Unit 7.4
Analytical & Collaborative CRM Systems
IT 233: Business Information Systems
Learning Objectives
By the end of this chapter, you will be able to:
- ✅ Define Analytical CRM and its role in analyzing customer data.
- ✅ Identify key functions like customer segmentation and churn analysis.
- ✅ Define Collaborative CRM and its purpose in unifying interactions.
- ✅ Explain how Collaborative CRM manages customer experience across channels.
Beyond Day-to-Day Operations
While Operational CRM handles daily interactions, we need more to build a complete strategy.
Operational CRM
Focuses on the front-office. Automates sales, marketing, and customer service.
It collects the data.
Analytical & Collaborative CRM
Focuses on the back-office and communication. Analyzes data and coordinates teams.
They make sense of the data and help us act on it.
Interactive: Classify the CRM Activity (1/2)
For each scenario, click the correct CRM type. Green = correct, Red = wrong.
Interactive: Classify the CRM Activity (2/2)
For each scenario, click the correct CRM type. Green = correct, Red = wrong.
Analytical CRM: The "Brain" 🧠
Analytical CRM is the back-office component that analyzes vast amounts of customer data to gain insights into customer behavior and guide business decisions.
🎯 Primary Goal: To understand customers on a deeper, data-driven level.
🎬 Watch: Operational vs Analytical CRM
Functions of Analytical CRM 📊
Customer Segmentation
- Groups customers by shared traits (demographics, purchase history).
- Allows for highly targeted marketing and personalized service.
Profitability Analysis
- Identifies your most and least profitable customers.
- Helps focus resources on high-value relationships.
Interactive: Segment These Customers
Click a customer profile to select it, then click a segment bucket to assign it.
🧮 Worked Example: RFM Segmentation
Score each customer 1–5 on Recency (how recently they bought), Frequency (how often) and Monetary (how much). Illustrative scores for a stationery shop:
| Customer | R | F | M | Segment → action |
|---|---|---|---|---|
| A | 5 | 5 | 5 | Champion → early access to new stock |
| B | 1 | 4 | 4 | Used to be loyal, now silent → "We miss you" offer |
| C | 5 | 1 | 1 | New customer → welcome discount on 2nd purchase |
| D | 1 | 1 | 1 | Lost, low value → no spending on them |
Analytical CRM: Predictive Power ⚡
Predictive Analytics
- Churn Analysis: Predicts which customers are at risk of leaving.
- Next Best Offer: Predicts the product a customer is most likely to buy next.
Customer Lifetime Value (CLV)
- Estimates the total revenue a business can expect from a single customer.
- A key metric for long-term strategic planning.
Interactive: CLV & Churn Risk Calculator
Enter customer data to estimate Customer Lifetime Value and churn risk.
🧮 Worked Example: Saving a Customer Before They Leave
Illustrative: a Nepali internet service provider (ISP).
- Data: CRM combines 3 complaints about slow speed, a late payment and a visit to the "cancel" page.
- Prediction: the churn model flags the customer as high risk.
- Value check: 4 years as a customer, NPR 1,500/month → worth about NPR 18,000 a year.
- Action: a technician visit plus one free month (cost about NPR 1,500).
- Logic: spend NPR 1,500 to keep NPR 18,000 a year, instead of paying to win a new customer.
The Tech Behind the Analysis
Analytical CRM relies on powerful technologies to process data:
Data Warehouses
Central repositories that store and integrate customer data from multiple sources.
Data Mining
Techniques used to discover hidden patterns and relationships in large datasets.
OLAP Tools
Online Analytical Processing allows for fast, multi-dimensional analysis of data.
🛒 Data Mining in Action: Market-Basket Analysis
Finds products that are often bought together ("association rules").
- Illustrative: a supermarket finds that customers who buy instant noodles on Friday nights often also buy soft drinks.
- Uses: shelf placement, combo offers, "you may also like" suggestions online.
- Rules are measured by how often items appear together (support) and how reliable the link is (confidence).
🎰 Real Case: The Best Customers Weren't Who They Thought
In the late 1990s, US casino company Harrah's (now Caesars Entertainment) linked its loyalty card, Total Rewards, across all its properties.
- Every card swipe went into one data warehouse.
- Analysis showed much of its profit came from ordinary, frequent local visitors, not the rare big spenders it had courted.
- Harrah's shifted marketing and service to that segment, and built one of the best-known loyalty programmes in its industry.
Harrah's, Las Vegas
🎬 Watch: Harrah's Data Machine
Collaborative CRM: Working Together 🤝
Collaborative CRM facilitates communication, cooperation, and collaboration between all stakeholders—internal departments and external partners—involved in the customer relationship.
🎯 Primary Goal: To provide a seamless and consistent customer experience across all touchpoints.
🎬 Watch: The Omnichannel Experience
Functions of Collaborative CRM
Interaction Management
- Tracks every interaction (email, phone, social media, in-person).
- Creates a single, complete customer history available to everyone.
Channel Management
- Coordinates interactions across different communication channels.
- Ensures a smooth transition so customers don't have to repeat themselves.
It also includes Partner Relationship Management (PRM) to collaborate with vendors and distributors.
Interactive: Collaborative CRM in Action
Follow a customer's issue across channels. Notice how Collaborative CRM keeps the context intact at each step.
CRM in Action: A Nepali Example
Scenario: An e-commerce site like Daraz
🔍 Analytical CRM: Analyzes past Dashain sales data. It identifies a segment of customers who buy high-end smartphones. It then predicts the "next best offer" is a protective case and wireless earbuds.
🗣️ Collaborative CRM: The marketing team uses this insight for a targeted email campaign. A customer from that segment inquires about the earbud warranty on Facebook. The social media agent sees the customer's entire purchase history and can answer knowledgeably. The information is consistent everywhere.
Putting It All Together: The CRM Ecosystem
1. Operational CRM
Collects customer data from daily interactions (sales, service calls, website visits).
Input: Raw Data
2. Analytical CRM
Analyzes the data to find patterns, segment customers, and predict behavior.
Output: Actionable Insights
3. Collaborative CRM
Shares these insights across all departments and channels to create a unified experience.
Result: Better Decisions
Interactive: Sort the CRM Activities
Click an activity card to select it, then click the matching CRM bucket to place it.
🧪 Quick Activity: Which Analytical Technique?
Segmentation, churn prediction, market-basket or CLV?
- A bookshop wants to know which titles to place next to each other. → Market-basket
- A gym wants to know which members are likely to quit next month. → Churn prediction
- A bank wants to know how much a new student account is worth over 20 years. → CLV
- A clothing brand wants different campaigns for teens, office workers and parents. → Segmentation
💬 Discuss: Data That Helps, Data That Hurts
- Would you be happy if your mobile operator offered you a deal just as you were about to switch?
- Is it fair to give "low-value" customers less service?
- How does collaborative CRM make sure the insight actually reaches the person talking to the customer?
Key Takeaways
- Analytical CRM analyzes customer data to provide strategic insights like segmentation, churn risk, and customer lifetime value (CLV).
- Collaborative CRM focuses on sharing information across teams and partners to provide a seamless, consistent customer experience.
- The three types of CRM (Operational, Analytical, Collaborative) work together as a cohesive system to manage the entire customer lifecycle.
Exam Practice 📝
Short answer
- What is analytical CRM?
- What is collaborative CRM?
- Distinguish between operational and analytical CRM.
Exam Practice 📝 (continued)
Long answer
- Compare operational, analytical, and collaborative CRM with examples.
- Explain how analytical CRM helps businesses retain customers.
Revise the answers in the full note.
Image & Video Credits
Images
- Harrahs 3: Tony Hisgett from Birmingham, UK, CC BY 2.0, via Wikimedia Commons
- Market basket diagram: course author (original), CC BY 4.0
Videos (YouTube)
- SIS BINUS, "Operational vs Analytical CRM" (196–281 s)
- Hard Numbers, "26% of Customers, 82% of Revenue: Harrah's Data Machine" (63–118 s)
- Shep Hyken, "The Omnichannel Customer Experience – What Is It?" (44–131 s)
Thank You
Next Topic: Unit 7.5: The Structure of a Supply Chain | IT 233