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Text Analytics Beginner’s Guide
Extracting Meaning from Unstructured Data
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
©2013 Angoss Software Corporation. All rights reserved.
Contents
Text Analytics 3 Use Cases 7 Terms 9 Trends 14 Scenario 15 Resources 24
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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.
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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?
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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’.
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
Terms
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.
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?
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
Terms
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.
Concept Score Software and Internet
.56
Social Media .60 Technology .49 Business .72
Classification/Concepts “What” are the important, high-level concepts?
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
Terms
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 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?
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
Scenario
Sentiment breakdown across all reviews
Sentiment distribution across all documents
Sentiment distribution for Top 10 topics, themes and entities
Sentiment Dashboard
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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.
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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.
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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
SportsHigh 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 MediaHigh 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
WarHigh 768 39.65%
Low 1,169 60.35%
Total 1,937 1.03%
Software and Internet
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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 Sale Price $13.24
Avg Sentiment null
Most Common Phrase null
Treatment Ignore
null
Total 188,788 99.99%
Avg Rating 4.20
Avg Sale Price $15.05
Avg Sentiment 0.22
Most Common Phrase great
[1,5644] rating
Total 75,890 40.19%
Avg Rating 3.01
Avg Sale Price $14.71
Avg Sentiment 0.12
Most Common Phrase great
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 Sale Price $15.27
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 Sale Price $13.45
Avg Sentiment 0.34
Most Common Phrase wonderful
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 Sale Price $18.65
Avg Sentiment 0.30
Most Common Phrase great
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 Sale Price $15.32
Avg Sentiment 0.24
Most Common Phrase wonderful
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 Sale Price $12.40
Avg Sentiment 0.26
Most Common Phrase wonderful
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 Sale Price $17.98
Avg Sentiment 0.23
Most Common Phrase wonderful
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 Sale Price $17.05
Avg Sentiment 0.27
Most Common Phrase wonderful
Treatment E-Mail New Hot Reads
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 Sale Price $20.97
Avg Sentiment 0.24
Most Common Phrase wonderful
Treatment E-Mail 25% Off Coupon
Environment
Hardware
Price
High 1,295 15.99%
Low 6,802 84.01%
Total 8,097 4.29%
Avg Rating 5.00
Avg Sale Price $16.66
Avg Sentiment 0.29
Most Common Phrase wonderful
Treatment E-Mail New Hot Reads
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 Sale Price $25.10
Avg Sentiment 0.34
Most Common Phrase great
Treatment E-Mail 25% Off Coupon
Social Media
Software and Internet
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
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
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Text Analytics | Use Cases | Terms | Trends | Scenario | Resources
©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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