Ebook: Text Analytics Beginner's Guide

Text Analytics
Beginner’s Guide
Extracting Meaning from
Unstructured Data

33
Text Analytics
Powerful trends in social media, e-discovery,
customer services (call center transcriptions
of voice calls, customer complaint emails and
instant messaging) and customer-centric
business strategies are driving IT leaders to
consider text analytics as a powerful
business tool.
The transformed information from text
analytics can be combined with structured
data (e.g., sales and demographic data)
and analyzed using various business
intelligence or predictive and automated
discovery techniques.
Successful companies today both listen to and understand what customers are
saying and are taking action in response to customer feedback by incorporating the
voice of the customer (VOC) into business strategies for sales, marketing and
customer service using text analytics.

44
Text Analytics
Text analytics is the process of analyzing
unstructured text, extracting relevant
information, and transforming it into
structured information that can be
leveraged in various ways.
Text analytics describes a set of
linguistic, statistical and
machine learning techniques
that model and structure the
information content of textual
sources for business
intelligence, exploratory data
analysis, research or
investigation.
What is Text Analytics?

55
Text Analytics
Today, 80% of business information
originates in unstructured data; primarily
text with no identifiable structure.
...although structured data
continues to be the primary source
for business intelligence.
Structured Data

66
Text Analytics
• Emails
• Customer Surveys
• Documents
• Call Center Notes
• Claims Records
• Customer Forms
• Customer Letters
• Blogs
• Social Media
• Tweets
• Online Forums
• Articles / Reports
• Web
INTERNAL EXTERNAL
Unstructured Data

77
Use Cases
Text Analytics transforms unstructured data into
structured data for analysis to help...
• Monitor and analyze brand reputation
• Determine purchase behavior
• Identify product issues
• Summarize surveys, customer reviews
• Improve customer service and
customer experience management
• Understand customer feedback
• Improve customer retention
• Predict and reduce churn
• Identify and reduce claims fraud
• Develop cross-sell, upsell strategies
• Design next best offer strategies

88
Use Cases
Marketing Business Industry-Specific
• Voice of customer
• Social media analysis
• Churn analysis
• Market research
• Survey analysis
• Competitive intelligence
• Document categorization
• Human resources
• Records retention
• Risk analysis
• Website navigation
• News feeds analysis
• Fraud detection
• E-discovery
• Warranty analysis
• Medical research

99
Terms
1. Entity: “Who, where, when” is
being discussed?
2. Theme: “What” are the important
words?
3. Classification: “What” are the
important concepts?
4. Sentiment : “How” is the
conversation going? Is it positive
or negative?
Or…given a collection of text, text analytics
tells you who, where, when, what, and
how so that you can figure out ‘why’.

1010
Terms
Entity
“Who, where, when” is being discussed?
Yahoo wants to make its Web e-mail service a place you never want to
– or more importantly – have to leave to get your social fix.
The company on Wednesday is releasing an overhauled version of its
Yahoo Mail Beta client that it says is twice as fast as the previous
version, while managing to tack on new features like an integrated
Twitter client, rich media previews and a more full-featured instant
messaging client.
Yahoo says this speed boost should be especially noticeable to users
outside the U.S. with latency issues, due mostly to the new version
making use of the company's cloud computing technology. This means
that if you're on a spotty connection, the app can adjust its behavior to
keep pages from timing out, or becoming unresponsive.
Besides the speed and performance increase, which Yahoo says were
the top users requests, the company has added a very robust Twitter
client, which joins the existing social-sharing tools for Facebook and
Yahoo.
Entity Type
Yahoo Company
Twitter Company
Facebook Company
U.S. Place

1111
Terms
messaging client.
Yahoo.
Theme Score
Cloud computing
technology
4.11
E-mail service 2.672
Top users
requests
2.669
Theme
“What” are the important words being used?

1212
Terms
messaging client.
Yahoo.
Concept Score
Software and
Internet
.56
Social Media .60
Technology .49
Business .72
Classification/Concepts
“What” are the important, high-level concepts?

1313
Terms
messaging client.
Yahoo.
Entity Sentiment
Yahoo .534
Twitter .48
Facebook .534
Concept Sentiment
Software and Internet 0.0
Social Media .48
Technology .49
Theme Sentiment
Cloud computing
technology
1.3
Mail service .16
Top user requests .83
Sentiment
“How” is the conversation going ? Positive or negative?

1414
Trends
1. Social media analytics adoption drives text analytics.
2. Analytics moves beyond sentiment analysis.
3. The market begins to get the connection between text and Big Data.
4. Marrying structured and unstructured data becomes more popular.
5. The cloud becomes more popular for text analytics.
Text Analytics Victory Index Report, January, 2013

1515
Scenario
An online book retailer tracks customer feedback by analyzing reviews
and comments from online forums and social media.
They use Angoss KnowledgeREADER™ to extract meaning from the
text to discover what is being discussed and how – the sentiment
(positive or negative), and answer:
• What are customers saying on a regional basis?
• How frequently do certain entities, themes and topics occur?
• Which themes and topics occur together, and are related?
• How is sentiment trending over time?
• What is the context of what is being discussed at the document
level?
Book Reviews: Customer Feedback

1616
Scenario
Sentiment breakdown across all
reviews
Sentiment distribution across all
documents
Sentiment distribution for Top 10
topics, themes and entities
Sentiment Dashboard

1717
Scenario
The retailer can compare overall
sentiment across stores, or isolate
individual topics, themes, entities
and phrases to determine how those
items are discussed between various
regions
For example, you can see that the
topic “Technology” is viewed more
negatively in Store 2, but it is also
discussed more frequently as well.
Comparison Analysis

1818
Scenario
By isolating topics, themes, entities
or phrases, the retailer can examine
how frequently they were
mentioned.
They can also view how customer
sentiment regarding these terms
changed alongside the frequency of
their occurrence.
Trend Analysis

1919
Scenario
Association Discovery
Using the Association Map, the
retailer can visually determine the
frequency with which certain terms
occur, and how closely they relate to
other terms used in customer
reviews.
The retailer can quickly assess how
well certain subjects are received,
and how much relative interest their
customers have in those subjects.

2020
Scenario
Document Summary
Individual terms can be isolated, as
well as the sentences and documents
that reference them – giving you a
detailed look at the context used in
reviews.
Each text record can be completely
isolated for a full examination of the
content and sentiment contained
within.

2121
Scenario
Decision Tree
KnowledgeREADER can be used to analyze the output of your text analysis with structured data, and use data
mining and predictive analytics techniques to expand customer insights.
In this example, the retailer has created a Decision Tree that allows them to determine the price breakdown across
book genres. The Decision Tree uses ‘High’ and ‘Low’ price brackets to segment genres.
The retailer can now determine if there is a correlation between price, genre and overall sentiment. They may use
these insights to inform product inventory or pricing decisions.
Price
High 26,820 14.21%
Low 161,985 85.79%
Total 188,805 100.00%
rank_1_topic
High 8,662 10.94%
Low 70,489 89.06%
Total 79,151 41.92%
null
Automotive
Hotels
Video Games
Weather
High 5,906 17.57%
Low 27,711 82.43%
Total 33,617 17.81%
Advertising
Aviation
Education
Investing
Law
Religion
High 3,037 13.43%
Low 19,583 86.57%
Total 22,620 11.98%
Agriculture
Art
Biotechnology
Crime
Disasters
Food
Politics
Space
Sports
High 1,136 9.16%
Low 11,270 90.84%
Total 12,406 6.57%
Banking
Beverages
Marriage
Real Estate
Renewable Energy
Robotics
Travel
High 1,862 19.87%
Low 7,509 80.13%
Total 9,371 4.96%
Business
Economics
Mobile Devices
High 889 15.18%
Low 4,968 84.82%
Total 5,857 3.10%
Elections
Fashion
Intellectual Property
Labor
Popular Culture
High 551 23.93%
Low 1,752 76.07%
Total 2,303 1.22%
Environment
Social Media
High 92 30.77%
Low 207 69.23%
Total 299 0.16%
Hardware
High 853 11.83%
Low 6,356 88.17%
Total 7,209 3.82%
Health
Traditional Energy
High 3,064 21.83%
Low 10,971 78.17%
Total 14,035 7.43%
Science
Technology
War
High 768 39.65%
Low 1,169 60.35%
Total 1,937 1.03%
Software and Internet

2222
Scenario
Strategy Tree
KnowledgeREADER can be used to build and
deploy predictive strategies with Strategy Trees.
Here, the retailer has identified segments based
on price and genre. In addition, they can track key
metrics that drive store performance.
Combined with the text analysis output, this
measures the average sentiment, rating, sale price
and the most common themes discussed in each
segment.
By associating a treatment with each segment, the
retailer can automatically assign specific actions
or activities to each segment.
Now, the book retailer can quickly turn insight into
action.
Total 188,805 100.00%
Avg Rating 4.20
Avg Sale Price $15.05
Avg Sentiment 0.22
Most Common Phrase great
word_count
Total 17 0.01%
Avg Rating 4.65
Avg Sentiment null
Most Common Phrase null
Treatment Ignore
null
Total 188,788 99.99%
Avg Rating 4.20
Avg Sentiment 0.22
[1,5644] rating
Total 75,890 40.19%
Avg Rating 3.01
Avg Sentiment 0.12
Treatment Ignore
[1,4]
Price
High 16,414 14.54%
Low 96,484 85.46%
Total 112,898 59.80%
Avg Rating 5.00
Avg Sentiment 0.30
Most Common Phrase wonderful
5 rank_1_topic
Price
High 5,208 10.67%
Low 43,581 89.33%
Total 48,789 25.84%
Avg Rating 5.00
Avg Sentiment 0.34
Treatment E-Mail BOGO
null
Beverages
Hotels
Real Estate
Video Games
Weather
Price
High 1,211 21.10%
Low 4,529 78.90%
Total 5,740 3.04%
Avg Rating 5.00
Avg Sentiment 0.30
Treatment E-Mail New Hot Reads
Advertising
Aviation
Business
Economics
Price
High 1,755 13.67%
Low 11,079 86.33%
Total 12,834 6.80%
Avg Rating 5.00
Avg Sentiment 0.24
Treatment E-Mail Buy 3 Get 4th Free
Agriculture
Art
Crime
Disasters
Health
Space
Sports
Traditional Energy
Price
High 618 9.61%
Low 5,813 90.39%
Total 6,431 3.41%
Avg Rating 5.00
Avg Sentiment 0.26
Treatment E-Mail BOGO
Automotive
Banking
Marriage
Renewable Energy
Robotics
Travel
Price
High 1,819 22.68%
Low 6,200 77.32%
Total 8,019 4.25%
Avg Rating 5.00
Avg Sentiment 0.23
Treatment E-Mail 25% Off Coupon
Biotechnology
Elections
Science
Technology
War
Price
High 3,725 18.14%
Low 16,815 81.86%
Total 20,540 10.88%
Avg Rating 5.00
Avg Sentiment 0.27
Education
Intellectual Property
Labor
Law
Religion
Price
High 369 25.31%
Low 1,089 74.69%
Total 1,458 0.77%
Avg Rating 5.00
Avg Sentiment 0.24
Environment
Hardware
Price
High 1,295 15.99%
Low 6,802 84.01%
Total 8,097 4.29%
Avg Rating 5.00
Avg Sentiment 0.29
Fashion
Food
Investing
Mobile Devices
Politics
Popular Culture
Price
High 414 41.82%
Low 576 58.18%
Total 990 0.52%
Avg Rating 5.00
Avg Sentiment 0.34
Social Media
Software and Internet

2323
Scenario
Angoss KnowledgeREADER
KnowledgeREADER is an industry-first software application that brings a new age
of integrated customer intelligence by combining visual text discovery and
sentiment analysis with the power of predictive analytics.
Now, customer intelligence professionals and marketers can easily understand and
model customer feedback without relying on data analysts.
KnowledgeREADER delivers unparalled customer intelligence and voice of the
customer insights to support customer experience management—above and
beyond what text analytics users have come to expect.
Learn more about KnowledgeREADER

2424
Resources
Video
Quick Tour of KnowledgeREADER
Articles
Voice of the Customer, How to Move Beyond Listening to Action
Text Analytics Categorization and Concept Topics
Text Analytics Phrase and Theme Extraction
Text Analytics Sentiment Extraction
Text Analytics Named Entity Extraction
Brochure
KnowledgeREADER
Web
KnowledgeREADER

25
©2013 Angoss Software Corporation. All rights reserved.
About Angoss
Angoss Software Corporation is a global leader in delivering
business intelligence software and predictive analytics to
businesses looking to improve performance across sales, marketing
and risk. With a suite of desktop, client-server and big data software
products and Cloud solutions, Angoss delivers powerful approaches
to turn information into actionable business decisions and
competitive advantage. Angoss software products and solutions are
user-friendly and agile, making predictive analytics accessible and
easy to use.
For more information visit www.angoss.com.

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Ebook: Text Analytics Beginner's Guide