Analytical CRM: In this article, we are covering the fifth part of Customer Relationship Management Complete Notes which is important for different competitive exams like Business and Marketing Exams, Management and Leadership Exams, Information Technology Exams, Sales and Customer Service Certification Exams, MBA Entrance Exams, Industry-Specific Exams etc.
Table of Contents
Notes on Analytical CRM
This is the fifth part of CRM Notes – Analytical Customer Relationship Management where we are going to cover Strategic CRM Planning Process, CRM Implementation, CRM Tools, Definition of Analytical Customer Relationship Management, Features of Analytical Customer Relationship Management, Purpose of Analytical Customer Relationship Management, Importance of Analytical Customer Relationship Management and Benefits of Analytical Customer Relationship Management.
Strategic CRM Planning Process
- Defining the business objectives.
- Understanding CRM Three dimensions (people, process, IT)
- Using a structured approach to manage CRM
- Identifying both corporate and customer needs
- Using customer needs to re-engineer business processes
- Selecting technology based on business needs and functionality
- Ensuring systems development is business-led
- Ensuring actionable measures of customer performance
- Actively managing culture and change, win buy-in
- Using a phased implementation strategy
CRM Implementation
- Develop the CRM Strategy
- Build CRM Project foundations
- Need specifications and partner selection
- Project implementation
- Performance evaluation
CRM Tools
- Strategic CRM
- Technology and Implementation
- Mobile Business for the Enterprise
- Sales and Marketing
- Business Intelligence
- Customer Contact Center
1. STRATEGIC CRM
- BUSINESS CASE
- CUSTOMER KNOWLEDGE
- CUSTOMER LOYALTY
- CUSTOMER RETENTION
- CUSTOMER SATISFACTION
- DIRECTION
- LEADERSHIP
- MASTER PLAN
- METRICS OR MEASUREMENT
- PEOPLE &PROCESS
- ROI
- STRATEGY & SUCCESS
- TECHNOLOGY
- TOP MANAGEMENT
- TRENDS
- VISION
2. TECHNOLOGY & IMPLEMENTATION
- ENTERPRISE ARCHITECTURE AND APPLICATION
- CRM –INDUCED CULTURE CHANGE
- MIGRATION MANAGEMENT
- KNOWLEDGE BASED UTILIZATION
- APPLICATION SERVERS
- SYSTEM INTEGRATORS
- PLANNING AND INVESTIGATING
- IMPLEMENTATION AND DEPLOYMENT
- CHANGE MANAGEMENT
- MAINTAINING AND UPGRADING
3. MOBILE BUSINESS FOR THE ENTERPRISE
- DELIVERY TECHNOLOGY
- DISPLAY TECHNOLOGY
- FIELD FORCE AUTOMATION
- INPUT TECHNOLOGY AND DEVICES
- MOBILE COMMERCE
- MOBILE ENTERPRISE
- MOBILE OPERATING SYSTEM
- WIDE AREA NETWORK
- WIRELESS APPLICATION SERVICE PROVIDER
- WIRELESS DEVICES
4. SALES AND MARKETING
- ENTERPRISE RELATIONSHIP MANAGEMENT(ERM)
- E-SALES
- LEAD QUALIFICATION
- OPERATIONAL CRM
- PARTNER RELATIONSHIP MANAGEMENT
- REPEAT BUSINESS
- SALES FORCE AUTOMATION
- ANALYTICAL CRM
- CUSTOMER PROFILEING AND SEGEMENTATION
- E-MARKETING AUTOMATION
- LEAD QUALIFICATION in sales
- PERSONALISATION
5. BUSINESS INTELLIGENCE
- ANALYTICAL PROCESS
- CUSTOMER INTELLIGENCE SYSTEM
- CUSTOMER SCORING
- DATA CLEANING
- DATA MINING
- DATA WAREHOUSE
- FILTERING AND HOUSE HOLDING
- INFORMATION DATABASE
- LEGAMART
- METAMART
- OPERATIONAL SYSTEM OR DATABASE
6. CUSTOMER CONTACT CENTER
- CALL CENTER AND HELP DESK
- CUSTOMER INTERACTIVE CENTER
- CUSTOMER RETENTION
- CUSTOMER SUPPORT
- E-SERVICE SYSTEM
- LIVE SUPPORT AND SERVICE
- ON-LINE SUPPORT AND SERVICE
What is Analytical CRM?
Analytical CRM may be defined as a decision support system that is targeted to helping senior executives, marketing, sales and customer support personnel to better understand and capitalize upon their customer needs, the company’s interaction with the customer and the customer buying cycle.
Analytical Customer Relationship Management consist of applications that enable business to analyze relevant data in order to achieve a more meaningful and profitable interaction with the customer.
It uses customer data for analysis, modeling and evaluation to create a mutual relationship between company and its customers.
It helps to better understanding of customer behavior.
The analytical CRM solution enable the effective management of a customer relationship.
Analysis of customer data can a company begin to understand behaviors, identify buying patterns and trends and discover causal relationship.
Key Features of Analytical CRM
- It integrates and inheriting all this data into a central repository knowledge base with an overall organization view.
- It combines and interacts the value of customers with strategic business management of organization and value of stakeholders.
- It determines, develops and analyze inclusive set of rules and analytical methods to scale and optimize relationship with customers by analyzing and resolving of all questions.
Need of Analytical Customer Relationship Management
- Customer Acquisition
- Customer Attrition
- Time Unit Attrition
- Revenue Dollar Model
- Customer Upgrade
Purpose of Analytical CRM
- Design and execution of targeted marketing campaigns to optimize marketing effectiveness.
- Design and execution of specific customer campaigns, including customer acquisition, cross selling, up-selling, retention.
- Analysis of customer behavior to aid product and service decision making.
- Management decisions
- Prediction of the probability of customer defection
- Analytical Customer Relationship Management generally makes heavy use of data mining.
Importance of Analytical CRM
- Make more profitable customer by providing high value services.
- Retaining profitable customer through sophisticated analysis.
- Addressing individual customer needs and efficiently improving the relationship with new and existing customer.
- Improves customer satisfaction and loyalty.
- Find and explore useful knowledge in large customer database.
- It helps in classifying customers, predicting customer behavior.
Benefits of Analytical CRM
Analytical Customer Relationship Management can make a considerable contribution toward providing the answers to numerous questions and thereby support a whole range of business decisions. The analytical capabilities allow a firm to identify new trends in the markets and then to channel the investments in these markets. They also help you gain further insights into customer needs and preferences by identifying patterns to:
- Acquire new profitable customers.
- Improve the firm’s relationships with existing customers by addressing their individual needs.
- Optimize cross-selling and up-selling opportunities.
- Improve customer loyalty and reduce customers’ propensity to churn.
With Analytical Customer Relationship Management, a firm can increase profits by as much as 100% by retaining an additional 5% of their customers. By some estimates, it costs four to seven times more to replace a customer than it does to keep one.
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FAQs on Analytical CRM
What is Analytical CRM, and how does it differ from Operational CRM?
Analytical CRM is a subset of CRM that focuses on analyzing customer data to gain insights and make data-driven decisions. It involves tools and techniques for data mining, predictive analytics, and business intelligence to understand customer behavior, preferences, and trends. Operational CRM, on the other hand, deals with automating and streamlining day-to-day customer interactions like sales, marketing, and customer service. The key difference is that Analytical CRM emphasizes data analysis for strategic decision-making, while Operational CRM focuses on improving customer-facing processes.
What are the primary benefits of implementing Analytical CRM for businesses?
Analytical CRM offers several benefits, including:
Customer Insights: It helps businesses gain a deep understanding of customer behavior, allowing for personalized marketing and product recommendations.
Improved Decision-Making: Analyzing customer data enables data-driven decision-making, leading to better resource allocation and more effective strategies.
Enhanced Customer Retention: By identifying at-risk customers and understanding their needs, businesses can take proactive measures to retain them.
Cost Reduction: Analyzing customer data can reveal inefficient processes, helping companies reduce costs and improve operational efficiency.
What types of data are typically analyzed in Analytical CRM?
Analytical CRM analyzes various types of data, including:
Customer Demographics: Information such as age, gender, location, and income helps segment customers and target marketing efforts.
Purchase History: Analyzing what customers buy, when they buy, and how much they spend provides insights into buying patterns and preferences.
Behavioral Data: Tracking website visits, click-through rates, and social media interactions helps understand how customers engage with a company online.
Customer Service Interactions: Analyzing customer support interactions can uncover common issues and areas for improvement.
What tools and technologies are commonly used in Analytical CRM?
Analytical CRM relies on various tools and technologies, including:
Data Warehouses: These store and consolidate customer data from various sources for analysis.
Data Mining Software: Tools like machine learning algorithms and statistical models help discover patterns and trends in customer data.
Business Intelligence (BI) Platforms: BI tools facilitate data visualization and reporting, making it easier to communicate insights to stakeholders.
Customer Analytics Software: Specialized software is used for customer segmentation, churn prediction, and other analytical tasks.
What are some best practices for implementing Analytical CRM successfully?
Successful implementation of Analytical CRM involves several best practices:
Data Quality: Ensure data accuracy and completeness by regularly cleaning and validating customer data.
Clear Objectives: Define clear goals and objectives for your Analytical CRM initiatives to guide the analysis process.
Cross-Functional Collaboration: Involve various departments like marketing, sales, and IT to ensure data integration and alignment with business goals.
Privacy and Compliance: Adhere to data privacy regulations and ensure customer consent for data usage.
Continuous Improvement: Analytical CRM is an ongoing process; regularly review and refine your analytical models and strategies to stay relevant and effective.