses based on customer lifecycles Better marketing resources allocation Customer portfolio analyses based on acquisition and retention costs Summary : - Marketing databases allow marketers to analyze customers and classify them into different groups to implement different marketing programs effectively. - Assessing Customer Value is critical for Customer Portfolio Management. - Customer Portfolio Management’s goal is to optimize the current and future value of the customers for the company. - Firms use different surrogate measures of customer value to prioritize their customers and to differentially invest in them.  Chapter 6 Satisfaction, Loyalty, and Loyalty Programs The Satisfaction Loyalty Profit Chain Satisfaction: positive disconfirmation between customer expectations and actual product or service performance. Influenced by product quality, service quality, and employee performance, satisfaction occurs when expectations are met or exceeded, while unmet expectations lead to dissatisfaction. Loyalty: Satisfaction often precedes loyalty, which can be behavioral (measured by actions like repeated purchases) and attitudinal (emotional attachment and trust ). Both types are essential for fostering long-term customer relationships. Profitability: Loyal customers typically bring higher customer lifetime value (CLV) and increased profitability. Firms with strong customer loyalty often enjoy better financial performance due to the repeat business and brand advocacy from loyal customers. Antecedents of Satisfaction Customer expectations form through past experiences, word-of -mouth, advertising, and personal needs. When a brand meets or surpasses these expectations, satisfaction ensues, while unmet expectations result in dissatisfaction. Example: A hotel guest expecting a standard room may experience heightened satisfaction when given an upgraded room. Conversely, a lower-quality room than expected can cause dissatisfaction. Measuring Customer Satisfaction Customer Satisfaction Barometers: satisfaction surveys taken at various customer touch points, such as post-purchase or post-service, gauge satisfaction levels. Mystery Shoppers: evaluate service quality, mystery shoppers provide valuable insights, especially in retail and hospitality industries. Lost Customer Surveys: analyzing customer churn to understand reasons for defection helps businesses identify dissatisfaction points and improve customer retention strategies. Loyalty Programs : Marketing process and system of marketing actions (stimuli, rewards, communication) creating a sense of belonging, encouraging ongoing engagement with the brand, with the target to : give rewards to customers based on their repeat purchasing encourage repeat purchase behavior personnalise the relation optimize marketing ressources allocation. Consumers who enter a loyalty program are expected to transact more with the focal company, giving up the free choice they have otherwise (induced loyalty). In exchange for concentrating their purchases with the focal firm, they accumulate assets (for example, ‘points or miles’). Points are exchanged for products and services. CRM tool used by marketers to identify, award, and retain profitable customers. Types of Loyalty Behavioral Loyalty: observed and measurable actions a customer has demonstrated towards a particular product or service like purchase frequency and share of wallet. Attitudinal Loyalty: reflects a deeper emotional connection marked by trust and brand attachment. Real loyalty = Attitudinal Loyalty + Behavioral Loyalty Relationship Marketing Paradigm The Satisfaction-Loyalty-Profit Chain, also known as the Relationship Marketing Paradigm, emphasizes the importance of creating personalized, relationship-driven experiences to improve satisfaction, loyalty, and long-term profitability. Loyalty Programs and Customer Behavior Loyalty programs incentivize repeat purchases by rewarding customers with benefits like discounts, vouchers, or points, promoting behavioral loyalty. Examples: Programs in retail, airlines, and hotels allow customers to accumulate rewards through continued brand engagement, thus encouraging repeat patronage in exchange for benefits. Costs and Benefits for Customers Customers weigh the benefits of a loyalty program (e.g., exclusive discounts, services) against the cost of reduced choice. The higher the perceived value of these benefits, the more customers are inclined to limit their options and commit to the brand. Types of Loyalty Benefits Economic Benefits: discounts, vouchers, or points tied to purchase amounts. Relationship Benefits: privileged access or personalized services enhancing emotional bonds. Exploratory and H edonic Benefits: fun experiences or engaging brand interactions. Functional Benefits: convenience features like priority checkouts. Informational Benefits: access to exclusive information or product insights. Efficiency Profits (performance): loyalty programs increase customer basket size, purchase frequency, and share of wallet, often reducing price sensitivity. This behavior elevates retention, CLV and profitability. Effectiveness Profits (quality): better learning about customers preferences, allowing sustainable value creation through better personalization of products and services, generating competitive advantage, enhancing customer satisfaction and loyalty. Value Alignment : involves focusing resources on high-value customers and serving them in the best manner (segmentation), while reducing investment in lower-value segments. This strategy is essential in industries with diverse customer profitability, such as airlines or financial services. Customer Portfolio Management Managing a customer portfolio means segmenting customers based on their lifetime value and profitability. Prioritizing high-value customers with premium services and rewards, while optimizing investment in lower-value customers, ensures efficient resource allocation. Summary : Satisfaction serves as the foundation for loyalty, which drives profitability. Loyalty programs aim to foster both behavioral and attitudinal loyalty by creating rewarding experiences, thereby enhancing customer retention and contributing to long-term business success. Satisfaction-profit-chain (SPC ) needs to be implemented at a disaggregate level or individual level rather than aggregate, firm-level. Loyalty can be obtained by product, service and relationship satisfaction and LP’s. LP are CRM tools to personalize the relationship and give rewards to encourage repeat purchase behavior. The targets of LP’s are building true (attitudinal & behavioral ) loyalty or Efficiency Profits, Effectiveness Profits, and Value Alignment.  Chapter 7 Personalization Definition Personalization : process by which firms proactively tailor services, products, communication, and web interfaces based on personal customer data (preferences, behavior, transactional history, and geographical data). The goal is to make the customer relationship more interactive and convenient. Personalization is done by the system or the company (e.g. Amazon, Netflix), whereas customization is realized by the customer himself proactively (e.g. Dell ). Targets of Personalization: - Value systems from the individual fit that a service provides, and the convenience of having it delivered in a proactive fashion (Reduce research efforts) - Feeling unique and important - Cross-selling possibilities This leads to : More satisfaction, differentiation, true loyalty & customer engagement, less customers’ switching behaviors. Types of Personalization: - Behavioral : uses past transactional data (e.g., what products were bought Amazon). - Social -based : personalized recommendations through data from social media activity (likes, comments) to understand preferences. - Location-based :uses location data to suggest nearby products or services (e.g., restaurants or stores). - IoT : smart, connected objects (sleep, heart rhythm, sport ) Examples: Netflix: Uses viewing data (history, time of day, and device) to recommend content similar to what the user has watched. Amazon: Suggests complementary products based on prior purchases. Definition Customization : is done by the customer, where they personalize the products or services they purchase by choosing specific features or components that suit their needs. The company provides a framework or options, and the customer tailors the product. Example: ○ Dell or Apple: Customers can choose specific components like RAM size, screen size, or keyboard language when configuring a laptop. Advantages of Personalization: Efficiency: reduces the customer’s search effort by proactively offering products that match their needs, minimizing cognitive energy and time spent. Increased Customer Loyalty: satisfying personalized interactions lead to higher levels of trust, attachment, and loyalty toward the brand. Customer Lifetime Value (CLV): higher repurchase rates, cross-selling opportunities, and increased customer lifetime value through long-term engagement. Combination of Data Types: Firms can combine behavioral data (purchases, browsing history), social media data (posts, likes), and location data (current or previous geolocation) to optimize customer interactions and provide hyper-personalized recommendations. AI and Machine Learning play a crucial role in analyzing this data to predict and deliver relevant offers and services. Impact on Customer Engagement: Personalization leads to better customer satisfaction and engagement, encouraging behaviors such as positive word-of -mouth and loyalty. The integration of personalization strategies ultimately enhances the customer’s lifetime value by increasing the likelihood of repeat purchases, cross-purchases, and potentially upselling higher-value products. Hyper-personalized marketing in a smart home context powered by the Internet of Things (IoT ) and Artificial Intelligence (AI) IoT and AI Integration: The internet of things (IoT ) enhances customer experience, increases the amount of data gained through connected devices, and widens the scope of analytics. This provides a range of exciting marketing possibilities such as selling existing products and services more effectively, delivering truly personalized customer experiences, and potentially creating new products and services. AI is layered on top of this network to analyze the data, offering hyper-personalized services by understanding users' behaviors, preferences, and even health conditions. Big data analyses: IoT creates a tremendous amount of big data (social, behavioral, patterns, interests, activities of billions of people and devices every day. AI is good at crunching numbers and analyzing data. Satisfaction and Sentiment analysis: Detect emotions in texts to understand feelings or understand perception (e.g by monitoring public online conversation in social media, reviews, email, chatbot conversations). Personalized User Experience: big data from IoT and other sources is analyzed by AI to create personalization and consumer services having high value. Advertisement Optimization in buying, coordination of online ad-space and targeting of online-advertising. Optimize social media outreach.  Customized email marketing campaigns: by analyzing user behavior and preferences and recommended personalized products/services. AI-powered Chatbots: humanely talk to users and don’t get short-tempered when a user asks any question. Virtual Personal Agent (VPA ): assist users over time. Generally “lives” in smart homes or consumer devices (Alexa, Siri, Google H ome). The automated response is personalized. AI to optimize Ad investment Consumer Data Collection: Devices in the smart home collect a vast array of consumer data, such as food consumption patterns, brand preferences, and dietary restrictions (e.g., allergies). This data is combined with social media interactions, search histories, and even health data from smart wearables to provide a holistic view of consumer behavior. Hyper-Personalized Offerings: Based on real-time data analysis, the smart system can make personalized product recommendations, predict future needs, and even automatically reorder items (e.g., milk, wine, gluten-free foods) through direct connections with online retailers. For instance, the smart fridge can track inventory using barcodes or RFID and notify the user when products are low or about to expire. H ealth and Wellness Integration: AI-based systems take into account health conditions (e.g., allergies, weight loss goals) and suggest foods and recipes that align with the user’s wellness objectives. Smart devices can optimize diet plans by recommending nutritious meals and automatically adjusting the home environment (e.g., temperature, lighting) to support well-being. Recommender Systems and AI-Powered Suggestions: AI-powered recommender systems suggest complementary items (e.g., pairing wine with pasta or chips with beer) based on what’s in the fridge and the user’s habits. The system also plans weekly meals, creates shopping lists, and even places orders automatically, ensuring that the user never runs out of essential items. Smart Appliances and Volumetric Cooking: Advanced smart ovens and cookers use volumetric cooking, allowing users to put all ingredients in at once and have them cooked at different speeds so that everything is ready at the same time. These appliances not only cook but can also automatically order ingredients from retailers, minimizing waste and ensuring just-in-time delivery. Customer Engagement and Loyalty: By offering a seamless, hyper-personalized experience, companies foster deep relationships with customers, increasing both attitudinal and behavioral loyalty. High levels of personalization and data-driven recommendations lead to increased trust in brands, higher customer lifetime value, and better customer equity in the long term. Privacy and Trust Concerns: Brands need to ensure that they protect user data and build trust by not abusing the information collected. Future of Personalized Marketing: The course envisions a future where consumers have minimal decision-making burden, as AI-driven systems handle routine tasks like grocery shopping, meal planning, and even health management, resulting in a highly convenient and personalized lifestyle. The ultimate goal is the right product, delivered to the right person, at the right time—maximizing consumer satisfaction and loyalty while minimizing waste and unnecessary effort.  Chapter 8 Conclusion 1. Expanded Marketing Process Model: ○ The course presents an expanded model of the marketing process, focusing on value creation through Customer Relationship Experience (CRX ) marketing. ○ CRM extends traditional marketing by emphasizing relationship building with customers. 2. Value Creation: ○ The primary goal of marketing is to create value for customers. ○ CRM aims to establish personalized and close relationships, enhancing the overall value creation process. 3. Strategic vs. Functional CRM : ○ Strategic CRM : Involves understanding the market and designing customer-driven strategies. It includes elements such as strategic customer relationship management and analytical CRM. ○ Functional CRM : Focuses on implementing strategies through operational processes and automating customer relationships. 4. Data Management: ○ Emphasizes the importance of building large databases (big data) to enhance customer knowledge. ○ Data types include demographic, behavioral, transactional, geographical, and social media data. 5. Analytics and Metrics: ○ Utilizing customer analytics to derive insights and metrics such as customer retention rates, lifetime value, and wallet share. ○ Key performance indicators (KPIs) for measuring CRM success include acquisition, retention, and defection metrics. 6. Segmentation and Personalization: ○ Importance of segmenting customers based on their needs and preferences. ○ Micro-personalization is highlighted, aiming for one-to-one relationships where each customer is treated as a unique segment. 7. Marketing Mix Personalization: ○ Personalizing the four P’s of marketing (Product, Price, Promotion, Place) to align with customer segments. ○ Pricing strategies may vary based on customer sensitivity and segmentation. 8. Omnichannel Distribution: ○ Emphasizes the need for products to be available across various channels, both online and offline, to cater to diverse customer preferences. 9. Relationship Marketing: ○ Encourages establishing loyalty programs and offering incentives to enhance customer satisfaction and build lasting relationships. ○ Loyalty is crucial for driving customer retention and increasing lifetime value. 10. Emotional Attachment and Brand Loyalty: ○ Aims to create emotional connections with customers, leading to brand attachment that goes beyond simple inertia. ○ Encourages the development of strategies to enhance attitudinal loyalty and reduce price sensitivity.  11. Customer Lifetime Value (CLV): ○ Highlights the importance of measuring CLV and understanding its impact on overall customer equity and business profitability. 12. Measurement and Feedback: ○ Stresses the ability to measure the impact of CRM initiatives on customer behavior and financial performance. ○ Feedback mechanisms and customer satisfaction metrics are critical for continuous improvement. Final exam : 17 december mcq on moodle 20% of final grade Case study : 28 november 40% final grade Group work : 40% final grade