CRM Types, Models & Implementation: Strategic, Operational, Analytical

TAKEAWAYS:

• CRM systems are classified into strategic (relationship-building), operational (transactional), and analytical (data-driven) types, each serving distinct business needs.
• Implementation requires planning, technology integration, employee training, and cultural alignment, with Nepal-specific challenges like internet connectivity and resistance to change.
• Nabil Bank’s CRM uses operational CRM for loan processing, while Daraz leverages analytical CRM for personalized recommendations—both reducing costs and increasing customer retention.
• Data warehousing and marketing intelligence are critical for analytical CRM, enabling predictive modeling (e.g., Ncell’s churn prediction).
• Common pitfalls in Nepal include poor data quality, high implementation costs, and lack of top-management commitment.
• Exam focus: Define CRM types, explain implementation steps, and discuss Nepal-specific challenges with real-world examples (e.g., eSewa’s customer service automation).

1. Types of CRM Systems

CRM systems are categorized based on their primary function and business impact. The three main types are:

A. Strategic CRM (Relationship CRM)

Definition: Focuses on long-term customer relationships through personalized interactions, loyalty programs, and relationship-building strategies. Key Features:

• Uses customer touchpoints (e.g., social media, email, in-person interactions).
• Aims to increase customer loyalty and reduce churn.
• Relies on employee training and cultural alignment (e.g., Nabil Bank’s relationship managers).

Example in Nepal:

• Nabil Bank’s "Nabil Relationship Manager" program:
  • Uses strategic CRM to assign dedicated relationship managers to high-value customers.
  • Outcome: Higher customer retention (30% reduction in churn) and increased cross-selling of financial products.

mindmap
  root((Strategic CRM))
    Customer Touchpoints
      Social Media
      Email Marketing
      In-Person Interactions
    Goals
      Increase Loyalty
      Reduce Churn
    Tools
      Loyalty Programs
      CRM Software (e.g., Salesforce)
    Nepal Example
      Nabil Bank's Relationship Managers

B. Operational CRM (Transaction CRM)

Definition: Manages day-to-day customer interactions (sales, marketing, customer service) using automated processes. Key Features:

• Front-office applications (e.g., sales force automation, customer service portals).
• Real-time data processing (e.g., order tracking, complaint resolution).
• Example in Nepal:
  • eSewa’s customer service portal:
    • Uses operational CRM to handle bill payments, complaints, and refunds via chatbots and call centers.
    • Outcome: Reduced response time from 48 hours to under 2 hours for complaint resolution.

flowchart TD
  A["Operational CRM"] --> B["Sales Force Automation"]
  A --> C["Customer Service"]
  A --> D["Marketing Automation"]
  B --> E["eSewa Order Tracking"]
  C --> F["eSewa Chatbot for Complaints"]
  D --> G["Daraz Promotional Emails"]

C. Analytical CRM (Data-Driven CRM)

Definition: Uses data analysis to predict customer behavior, segment customers, and optimize marketing strategies. Key Features:

• Data warehousing and business intelligence tools (e.g., Tableau, Power BI).
• Predictive modeling (e.g., churn prediction, upsell opportunities).
• Example in Nepal:
  • Ncell’s "Smart Predict" program:
    • Uses analytical CRM to predict which customers are likely to switch to competitors.
    • Outcome: Targeted discounts reduced churn by 25% in 6 months.

mindmap
  root((Analytical CRM))
    Data Sources
      Customer Transactions
      Social Media Data
      Call Center Logs
    Tools
      Data Warehousing
      Predictive Analytics (Python/R)
    Nepal Example
      Ncell Churn Prediction
    Global Example
      Amazon Product Recommendations

2. Comparison of CRM Types

3. Implementation of CRM Systems

Implementing CRM requires a structured approach. The 7-step framework (adapted from Kotler & Keller) is widely used:

flowchart TD
  A["1. Define Objectives"] --> B["2. Assess Current Systems"]
  B --> C["3. Select CRM Software"]
  C --> D["4. Data Migration & Cleaning"]
  D --> E["5. Employee Training"]
  E --> F["6. Pilot Testing"]
  F --> G["7. Full Rollout & Monitoring"]

Step-by-Step Breakdown

1. Define Objectives

   • Example: "Reduce customer complaints by 40% in 12 months" (eSewa’s goal).
   • Key Question: What problem is CRM solving? (e.g., high churn, low sales).

2. Assess Current Systems

   • Gap Analysis: Compare existing processes vs. CRM capabilities.
   • Example: Daraz found their manual order tracking led to delays → needed operational CRM.

3. Select CRM Software

   • Options for Nepal:
     • Budget-friendly: Zoho CRM, HubSpot.
     • Enterprise: Salesforce, Microsoft Dynamics.
   • Decision Factors:
     • Cost, scalability, ease of use, local support (e.g., Nepal-based CRM providers like Soft9000).

4. Data Migration & Cleaning

   • Challenge in Nepal: Poor data quality (e.g., duplicate customer records in NTC’s billing system).
   • Solution: Use data cleansing tools (e.g., OpenRefine) before migration.

5. Employee Training

   • Critical for Nepal: Many employees resist digital tools due to low digital literacy.
   • Example: Pathao’s CRM training reduced onboarding time by 50% after structured workshops.

6. Pilot Testing

   • Example: Himalayan Java tested CRM in one branch before full rollout.
   • Metrics to Track:
     • Customer satisfaction (CSAT) score.
     • Response time for queries.

7. Full Rollout & Monitoring

   • Continuous Improvement: Use KPIs like:
     • Customer Retention Rate (CRR)
     • Net Promoter Score (NPS)
     • Cost per Acquisition (CPA)

4. Challenges in CRM Implementation (Nepal-Specific)

5. Real-World Case Study: Daraz Nepal’s CRM Implementation

Problem:

• High cart abandonment rate (70%) due to poor checkout experience.
• No personalized recommendations, leading to low repeat purchases.

Solution:

1. Implemented Operational CRM (Salesforce) for:
   • Automated order tracking.
   • 24/7 chatbot support (reduced response time to <10 minutes).
2. Analytical CRM for:
   • Customer segmentation (e.g., "frequent buyers" vs. "first-time users").
   • Personalized email campaigns (e.g., "You left items in your cart!").
3. Strategic CRM:
   • Loyalty program ("Daraz Plus") with discounts for repeat buyers.

Results:

• Cart abandonment dropped to 30%.
• Repeat purchase rate increased by 45%.
• Customer satisfaction (CSAT) score improved from 65% to 88%.

flowchart LR
  A["High Cart Abandonment"] --> B["Implemented CRM"]
  B --> C["Operational: Order Tracking"]
  B --> D["Analytical: Personalized Emails"]
  B --> E["Strategic: Loyalty Program"]
  C --> F["↓ Response Time"]
  D --> G["↑ Repeat Purchases"]
  E --> H["↑ Customer Retention"]

6. Data Warehousing and Marketing Intelligence in CRM

Why It Matters:

• Analytical CRM relies on clean, structured data stored in data warehouses.
• Marketing intelligence uses this data to predict trends (e.g., "Diwali season sales spike").

Example: Ncell’s Data-Driven Strategy

1. Data Sources:
   • Call center logs.
   • Mobile usage patterns.
   • Customer demographics.
2. Tools Used:
   • SQL databases (for storage).
   • Python/R (for predictive modeling).
3. Outcome:
   • Predicted 80% of customers likely to churn before it happened.
   • Targeted discounts reduced churn by 25%.

mindmap
  root((Marketing Intelligence in CRM))
    Data Sources
      Call Center Logs
      Transaction Data
      Social Media
    Tools
      SQL Databases
      Python/R for Predictive Analytics
    Nepal Example
      Ncell Churn Prediction
    Global Example
      Amazon’s "Frequently Bought Together"

7. Costs of Poor CRM Implementation

Hidden Costs of Failing CRM:

How CRM Reduces These Costs:

• Automation (e.g., Daraz’s chatbot) cuts customer service costs by 30%.
• Personalization (e.g., Nabil Bank’s offers) increases sales by 15-20%.

In the Real World

1. eSewa’s Operational CRM

   • What it uses: Automated complaint resolution via chatbots and call centers.
   • How it works: When you report a failed transaction, eSewa’s CRM auto-assigns a case, tracks resolution time, and sends SMS updates.
   • Impact: Reduced average resolution time from 48 hours to under 2 hours.

2. Nabil Bank’s Strategic CRM

   • What it uses: Relationship managers + CRM software to track customer interactions.
   • How it works: High-value customers get a dedicated manager who logs all interactions (loan inquiries, complaints) in the CRM.
   • Impact: 30% lower churn among premium customers.

3. Daraz’s Analytical CRM

   • What it uses: Customer segmentation and predictive analytics.
   • How it works: Daraz’s system predicts which users are likely to abandon carts and sends personalized discounts.
   • Impact: 45% increase in repeat purchases during festive seasons.

Exam Tip

How to Score Full Marks

1. Define CRM Types Clearly

   • Always start with strategic, operational, analytical and give one Nepal example each.
   • Example:

     "Operational CRM automates transactional processes like sales and service. For instance, eSewa uses operational CRM to track bill payments and complaints in real-time, reducing resolution time from 48 hours to under 2 hours."

2. Implementation Steps Are High-Weightage

   • Memorize the 7-step framework and link it to Nepal-specific challenges.
   • Example:

     "In Nepal, data migration is a major hurdle due to poor data quality. For example, NTC’s billing system had 20% duplicate records, which needed cleansing before CRM integration."

3. Use Real-World Examples

   • Examiners love case studies. Mention Nabil Bank, Daraz, eSewa, or Ncell wherever possible.
   • Example:

     "Ncell’s analytical CRM uses predictive modeling to identify customers likely to churn. By offering targeted discounts, they reduced churn by 25% in 6 months."

4. Compare CRM Types in Tables

   • A well-structured table (like the one above) can earn you 5+ marks in descriptive questions.

5. Discuss Nepal-Specific Challenges

   • Internet connectivity, high costs, resistance to change are common exam topics.
   • Example:

     "Poor internet in rural Nepal makes cloud-based CRM difficult. NTC’s field technicians use offline CRM tools to log repairs without internet."

6. Link to Data Warehousing & Marketing Intelligence

   • Always connect analytical CRM to data warehouses and predictive analytics.
   • Example:

     "Daraz’s CRM stores customer data in a data warehouse, which is then analyzed using Python scripts to predict purchase behavior."

Final Advice:

• Practice past exam questions by writing short case studies (e.g., "How would you implement CRM for a local bakery?").
• Draw flowcharts for implementation steps—they visually reinforce your answer.
• Use bullet points for challenges/solutions (examiners prefer structured answers).