Data Lake Architecture

Hearing the Voice of the Customer

Increase the awareness of your customer’s behavior to survive and excel within your industry.

One hundred years ago, the voice of the customer was easily and routinely heard by the shopkeeper. In small towns, the shopkeeper knew everyone. Today’s world has gotten much bigger and much more complex. No longer does the store owner personally know everyone who comes into the store. Yet there are three important abilities technologies offer that make it possible to listen to the voice of the customer today:

  • The ability to acquire, store, and manage huge amounts of data
  • The ability to read and understand text in a computerized environment
  • The ability to visualize data

This book answers important questions such as:

  • Where is the voice of the customer heard?
  • How does the corporation find and capture the voice of the customer?
  • How is the voice of the customer actually interpreted and understood?
  • How do you cope with the volume of messages the customer is sending you?
  • How do you separate noise from the important messages?
  • How do you analyze the composite voice of the customer over thousands of customers?
  • How do you reduce the voice of the customer to a visual format that is understood by management?
  • How do you know when the message the customer is sending changes?

After reading this book the reader will be able to manage, build, and operate a corporate infrastructure that listens to the voice of the customer.

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Topics

1: value
Where is the voice of the customer?
What is the customer saying?
New customers versus existing customers
Changing marketplace
How to listen to the voice of the customer?
Feedback to the customer
In summary


2: source
On paper
Voice recognition
Email
Social media
Spreadsheets
Surveys
Warranty claims
Processing the voice of the customer
In summary


3: technology
Components of technology
Special technology needed
No special technology needed
Volumes of data
Converting text into a database format
Visualization
In summary


4: taxonomies
Generic vs specific taxonomies
Taxonomy depth
Multi lingual taxonomies
Other forms of taxonomies
Dynamics of a taxonomy
In summary


5: text
Connectors
Predicates
Complex sentences
Negatives
Scope of inference
Supercategories
What is a product?
Drill down analysis
Is there text that cannot be analyzed?
In summary


6: visualization
Visualizing the voice of the customer
Expectation phenomenon
The importance of negative feedback
Non sentiment data
In summary


7: restaurants
The voice of the customer
Feedback over the internet
Textual etl
So what is the customer saying?
Leaving money on the table
Drill down processing
In summary


8: call centers
What you would like to know
Textual etl
Visualization
Processing text
The relational database
In summary


9: airlines
Listening to the customer
Gathering the customer feedback
In summary


10: surveys
The real value of the survey
Taxonomies
Sentiment and declarative statements
Different types of sentiment
Segmenting the respondents
In summary


11: strategy
Strategically and tactically
A corporate benchmark
What’s on the customer’s mind?
How to improve the customer experience
In summary


12: infrastructure
Refining raw data
Different kinds of visualization
Origins of drill down processing
Unit of time
In summary


13: combinations
In summary

About Bill

Bill Inmon, the “father of the data warehouse,” has written 60 books published in nine languages. ComputerWorld named Bill one of the ten most influential people in the history of the computer profession. Bill’s latest adventure is the building of technology known as textual disambiguation.

Storytelling & Communication Books