CRM Concepts and AI Integration Quiz

Management Information Systems (MIS) Lecture Notes

• Course code: ADM 2372
• Instructor: Mayur Joshi, PhD
• Contact email: [email protected]
• Copyright information provided
• All rights reserved, no reproduction, storage, or transmission without instructor permission

Week 8: Customer Relationship Management (CRM)

• Chapter 11
• Agenda:
  • Why CRM?
  • Defining CRM
  • Operational CRM
  • Analytical CRM
  • Examples
  • Role of AI in CRM

ERP: New Generation

• Current ERP systems (ERP II) offer web-enabled access for customers, suppliers, and partners via connections (e.g., VPN).

ERP: Core and Extended Modules

• ERP systems have core modules (accounting & finance, manufacturing & production, human resources, supply chain management) and integrated extended modules (business intelligence, e-business, customer relationship management) connected to the ERP platform and database.

ERP: Modules and Other Systems

• Shows integration of ERP (accounting, finance, human resources, marketing, sales, operations, and production management) with CRM, SCM, and organizational levels of business (executive, management, transaction). —Also shows business to consumer (B2C) and business to business (B2B) e-commerce transactions.

The Customer is King!

• Historical context: Neighborhood stores prioritized knowing customers' needs and fostering loyalty.
• Modern approach: CRM aims to replicate this through data collection and analysis.
• Examples from Amazon: Vision is customer-focused.

How? Why?

• Customer profiles & personalization
• Low customer acquisition vs. customer retention costs; acquisition is 5-10 times more expensive than retention.
• Dissatisfied customers disproportionately impact others.

Defining CRM

• CRM is a customer-centric organizational strategy, not just software.
• Enables personalized marketing and intimate business relationships with customers. -Supports customer acquisition, retention, and relationship growth.

Collaborative CRM

• Integrates marketing, sales, and service communications across the organization.

Defining CRM (cont.)

• RFM (Recency, Frequency, and Monetary value) used to identify valuable customers. This is a way to measure customer value from customer data.

CRM Process

• Organization solicits potential customers.
• Some customers become repeat customers.
• Organizations segment repeat customers into low-value and high-value groups.
• Customers sometimes churn over time.
• Goal is to maximize high-value repeat customers and minimize churn.

CRM: Strategy versus System

• CRM strategy is the customer-centric orientation of the organization.
• CRM systems support the strategy through information systems.

Customer Touch Points

• Different ways organizations interact with customers.
• Includes traditional methods (e.g., phone calls, direct mail).
• Includes digital methods (e.g., email, website interactions, mobile apps).

Data Consolidation

• All customer data needs to be accessible across all departments and employees interacting with customers.
• CRM for a 360-degree view of every customer interaction.

CRM Evolution

• Stages of CRM: Reporting, Analysis, and Prediction.

Operational CRM System

• Supports daily front-office operations.
• Deals directly with customers.
• Automates tasks like call centers, marketing campaigns, and sales processes

Operational CRM Systems (Benefits)

• Efficient, personalized marketing/sales/service
• Comprehensive 360-degree customer view.
• Access to customer history data across all touch points.

Operational CRM (Types)

• Customer-facing: CRM used by employees directly interacting with customers.
• Customer-touching: Systems customers utilize for interactions (email, FAQ, loyalty programs, etc.)

Customer-Facing Applications

• Customer service & support.
• Sales Force Automation (SFA).
• Marketing
• Campaign Management.

Customer Service & Support

• Automation of requests, complaints, returns, and information.
• Customer Interaction Centers (CIC) with various channels (website, phone, fax).
• Call centers, outbound/inbound telesales, and other forms of customer support.

Sales Force Automation (SFA)

• Tracks sales transactions, contacts, and follow up.
• Provides sales leads and forecasting tools.

Marketing

• Enables identifying best customers & running marketing campaigns.
• Uses cross-selling/upselling strategies.
• Enables grouping/bundling products for selling.

Customer-Touching Applications

• e-CRM: Customer self-help apps (search, comparison).
• Technical information and support (product manuals, replacement parts, FAQs).
• Customized products & services with options available.

Customer-Touching Applications (cont.)

• Personalized web pages for personalized customer experience.
• FAQs and chatbots for repetitive queries.
• Email and automated response feature.
• Loyalty programs.

Operational CRM: Example in Marketing

• Email marketing system from Oracle Siebel CRM: guides marketing campaigns (design, launch, tracking, evaluation).
• System shows email campaign creation, email template design, template contents, and customization.
• System for creating and launching email campaigns.

Operational CRM: Example in Sales

• Sales Force Automation (SFA) from SugarCRM: tracks sales steps.
• Displays functionalities, including customer management, opportunities, pipeline, and sales forecasting views.

Operational CRM: Example in Sales (cont.)

• Contact management system to identify prospective customers for future sales.
• Shows examples of storing/accessing contact data, managing, and generating new customer opportunities.

Operational CRM: Example in Sales (cont.)

• Opportunity Management system from SugarCRM to find/target future sales opportunities; shows relevant dashboards, opportunity lists, and details.

Operational CRM: Example in Customer Service

• Call center system: Supports customer inquiries & issues resolutions by CSRs.
• System screens displays elements like customer service requests, resolution steps, and customer information for CSRs.

Analytical CRM

• BI tools providing business intelligence for analyzing customer data.
• Finding new customers similar to existing best customers (e.g., based on demographics, location, purchasing behavior).
• Reactivation of inactive customers with customized communications, offers, and discounts..

Analytical CRM: Example in Marketing

• Marketing analysis from SugarCRM: Measures ROI, tracking campaign results, and understanding campaign effectiveness.
• Shows examples of campaign analytics and ROI dashboards.
• Provides visuals of campaign and customer data to determine its effect on business.

Analytical CRM: Example in Sales

• Sales analytics from Siebel CRM (now part of Oracle).
• Customizable dashboards and key performance indicators (KPIs) to boost sales efficiency.
• Provides sales pipeline insights from various views (pipeline overview, lead quality, deal size, top opportunities)

Operational vs Analytical CRM

• Operational CRM handles interactions with customers in marketing, sales, and service. Analytical CRM analyzes customer data (e.g., using data warehousing or data marts) with BI tools and insights to plan ahead.

Examples of new CRM products

• Microsoft Dynamics CRM for sales, marketing, and service.

CRM & Privacy

• Customer concerns about data collection within CRM systems.
• Demonstrating that some customers value these systems.

CRM Metrics

• Measures of effectiveness for CRM systems in various areas (e.g. sales cycle, revenue per customer, average order size, customer acquisition and retention costs, campaign response, marketing & service efficiency).

What you can do with CRM

• Salesforce website for accessing and starting a free CRM trial.

Role of AI in CRM

• Customer insights and predictions: AI analyzes customer data to improve customer relationships through personalized experiences based on insights.
• Automated Customer Support: AI-powered chatbots enable 24/7 customer support via instant responses, freeing up human agents to handle complex cases and issues.
• Personalized Marketing and Sales: AI segments audiences, tailors marketing efforts, and increases customer satisfaction rates with more relevant product/service offerings.
• Lead Scoring and Forecasting: AI anticipates conversion likelihoods for improving sales team efficiency in targeting the most promising leads.
• Automating Routine Tasks: AI automates repetitive tasks (data entry, updating customer information, scheduling follow-ups), boosting CRM efficiency and minimizing human error.
• Sentiment Analysis: Analyzing customer feedback for proactively addressing concerns and enhancing customer experience.

Test your knowledge on the fundamentals of Customer Relationship Management (CRM) and how AI is transforming customer interactions. This quiz covers customer touch points, the importance of CRM phases, and the impact of AI on marketing and customer support. Enhance your understanding of modern CRM strategies.