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DATA MINING IN CRM
ROLUSTECH
AGENDA
• What is Data Mining?
• Role of Data Mining in CRM
• How will Data Mining benefit my business?
• Techniques of Data Mining in CRM
What is Data Mining?
• The process of determining useful
patterns and relationships in big data
through algorithms, to extract
knowledge from data warehouses.
Role of Data Mining in CRM
• Get a holistic view of customer life-
cycle
• More data will result in accurate
models
• Leverage forecasting and descriptive
modeling techniques
• Have a proactive approach with
predictive analytics
How will Data
Mining Benefit my
Business?
● Conduct Basket Analysis for
better stocking, store layout, and
promotion strategies
● Sales Forecasting to optimize
your sales, supply chain and
financial management
● Predictive Lifecycle
Management for each customer
to segment them accordingly
How will Data
Mining Benefit my
Business?
● Optimal Allocation of company’s
resources for enhanced
productivity and better ROI
● Product Customization by
predicting features that meet the
customer’s demands
● Database Marketing for a
defined target market,
personalized campaigns and
promotional offers
How will Data
Mining Benefit my
Business?
● Predict Warranty Claims by the
customers and their average
cost to have efficient
management of funds
● Fraud detection by analyzing
past fraudulent transactions and
taking corrective measures
Techniques of Data Mining in CRM
Data Mining Techniques
• Clustering – Identify similar
data sets, and understand
both similarities and
differences in data to
increase conversion rates
• Classification – Gather all
information about a data set
and classify it into proper
categories.
• Anomaly Detection –
Information that does not
match the expected behavior
or projected pattern,
providing actionable
information
Data Mining Techniques
• Association Rule Learning –
Uncover hidden patterns from the
data to better understand your
customer’s habits and predict their
decisions
• Regression – Find dependency
between different data items and
map out the effect of variables on
each other. It helps in determining
customer satisfaction levels and its
impact on customer loyalty
Read our entire blog here:
https://www.rolustech.com/blog/data-mining-crm
Our Expertise
CRM Mobile Product Development
1 2 3
GET IN TOUCH
SUGARCRM
SERVICES
SALESFORCE
SERVICES
SUITECRM
SERVICES
SUGARCRM
PLUGINS
INDUSTRY
SOLUTIONS
Check out our links below
Further Reading
1. How is Big Data Relevant To CRM?
2.CRM and Small Data Analytics
3.Artificial Intelligence and the future of CRM
4.Top 4 Ways your CRM can use Predictive
Intelligence

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Data Mining in CRM

  • 1. DATA MINING IN CRM ROLUSTECH
  • 2. AGENDA • What is Data Mining? • Role of Data Mining in CRM • How will Data Mining benefit my business? • Techniques of Data Mining in CRM
  • 3. What is Data Mining? • The process of determining useful patterns and relationships in big data through algorithms, to extract knowledge from data warehouses.
  • 4. Role of Data Mining in CRM • Get a holistic view of customer life- cycle • More data will result in accurate models • Leverage forecasting and descriptive modeling techniques • Have a proactive approach with predictive analytics
  • 5. How will Data Mining Benefit my Business? ● Conduct Basket Analysis for better stocking, store layout, and promotion strategies ● Sales Forecasting to optimize your sales, supply chain and financial management ● Predictive Lifecycle Management for each customer to segment them accordingly
  • 6. How will Data Mining Benefit my Business? ● Optimal Allocation of company’s resources for enhanced productivity and better ROI ● Product Customization by predicting features that meet the customer’s demands ● Database Marketing for a defined target market, personalized campaigns and promotional offers
  • 7. How will Data Mining Benefit my Business? ● Predict Warranty Claims by the customers and their average cost to have efficient management of funds ● Fraud detection by analyzing past fraudulent transactions and taking corrective measures
  • 8. Techniques of Data Mining in CRM
  • 9. Data Mining Techniques • Clustering – Identify similar data sets, and understand both similarities and differences in data to increase conversion rates • Classification – Gather all information about a data set and classify it into proper categories. • Anomaly Detection – Information that does not match the expected behavior or projected pattern, providing actionable information
  • 10. Data Mining Techniques • Association Rule Learning – Uncover hidden patterns from the data to better understand your customer’s habits and predict their decisions • Regression – Find dependency between different data items and map out the effect of variables on each other. It helps in determining customer satisfaction levels and its impact on customer loyalty
  • 11. Read our entire blog here: https://www.rolustech.com/blog/data-mining-crm
  • 12. Our Expertise CRM Mobile Product Development 1 2 3
  • 14. Further Reading 1. How is Big Data Relevant To CRM? 2.CRM and Small Data Analytics 3.Artificial Intelligence and the future of CRM 4.Top 4 Ways your CRM can use Predictive Intelligence