Refer to Chapter 12: Customer analytics help to solve several important problems, including? (a) classification, ?(b) estimation, and ?(c) prediction.?? If you are employed or have worked
Refer to Chapter 12: Customer analytics help to solve several important problems, including
(a) classification,
(b) estimation, and
(c) prediction.
If you are employed or have worked at a company what opportunities exist to make better use of each of these analytical approaches to enhance customer relationships?
Or if you have limited employment experience then focus more on your role as a consumer, have you observed examples of marketing that suggest a company is engaging in classification, estimation, or prediction analyses?
Describe these examples, the extent to which the company’s customer analytics were right, and the impact that the marketing activities had on your relationship with the company.
Chapter 12 Preview
Data Mining and Customer Analytics
The Goal of Customer Analytics
The Analysis Process
Evolution of CRM Software
The Benefits of Customer Analytics
Not a Technology, but a Business Process
Key Questions in Analyzing Data
Using Analytics to Manage Multichannel Customer Experiences
The Three “I”s
Managing Customer Relationships: A Strategic Framework, Third Edition, Don Peppers and Martha Rogers
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Data Mining and Customer Analytics
Data mining: process of extracting and presenting new knowledge, previously undetectable, selected from databases for actionable decisions
Customer analytics: preferred term for “data mining”
Metaphor of “mining” implies batch process and static nuggets of information
Interactive age demands real-time analytics – to provide continuously developing, real-time insights into individual customers
Provides the missing link to understanding customers: prediction
Managing Customer Relationships: A Strategic Framework, Third Edition, Don Peppers and Martha Rogers
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The Goal of Customer Analytics
To enable the enterprise to classify, estimate, predict, cluster, and more accurately describe data about customers, using mathematical models and algorithms that ultimately simplify how it views its customer base and how it behaves toward individual customers
Managing Customer Relationships: A Strategic Framework, Third Edition, Don Peppers and Martha Rogers
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The Analysis Process
Classification: assigning instances to a group, then using the data to learn the pattern of traits that identify the group to which each instance belongs
Estimation: for determining a value for some unknown continuous variable, such as credit card balance or income
Regression: uses existing values to forecast what continuous values are likely to be
Prediction: using historical data to forecast future behavior
Clustering: maps customers within the database into groups based on their similarities
Managing Customer Relationships: A Strategic Framework, Third Edition, Don Peppers and Martha Rogers
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Evolution of CRM Software
Enterprise CRM
Based on client/server computing
SaaS CRM – “software as a service”
Greater efficiency and scalability for small-to-medium businesses
CRM in the cloud
Even greater risk reduction and efficiency
Provides access to broader data in cloud networks
Customers can interact with and customize platforms
Allows tracking of customer needs as well as values and behaviors
Managing Customer Relationships: A Strategic Framework, Third Edition, Don Peppers and Martha Rogers
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Who Benefits Most from Customer Analytics?
Consumer marketing companies collecting transactional data through call centers, Web sites, or electronic points of sale
Banks, credit card companies, telecommunications firms, and airlines were early adopters
Anyone generating large volumes of customer-specific information in the natural course of operating their business
Managing Customer Relationships: A Strategic Framework, Third Edition, Don Peppers and Martha Rogers
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Sales & Marketing Benefits of Customer Analytics
Improves shopper-to-buyer conversion rates through more relevant information and offers
Measurably increases sales through offering specific and more targeted cross-sell and upsell opportunities
Helps increase customer lifetime value, profitability, and Return on Customer
Improves operational efficiency through smarter, more relevant (and usually faster and less costly) customer service
Makes information exchanges and transactions easier, faster, and therefore more likely
Improves customer’s perception of service as a result of relevant messaging
Can provide improved service levels for best customers
Managing Customer Relationships: A Strategic Framework, Third Edition, Don Peppers and Martha Rogers
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Not a Technology, but a Business Process
Next level of analytics might include applying financial characteristics to data analysis, to more accurately portray the actual economic consequences of particular customer actions
Overall goal of analyzing data is deepening the relationship with each customer to increase the value of the customer base
A revolution in how marketing decisions are made – marketers can now predict how and how quickly customer value is changing and can take specific, real-time steps to increase customer value
Not a technology, but a business process
Managing Customer Relationships: A Strategic Framework, Third Edition, Don Peppers and Martha Rogers
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Key Questions in Analyzing Data
What does it mean for individual messages and sales offers to be “relevant”?
How many contacts should each of your customers receive from you – taking into account both inbound (customer-initiated) and outbound (company-initiated) contacts?
What should be the timing of your communications with your customer?
How should the budget be allocated across customers to make optimum use of corporate resources?
Which products or services, which messages through which channel, are most effective in driving customer value?
Managing Customer Relationships: A Strategic Framework, Third Edition, Don Peppers and Martha Rogers
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Using Analytics to Manage Multichannel Customer Experiences
Common today for a single brand to represent multiple lines of business, and for a single enterprise to encompass multiple brands
Analytics provides holistic view of the customer and makes customer behavior visible across the enterprise
Managing Customer Relationships: A Strategic Framework, Third Edition, Don Peppers and Martha Rogers
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The Three“I”s
Deepening customer insight
Data integration
Customer profiling and analysis
Channel analytics
Predictive modeling
Choreographing customer interaction
Outbound campaigns
Message personalization
Trigger-driven behavior monitoring
Continuously improving marketing performance
Campaign performance reporting
Marketing performance management
Marketing mix optimization
Managing Customer Relationships: A Strategic Framework, Third Edition, Don Peppers and Martha Rogers
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