Chat with us, powered by LiveChat 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 | WriteDen

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

 

 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. 

Managing Customer Relationships: A Strategic Framework, Third Edition, Don Peppers and Martha Rogers

MKT 456-CRM Instructor: Cynthia Bellian, MBA E-mail: [email protected]

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Managing Customer Experience and Relationships: A Strategic Framework

Chapter 12

Using Customer Analytics Measuring to Build the Success of the Customer-Strategy Enterprise

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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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