Best Software for 2025 is now live!

Best Text Analysis Software

Matthew Miller
MM
Researched and written by Matthew Miller

Text analysis software, also called text analytics or text mining software, helps users gain insights from both structured and unstructured text data using natural language processing (NLP). Such insights include sentiment analysis, key phrases, language, themes and patterns, and entities, among others. These solutions leverage NLP and machine learning to pull out different insights and provide visual representations of the data for easier interpretation.

Text analysis tools can consume text data from a variety of sources, including emails, phone transcripts, surveys, customer reviews, and other documents. By importing text data from these different sources, businesses are better equipped to understand and analyze customer or employee sentiment, intelligently classify documents, and improve written content. Text analysis software may be used in conjunction with other analytics tools, including big data analytics and business intelligence platforms.

To qualify for the Text Analysis category, a product must:

Import text data from a variety of different data sources
Use natural language processing to extract insights from the text, including key phrases, language, sentiment, and other patterns
Provide visualizations for text data

Best Text Analysis Software At A Glance

Best for Small Businesses:
Highest User Satisfaction:
Best Free Software:
Show LessShow More
Highest User Satisfaction:
Best Free Software:

G2 takes pride in showing unbiased reviews on user satisfaction in our ratings and reports. We do not allow paid placements in any of our ratings, rankings, or reports. Learn about our scoring methodologies.

No filters applied
189 Listings in Text Analysis Available
(104)4.3 out of 5
2nd Easiest To Use in Text Analysis software
View top Consulting Services for Google Cloud Natural Language API
Save to My Lists
Entry Level Price:Free
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Derive insights from unstructured text using Google machine learning.

    Users
    • Software Engineer
    Industries
    • Computer Software
    • Information Technology and Services
    Market Segment
    • 51% Small-Business
    • 20% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Google Cloud Natural Language API Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    NLP Capabilities
    36
    Ease of Use
    34
    Accuracy
    22
    Natural Language Processing
    22
    Sentiment Analysis
    22
    Cons
    Expensive
    15
    Pricing Issues
    6
    Limitations
    5
    Limited Language Support
    5
    Poor Documentation
    5
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Google Cloud Natural Language API features and usability ratings that predict user satisfaction
    8.3
    Has the product been a good partner in doing business?
    Average: 8.9
    8.7
    Custom Extension
    Average: 8.2
    8.8
    Compositionality
    Average: 8.2
    8.3
    Pre-Built Parameterization
    Average: 8.4
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Google
    Company Website
    Year Founded
    1998
    HQ Location
    Mountain View, CA
    Twitter
    @google
    32,520,271 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    301,875 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Derive insights from unstructured text using Google machine learning.

Users
  • Software Engineer
Industries
  • Computer Software
  • Information Technology and Services
Market Segment
  • 51% Small-Business
  • 20% Mid-Market
Google Cloud Natural Language API Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
NLP Capabilities
36
Ease of Use
34
Accuracy
22
Natural Language Processing
22
Sentiment Analysis
22
Cons
Expensive
15
Pricing Issues
6
Limitations
5
Limited Language Support
5
Poor Documentation
5
Google Cloud Natural Language API features and usability ratings that predict user satisfaction
8.3
Has the product been a good partner in doing business?
Average: 8.9
8.7
Custom Extension
Average: 8.2
8.8
Compositionality
Average: 8.2
8.3
Pre-Built Parameterization
Average: 8.4
Seller Details
Seller
Google
Company Website
Year Founded
1998
HQ Location
Mountain View, CA
Twitter
@google
32,520,271 Twitter followers
LinkedIn® Page
www.linkedin.com
301,875 employees on LinkedIn®
(126)4.4 out of 5
Optimized for quick response
1st Easiest To Use in Text Analysis software
Save to My Lists
Entry Level Price:Contact Us
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Canvs AI is a the leading insights platform designed to transform open-ended consumer feedback into actionable business intelligence through advanced AI text analysis. This innovative solution empower

    Users
    No information available
    Industries
    • Market Research
    • Entertainment
    Market Segment
    • 37% Small-Business
    • 35% Enterprise
    User Sentiment
    How are these determined?Information
    These insights, currently in beta, are compiled from user reviews and grouped to display a high-level overview of the software.
    • Canvs AI is a tool for organizing qualitative data and providing AI chat box for specific questions.
    • Users like the speed and efficiency of Canvs AI in analyzing open-ended survey responses, its intuitive interface, and the support from Canvs AI representatives.
    • Reviewers mentioned issues with the user interface, inaccuracies in AI categorization into codes, and the platform's learning curve.
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Canvs AI Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    41
    Helpful
    28
    Insights Generation
    28
    Insights Analysis
    25
    AI Technology
    22
    Cons
    Inaccuracy
    11
    Lacking Features
    8
    Limitations
    8
    Poor Understanding
    7
    AI Inaccuracy
    5
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Canvs AI features and usability ratings that predict user satisfaction
    9.0
    Has the product been a good partner in doing business?
    Average: 8.9
    7.4
    Custom Extension
    Average: 8.2
    7.7
    Compositionality
    Average: 8.2
    7.5
    Pre-Built Parameterization
    Average: 8.4
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Canvs AI
    Company Website
    Year Founded
    2010
    HQ Location
    Manhattan, New York
    Twitter
    @canvsai
    2,754 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    36 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Canvs AI is a the leading insights platform designed to transform open-ended consumer feedback into actionable business intelligence through advanced AI text analysis. This innovative solution empower

Users
No information available
Industries
  • Market Research
  • Entertainment
Market Segment
  • 37% Small-Business
  • 35% Enterprise
User Sentiment
How are these determined?Information
These insights, currently in beta, are compiled from user reviews and grouped to display a high-level overview of the software.
  • Canvs AI is a tool for organizing qualitative data and providing AI chat box for specific questions.
  • Users like the speed and efficiency of Canvs AI in analyzing open-ended survey responses, its intuitive interface, and the support from Canvs AI representatives.
  • Reviewers mentioned issues with the user interface, inaccuracies in AI categorization into codes, and the platform's learning curve.
Canvs AI Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
41
Helpful
28
Insights Generation
28
Insights Analysis
25
AI Technology
22
Cons
Inaccuracy
11
Lacking Features
8
Limitations
8
Poor Understanding
7
AI Inaccuracy
5
Canvs AI features and usability ratings that predict user satisfaction
9.0
Has the product been a good partner in doing business?
Average: 8.9
7.4
Custom Extension
Average: 8.2
7.7
Compositionality
Average: 8.2
7.5
Pre-Built Parameterization
Average: 8.4
Seller Details
Seller
Canvs AI
Company Website
Year Founded
2010
HQ Location
Manhattan, New York
Twitter
@canvsai
2,754 Twitter followers
LinkedIn® Page
www.linkedin.com
36 employees on LinkedIn®

This is how G2 Deals can help you:

  • Easily shop for curated – and trusted – software
  • Own your own software buying journey
  • Discover exclusive deals on software
(169)4.5 out of 5
4th Easiest To Use in Text Analysis software
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    The Chattermill Customer Feedback Analytics Platform helps businesses unlock their customer reality and understand the voice of their customers. Using Chattermill, companies can unify their customer

    Users
    • Product Manager
    • Senior Product Manager
    Industries
    • Retail
    • Financial Services
    Market Segment
    • 50% Mid-Market
    • 42% Enterprise
    User Sentiment
    How are these determined?Information
    These insights, currently in beta, are compiled from user reviews and grouped to display a high-level overview of the software.
    • Chattermill is a customer feedback analysis tool that consolidates feedback from multiple channels and extracts actionable insights using AI.
    • Users frequently mention the intuitive dashboard, the ability to uncover trends, and the helpful customer support team as key benefits of using Chattermill.
    • Users experienced difficulties with the initial setup, the interface can feel busy, and the keyword search function could be improved for better accuracy.
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Chattermill Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    38
    Feedback Management
    25
    Customer Insights
    22
    Insights Analysis
    21
    Insights Generation
    20
    Cons
    Not Intuitive
    8
    Inaccuracy
    7
    Lacking Features
    7
    Steep Learning Curve
    7
    Complex Usability
    6
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Chattermill features and usability ratings that predict user satisfaction
    9.3
    Has the product been a good partner in doing business?
    Average: 8.9
    8.2
    Custom Extension
    Average: 8.2
    7.9
    Compositionality
    Average: 8.2
    8.2
    Pre-Built Parameterization
    Average: 8.4
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    2015
    HQ Location
    London
    Twitter
    @ChattermillAI
    468 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    78 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

The Chattermill Customer Feedback Analytics Platform helps businesses unlock their customer reality and understand the voice of their customers. Using Chattermill, companies can unify their customer

Users
  • Product Manager
  • Senior Product Manager
Industries
  • Retail
  • Financial Services
Market Segment
  • 50% Mid-Market
  • 42% Enterprise
User Sentiment
How are these determined?Information
These insights, currently in beta, are compiled from user reviews and grouped to display a high-level overview of the software.
  • Chattermill is a customer feedback analysis tool that consolidates feedback from multiple channels and extracts actionable insights using AI.
  • Users frequently mention the intuitive dashboard, the ability to uncover trends, and the helpful customer support team as key benefits of using Chattermill.
  • Users experienced difficulties with the initial setup, the interface can feel busy, and the keyword search function could be improved for better accuracy.
Chattermill Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
38
Feedback Management
25
Customer Insights
22
Insights Analysis
21
Insights Generation
20
Cons
Not Intuitive
8
Inaccuracy
7
Lacking Features
7
Steep Learning Curve
7
Complex Usability
6
Chattermill features and usability ratings that predict user satisfaction
9.3
Has the product been a good partner in doing business?
Average: 8.9
8.2
Custom Extension
Average: 8.2
7.9
Compositionality
Average: 8.2
8.2
Pre-Built Parameterization
Average: 8.4
Seller Details
Year Founded
2015
HQ Location
London
Twitter
@ChattermillAI
468 Twitter followers
LinkedIn® Page
www.linkedin.com
78 employees on LinkedIn®
(71)4.2 out of 5
15th Easiest To Use in Text Analysis software
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. Amazon Comprehend identifies the language of the text; extracts

    Users
    No information available
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 39% Mid-Market
    • 38% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Amazon Comprehend Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    3
    Integrations
    2
    Multilingual Support
    2
    Access
    1
    Automation
    1
    Cons
    Expensive
    3
    Steep Learning Curve
    2
    Complex Setup
    1
    Data Management
    1
    Data Privacy
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Amazon Comprehend features and usability ratings that predict user satisfaction
    8.1
    Has the product been a good partner in doing business?
    Average: 8.9
    7.9
    Custom Extension
    Average: 8.2
    8.5
    Compositionality
    Average: 8.2
    8.2
    Pre-Built Parameterization
    Average: 8.4
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    2006
    HQ Location
    Seattle, WA
    Twitter
    @awscloud
    2,230,610 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    136,383 employees on LinkedIn®
    Ownership
    NASDAQ: AMZN
Product Description
How are these determined?Information
This description is provided by the seller.

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. Amazon Comprehend identifies the language of the text; extracts

Users
No information available
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 39% Mid-Market
  • 38% Small-Business
Amazon Comprehend Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
3
Integrations
2
Multilingual Support
2
Access
1
Automation
1
Cons
Expensive
3
Steep Learning Curve
2
Complex Setup
1
Data Management
1
Data Privacy
1
Amazon Comprehend features and usability ratings that predict user satisfaction
8.1
Has the product been a good partner in doing business?
Average: 8.9
7.9
Custom Extension
Average: 8.2
8.5
Compositionality
Average: 8.2
8.2
Pre-Built Parameterization
Average: 8.4
Seller Details
Year Founded
2006
HQ Location
Seattle, WA
Twitter
@awscloud
2,230,610 Twitter followers
LinkedIn® Page
www.linkedin.com
136,383 employees on LinkedIn®
Ownership
NASDAQ: AMZN
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Leveraged by brands and academics alike, ATLAS.ti allows anyone to analyze data and uncover valuable insights – no matter which sector you work in. From basic analysis tasks to the most in-depth rese

    Users
    No information available
    Industries
    • Higher Education
    • Research
    Market Segment
    • 37% Small-Business
    • 34% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • ATLAS.ti Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    4
    Intuitive
    3
    Useful
    3
    Categorization
    2
    Customer Support
    2
    Cons
    Data Inaccuracy
    1
    Error Handling
    1
    Lacking Features
    1
    Limited Features
    1
    Limited Language Support
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • ATLAS.ti features and usability ratings that predict user satisfaction
    9.0
    Has the product been a good partner in doing business?
    Average: 8.9
    7.9
    Custom Extension
    Average: 8.2
    8.3
    Compositionality
    Average: 8.2
    7.9
    Pre-Built Parameterization
    Average: 8.4
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    1993
    HQ Location
    Berlin
    Twitter
    @ATLASti
    4,381 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    53 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Leveraged by brands and academics alike, ATLAS.ti allows anyone to analyze data and uncover valuable insights – no matter which sector you work in. From basic analysis tasks to the most in-depth rese

Users
No information available
Industries
  • Higher Education
  • Research
Market Segment
  • 37% Small-Business
  • 34% Mid-Market
ATLAS.ti Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
4
Intuitive
3
Useful
3
Categorization
2
Customer Support
2
Cons
Data Inaccuracy
1
Error Handling
1
Lacking Features
1
Limited Features
1
Limited Language Support
1
ATLAS.ti features and usability ratings that predict user satisfaction
9.0
Has the product been a good partner in doing business?
Average: 8.9
7.9
Custom Extension
Average: 8.2
8.3
Compositionality
Average: 8.2
7.9
Pre-Built Parameterization
Average: 8.4
Seller Details
Year Founded
1993
HQ Location
Berlin
Twitter
@ATLASti
4,381 Twitter followers
LinkedIn® Page
www.linkedin.com
53 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Speak is a no-code transcription and natural language processing platform that helps researchers and marketers extract valuable insights from media. Get professional and automated transcription, gen

    Users
    No information available
    Industries
    • Non-Profit Organization Management
    Market Segment
    • 88% Small-Business
    • 8% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Speak Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    17
    Transcription
    11
    Transcripts
    10
    Useful
    9
    Insights Analysis
    7
    Cons
    High Subscription Cost
    3
    Cost
    2
    Delays
    2
    Poor Interface Design
    2
    Pricing Issues
    2
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Speak features and usability ratings that predict user satisfaction
    10.0
    Has the product been a good partner in doing business?
    Average: 8.9
    9.2
    Custom Extension
    Average: 8.2
    8.9
    Compositionality
    Average: 8.2
    8.8
    Pre-Built Parameterization
    Average: 8.4
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Speak Ai
    Year Founded
    2019
    HQ Location
    Toronto, CA
    Twitter
    @speakai_co
    256 Twitter followers
    LinkedIn® Page
    linkedin.com
    6 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Speak is a no-code transcription and natural language processing platform that helps researchers and marketers extract valuable insights from media. Get professional and automated transcription, gen

Users
No information available
Industries
  • Non-Profit Organization Management
Market Segment
  • 88% Small-Business
  • 8% Mid-Market
Speak Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
17
Transcription
11
Transcripts
10
Useful
9
Insights Analysis
7
Cons
High Subscription Cost
3
Cost
2
Delays
2
Poor Interface Design
2
Pricing Issues
2
Speak features and usability ratings that predict user satisfaction
10.0
Has the product been a good partner in doing business?
Average: 8.9
9.2
Custom Extension
Average: 8.2
8.9
Compositionality
Average: 8.2
8.8
Pre-Built Parameterization
Average: 8.4
Seller Details
Seller
Speak Ai
Year Founded
2019
HQ Location
Toronto, CA
Twitter
@speakai_co
256 Twitter followers
LinkedIn® Page
linkedin.com
6 employees on LinkedIn®
By SAP
(512)4.3 out of 5
View top Consulting Services for SAP HANA Cloud
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    SAP HANA Cloud is a modern database-as-a-service (DBaaS) powering the next generation of intelligent data applications. SAP HANA Cloud offers a competitive edge by incorporating advanced machine learn

    Users
    • Consultant
    • SAP Consultant
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 64% Enterprise
    • 23% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • SAP HANA Cloud Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    13
    Analytics
    9
    Features
    9
    Cloud Computing
    8
    Data Analysis
    8
    Cons
    Expensive
    10
    Complexity
    8
    Learning Curve
    7
    Performance Issues
    6
    Complex Implementation
    5
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • SAP HANA Cloud features and usability ratings that predict user satisfaction
    8.5
    Has the product been a good partner in doing business?
    Average: 8.9
    10.0
    Custom Extension
    Average: 8.2
    10.0
    Compositionality
    Average: 8.2
    8.3
    Pre-Built Parameterization
    Average: 8.4
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    SAP
    Year Founded
    1972
    HQ Location
    Walldorf
    Twitter
    @SAP
    301,846 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    125,049 employees on LinkedIn®
    Ownership
    NYSE:SAP
Product Description
How are these determined?Information
This description is provided by the seller.

SAP HANA Cloud is a modern database-as-a-service (DBaaS) powering the next generation of intelligent data applications. SAP HANA Cloud offers a competitive edge by incorporating advanced machine learn

Users
  • Consultant
  • SAP Consultant
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 64% Enterprise
  • 23% Mid-Market
SAP HANA Cloud Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
13
Analytics
9
Features
9
Cloud Computing
8
Data Analysis
8
Cons
Expensive
10
Complexity
8
Learning Curve
7
Performance Issues
6
Complex Implementation
5
SAP HANA Cloud features and usability ratings that predict user satisfaction
8.5
Has the product been a good partner in doing business?
Average: 8.9
10.0
Custom Extension
Average: 8.2
10.0
Compositionality
Average: 8.2
8.3
Pre-Built Parameterization
Average: 8.4
Seller Details
Seller
SAP
Year Founded
1972
HQ Location
Walldorf
Twitter
@SAP
301,846 Twitter followers
LinkedIn® Page
www.linkedin.com
125,049 employees on LinkedIn®
Ownership
NYSE:SAP
By IBM
(163)4.2 out of 5
9th Easiest To Use in Text Analysis software
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    IBM Watson Studio on IBM Cloud Pak for Data is a leading data science and machine learning solution that helps enterprises accelerate AI-powered digital transformation. It allows businesses to scale t

    Users
    • Software Engineer
    • CEO
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 50% Enterprise
    • 29% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • IBM Watson Studio Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    7
    AI Capabilities
    4
    AI Integration
    4
    AI Technology
    4
    Features
    4
    Cons
    Expensive
    2
    Learning Curve
    2
    Limited Language Support
    2
    Limited Userbase
    2
    Poor Customer Support
    2
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • IBM Watson Studio features and usability ratings that predict user satisfaction
    8.0
    Has the product been a good partner in doing business?
    Average: 8.9
    8.1
    Custom Extension
    Average: 8.2
    9.3
    Compositionality
    Average: 8.2
    9.2
    Pre-Built Parameterization
    Average: 8.4
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    IBM
    Year Founded
    1911
    HQ Location
    Armonk, NY
    Twitter
    @IBM
    711,154 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    317,108 employees on LinkedIn®
    Ownership
    SWX:IBM
Product Description
How are these determined?Information
This description is provided by the seller.

IBM Watson Studio on IBM Cloud Pak for Data is a leading data science and machine learning solution that helps enterprises accelerate AI-powered digital transformation. It allows businesses to scale t

Users
  • Software Engineer
  • CEO
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 50% Enterprise
  • 29% Small-Business
IBM Watson Studio Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
7
AI Capabilities
4
AI Integration
4
AI Technology
4
Features
4
Cons
Expensive
2
Learning Curve
2
Limited Language Support
2
Limited Userbase
2
Poor Customer Support
2
IBM Watson Studio features and usability ratings that predict user satisfaction
8.0
Has the product been a good partner in doing business?
Average: 8.9
8.1
Custom Extension
Average: 8.2
9.3
Compositionality
Average: 8.2
9.2
Pre-Built Parameterization
Average: 8.4
Seller Details
Seller
IBM
Year Founded
1911
HQ Location
Armonk, NY
Twitter
@IBM
711,154 Twitter followers
LinkedIn® Page
www.linkedin.com
317,108 employees on LinkedIn®
Ownership
SWX:IBM
By IBM
(34)4.2 out of 5
10th Easiest To Use in Text Analysis software
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Analyze text to extract meta-data from content such as concepts, entities, keywords, categories, relations and semantic roles.

    Users
    No information available
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 56% Small-Business
    • 26% Enterprise
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • IBM Watson Natural Language Understanding Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    9
    Accuracy
    5
    User Interface
    4
    Customization
    3
    Functionality
    3
    Cons
    Complex Setup
    4
    Limitations
    2
    Complexity
    1
    Difficult Learning
    1
    Not User-Friendly
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • IBM Watson Natural Language Understanding features and usability ratings that predict user satisfaction
    8.6
    Has the product been a good partner in doing business?
    Average: 8.9
    0.0
    No information available
    0.0
    No information available
    0.0
    No information available
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    IBM
    Year Founded
    1911
    HQ Location
    Armonk, NY
    Twitter
    @IBM
    711,154 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    317,108 employees on LinkedIn®
    Ownership
    SWX:IBM
Product Description
How are these determined?Information
This description is provided by the seller.

Analyze text to extract meta-data from content such as concepts, entities, keywords, categories, relations and semantic roles.

Users
No information available
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 56% Small-Business
  • 26% Enterprise
IBM Watson Natural Language Understanding Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
9
Accuracy
5
User Interface
4
Customization
3
Functionality
3
Cons
Complex Setup
4
Limitations
2
Complexity
1
Difficult Learning
1
Not User-Friendly
1
IBM Watson Natural Language Understanding features and usability ratings that predict user satisfaction
8.6
Has the product been a good partner in doing business?
Average: 8.9
0.0
No information available
0.0
No information available
0.0
No information available
Seller Details
Seller
IBM
Year Founded
1911
HQ Location
Armonk, NY
Twitter
@IBM
711,154 Twitter followers
LinkedIn® Page
www.linkedin.com
317,108 employees on LinkedIn®
Ownership
SWX:IBM
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Organizations face increasing demands for high-powered analytics that produce fast, trustworthy results. Whether it’s providing teams of data scientists with advanced machine learning capabilities or

    Users
    • Statistical Programmer
    • Biostatistician
    Industries
    • Pharmaceuticals
    • Banking
    Market Segment
    • 34% Enterprise
    • 33% Mid-Market
    User Sentiment
    How are these determined?Information
    These insights, currently in beta, are compiled from user reviews and grouped to display a high-level overview of the software.
    • SAS Viya is a data analysis platform that allows users to switch between low-code/no-code and hands-on coding to engineer, model, and analyze data.
    • Reviewers appreciate SAS Viya's ability to handle big data, its user-friendly interface, its integration with open-source languages like Python, R, and Java, and its efficient automation of programming tasks.
    • Users mentioned that SAS Viya has a steep learning curve, can be expensive compared to open-source alternatives, may require significant infrastructure for optimal performance, and lacks the flexibility of open-source tools for highly customized solutions.
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • SAS Viya Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    269
    Features
    167
    Analytics
    136
    Data Analysis
    112
    Performance Efficiency
    108
    Cons
    Learning Curve
    116
    Learning Difficulty
    106
    Complexity
    102
    Difficult Learning
    83
    Expensive
    82
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • SAS Viya features and usability ratings that predict user satisfaction
    8.0
    Has the product been a good partner in doing business?
    Average: 8.9
    7.7
    Custom Extension
    Average: 8.2
    8.0
    Compositionality
    Average: 8.2
    8.0
    Pre-Built Parameterization
    Average: 8.4
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Company Website
    Year Founded
    1976
    HQ Location
    Cary, NC
    Twitter
    @SASsoftware
    62,434 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    17,268 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Organizations face increasing demands for high-powered analytics that produce fast, trustworthy results. Whether it’s providing teams of data scientists with advanced machine learning capabilities or

Users
  • Statistical Programmer
  • Biostatistician
Industries
  • Pharmaceuticals
  • Banking
Market Segment
  • 34% Enterprise
  • 33% Mid-Market
User Sentiment
How are these determined?Information
These insights, currently in beta, are compiled from user reviews and grouped to display a high-level overview of the software.
  • SAS Viya is a data analysis platform that allows users to switch between low-code/no-code and hands-on coding to engineer, model, and analyze data.
  • Reviewers appreciate SAS Viya's ability to handle big data, its user-friendly interface, its integration with open-source languages like Python, R, and Java, and its efficient automation of programming tasks.
  • Users mentioned that SAS Viya has a steep learning curve, can be expensive compared to open-source alternatives, may require significant infrastructure for optimal performance, and lacks the flexibility of open-source tools for highly customized solutions.
SAS Viya Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
269
Features
167
Analytics
136
Data Analysis
112
Performance Efficiency
108
Cons
Learning Curve
116
Learning Difficulty
106
Complexity
102
Difficult Learning
83
Expensive
82
SAS Viya features and usability ratings that predict user satisfaction
8.0
Has the product been a good partner in doing business?
Average: 8.9
7.7
Custom Extension
Average: 8.2
8.0
Compositionality
Average: 8.2
8.0
Pre-Built Parameterization
Average: 8.4
Seller Details
Company Website
Year Founded
1976
HQ Location
Cary, NC
Twitter
@SASsoftware
62,434 Twitter followers
LinkedIn® Page
www.linkedin.com
17,268 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    The software combines machine-learning methods with a rules-based approach that's essential for understanding the subtle nuances of language and inferring intention.

    Users
    • Inside Sales Manager
    Industries
    • Computer Software
    Market Segment
    • 72% Enterprise
    • 19% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • SAS Visual Text Analytics Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Analytics
    1
    Ease of Use
    1
    Cons
    Difficulty in Adjustments
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • SAS Visual Text Analytics features and usability ratings that predict user satisfaction
    8.1
    Has the product been a good partner in doing business?
    Average: 8.9
    8.0
    Custom Extension
    Average: 8.2
    8.3
    Compositionality
    Average: 8.2
    8.1
    Pre-Built Parameterization
    Average: 8.4
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    1976
    HQ Location
    Cary, NC
    Twitter
    @SASsoftware
    62,434 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    17,268 employees on LinkedIn®
    Phone
    1-800-727-0025
Product Description
How are these determined?Information
This description is provided by the seller.

The software combines machine-learning methods with a rules-based approach that's essential for understanding the subtle nuances of language and inferring intention.

Users
  • Inside Sales Manager
Industries
  • Computer Software
Market Segment
  • 72% Enterprise
  • 19% Small-Business
SAS Visual Text Analytics Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Analytics
1
Ease of Use
1
Cons
Difficulty in Adjustments
1
SAS Visual Text Analytics features and usability ratings that predict user satisfaction
8.1
Has the product been a good partner in doing business?
Average: 8.9
8.0
Custom Extension
Average: 8.2
8.3
Compositionality
Average: 8.2
8.1
Pre-Built Parameterization
Average: 8.4
Seller Details
Year Founded
1976
HQ Location
Cary, NC
Twitter
@SASsoftware
62,434 Twitter followers
LinkedIn® Page
www.linkedin.com
17,268 employees on LinkedIn®
Phone
1-800-727-0025
(146)4.5 out of 5
12th Easiest To Use in Text Analysis software
View top Consulting Services for Dovetail
Save to My Lists
Entry Level Price:Free
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Dovetail is an AI-first insights hub designed to help organizations centralize and transform scattered customer feedback into actionable insights. This innovative software solution streamlines the pro

    Users
    • Product Designer
    • UX Researcher
    Industries
    • Computer Software
    • Information Technology and Services
    Market Segment
    • 47% Mid-Market
    • 27% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Dovetail Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    102
    Features
    70
    Useful
    46
    Time-saving
    43
    Insights
    41
    Cons
    Missing Features
    34
    Limitations
    30
    Inefficient Tagging
    26
    Complexity
    21
    Lacking Features
    20
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Dovetail features and usability ratings that predict user satisfaction
    9.1
    Has the product been a good partner in doing business?
    Average: 8.9
    4.2
    Custom Extension
    Average: 8.2
    4.7
    Compositionality
    Average: 8.2
    4.9
    Pre-Built Parameterization
    Average: 8.4
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Company Website
    Year Founded
    2017
    HQ Location
    Sydney, Australia
    Twitter
    @hidovetail
    2,167 Twitter followers
    LinkedIn® Page
    au.linkedin.com
    181 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Dovetail is an AI-first insights hub designed to help organizations centralize and transform scattered customer feedback into actionable insights. This innovative software solution streamlines the pro

Users
  • Product Designer
  • UX Researcher
Industries
  • Computer Software
  • Information Technology and Services
Market Segment
  • 47% Mid-Market
  • 27% Small-Business
Dovetail Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
102
Features
70
Useful
46
Time-saving
43
Insights
41
Cons
Missing Features
34
Limitations
30
Inefficient Tagging
26
Complexity
21
Lacking Features
20
Dovetail features and usability ratings that predict user satisfaction
9.1
Has the product been a good partner in doing business?
Average: 8.9
4.2
Custom Extension
Average: 8.2
4.7
Compositionality
Average: 8.2
4.9
Pre-Built Parameterization
Average: 8.4
Seller Details
Company Website
Year Founded
2017
HQ Location
Sydney, Australia
Twitter
@hidovetail
2,167 Twitter followers
LinkedIn® Page
au.linkedin.com
181 employees on LinkedIn®
(37)4.4 out of 5
8th Easiest To Use in Text Analysis software
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Lumoa is the first CX platform to offer GPT. In the past, companies used to spend weeks collecting, analyzing, interpreting, and reporting on customer feedback from multiple sources. Now, every empl

    Users
    No information available
    Industries
    • Financial Services
    • Telecommunications
    Market Segment
    • 62% Enterprise
    • 24% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Lumoa Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    25
    Helpful
    16
    Customer Support
    15
    Insights Generation
    14
    Insights Analysis
    13
    Cons
    Limitations
    5
    AI Limitations
    4
    Data Management
    4
    Filtering Issues
    4
    Poor Interface Design
    4
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Lumoa features and usability ratings that predict user satisfaction
    8.7
    Has the product been a good partner in doing business?
    Average: 8.9
    7.0
    Custom Extension
    Average: 8.2
    6.8
    Compositionality
    Average: 8.2
    7.3
    Pre-Built Parameterization
    Average: 8.4
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Lumoa
    Year Founded
    2016
    HQ Location
    Helsinki, Finland
    Twitter
    @LumoaMe
    1,281 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    25 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Lumoa is the first CX platform to offer GPT. In the past, companies used to spend weeks collecting, analyzing, interpreting, and reporting on customer feedback from multiple sources. Now, every empl

Users
No information available
Industries
  • Financial Services
  • Telecommunications
Market Segment
  • 62% Enterprise
  • 24% Mid-Market
Lumoa Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
25
Helpful
16
Customer Support
15
Insights Generation
14
Insights Analysis
13
Cons
Limitations
5
AI Limitations
4
Data Management
4
Filtering Issues
4
Poor Interface Design
4
Lumoa features and usability ratings that predict user satisfaction
8.7
Has the product been a good partner in doing business?
Average: 8.9
7.0
Custom Extension
Average: 8.2
6.8
Compositionality
Average: 8.2
7.3
Pre-Built Parameterization
Average: 8.4
Seller Details
Seller
Lumoa
Year Founded
2016
HQ Location
Helsinki, Finland
Twitter
@LumoaMe
1,281 Twitter followers
LinkedIn® Page
www.linkedin.com
25 employees on LinkedIn®
(497)4.6 out of 5
Optimized for quick response
6th Easiest To Use in Text Analysis software
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Altair AI Studio (formerly RapidMiner Studio) is a data science tool that anyone can use to design and prototype highly explainable AI and machine learning models that help build trust throughout an o

    Users
    • Student
    • Data Scientist
    Industries
    • Higher Education
    • Education Management
    Market Segment
    • 43% Small-Business
    • 30% Enterprise
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Altair AI Studio Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    4
    Data Visualization
    3
    Intuitive
    3
    AI Capabilities
    2
    AI Technology
    2
    Cons
    Lacking Features
    2
    Missing Features
    2
    Accuracy Issues
    1
    Difficult Customization
    1
    Expensive
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Altair AI Studio features and usability ratings that predict user satisfaction
    8.8
    Has the product been a good partner in doing business?
    Average: 8.9
    8.3
    Custom Extension
    Average: 8.2
    7.5
    Compositionality
    Average: 8.2
    8.3
    Pre-Built Parameterization
    Average: 8.4
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Altair
    Company Website
    Year Founded
    1985
    HQ Location
    Troy, MI
    Twitter
    @Altair_Inc
    7,334 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    4,102 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Altair AI Studio (formerly RapidMiner Studio) is a data science tool that anyone can use to design and prototype highly explainable AI and machine learning models that help build trust throughout an o

Users
  • Student
  • Data Scientist
Industries
  • Higher Education
  • Education Management
Market Segment
  • 43% Small-Business
  • 30% Enterprise
Altair AI Studio Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
4
Data Visualization
3
Intuitive
3
AI Capabilities
2
AI Technology
2
Cons
Lacking Features
2
Missing Features
2
Accuracy Issues
1
Difficult Customization
1
Expensive
1
Altair AI Studio features and usability ratings that predict user satisfaction
8.8
Has the product been a good partner in doing business?
Average: 8.9
8.3
Custom Extension
Average: 8.2
7.5
Compositionality
Average: 8.2
8.3
Pre-Built Parameterization
Average: 8.4
Seller Details
Seller
Altair
Company Website
Year Founded
1985
HQ Location
Troy, MI
Twitter
@Altair_Inc
7,334 Twitter followers
LinkedIn® Page
www.linkedin.com
4,102 employees on LinkedIn®
(40)4.8 out of 5
Optimized for quick response
11th Easiest To Use in Text Analysis software
Save to My Lists
Entry Level Price:$25,000.00
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Thematic uses AI to deliver layers of insights from feedback across channels, to help companies improve customer experiences, reduce churn and save costs. Powered by cutting-edge AI with human in the

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 53% Enterprise
    • 30% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Thematic Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    6
    Customer Support
    4
    Helpful
    3
    Insights Generation
    3
    Customer Insights
    2
    Cons
    This product has not yet received any negative sentiments.
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Thematic features and usability ratings that predict user satisfaction
    9.9
    Has the product been a good partner in doing business?
    Average: 8.9
    2.5
    Custom Extension
    Average: 8.2
    0.0
    Compositionality
    Average: 8.2
    7.2
    Pre-Built Parameterization
    Average: 8.4
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Thematic
    Company Website
    Year Founded
    2016
    HQ Location
    San Francisco, CA
    Twitter
    @getthematic
    489 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    38 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Thematic uses AI to deliver layers of insights from feedback across channels, to help companies improve customer experiences, reduce churn and save costs. Powered by cutting-edge AI with human in the

Users
No information available
Industries
No information available
Market Segment
  • 53% Enterprise
  • 30% Mid-Market
Thematic Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
6
Customer Support
4
Helpful
3
Insights Generation
3
Customer Insights
2
Cons
This product has not yet received any negative sentiments.
Thematic features and usability ratings that predict user satisfaction
9.9
Has the product been a good partner in doing business?
Average: 8.9
2.5
Custom Extension
Average: 8.2
0.0
Compositionality
Average: 8.2
7.2
Pre-Built Parameterization
Average: 8.4
Seller Details
Seller
Thematic
Company Website
Year Founded
2016
HQ Location
San Francisco, CA
Twitter
@getthematic
489 Twitter followers
LinkedIn® Page
www.linkedin.com
38 employees on LinkedIn®

Learn More About Text Analysis Software

What is Text Analysis Software?

Text analysis software helps businesses analyze their text data using natural language understanding, which is a subset of natural language processing. Because of the unstructured nature of text data, these analytics solutions take text as an input and provide some form of labels, tags, or insights as an input. In the age of digital transformation, businesses are embracing the need to understand company data like never before. 

Text analysis software, also known as text mining software or text analytics software, has become an important tool for nearly every business over the past decade. A more recent aspect of analytics and business intelligence is the need to understand not just structured data, but unstructured data as well. Unstructured data, such as text data, can be mined for meaning to inform business decisions. 

Text mining initiatives can help businesses ultimately better understand textual data sets. Being able to pull out actionable insights from numerical data housed in ERP systems, CRM software, or accounting software is one thing, but being able to gain insights from unstructured data sources is invaluable. Without dedicated software for this task, businesses must either spend significant time and resources on building natural language understanding models or haphazardly investigating the data.

What Types of Text Analysis Software Exist?

Many types of text analysis solutions share overlapping functionality, while simultaneously catering to different user personas like data analysts and financial analysts, or providing unique services.

Some solutions may offer self-service features so that the average employee can assemble their charts and graphs from big data sets. Others, however, require more significant support from IT or data analysts.

Self-service text analysis tools

Self-service text analysis tools do not require coding knowledge, so end users with limited to no coding knowledge can take advantage of them for data needs. This enables business users like sales representatives, human resource managers, marketers, and other non-data team members to make decisions based on relevant business data. Self-service solutions often provide drag-and-drop functionality for tagging text, prebuilt templates for querying data, and other tools for data discovery. Similar to analytics platforms, organizations use these tools to build interactive dashboards for discovering actionable insights.

For example, a customer service business leader might use this type of software to analyze thousands of customer emails to discover trends, such as sentiment and the choice of words they used. This analysis can inform how customer service agents respond to customers to achieve desired outcomes.

Traditional text analysis tools

As opposed to self-service options, some text analysis solutions are geared towards data professionals, such as data analysts and data scientists. They can use this software to train and deploy algorithms, as it assists them in tagging their data. Data scientists can use these tools to ingest text data, such as social media, call center transcriptions, news sources, and reviews, and to build and improve applications, achieving goals such as improving fraud detection and conducting sentiment analysis.

What are the Common Features of Text Analysis Software?

Many capabilities of text analysis software can help users pull business-critical insights from text data.

Language identification: Text analytics solutions provide users with the ability to understand which language the text was written in. This can be beneficial when determining where a social media post came from or when a business has offices in multiple countries.

Part of speech tagging: Once the language is identified, text analysis software can tag each word with a part of speech, signifying if the word is a noun, verb, adjective, and so on.

Syntax parsing: Syntax parsing is very similar to part of speech tagging, but instead of understanding each word, it helps break down how a sentence was constructed and why.

Entity recognition: Text analytics solutions can help determine not just parts of speech but actual entities. For example, the part of speech may be a noun, but text analytics will break down whether that noun is a person or a place.

Keyphrase extraction: Another major feature of text mining and text analytics is keyphrase extraction, which allows users to determine patterns and themes within the text. These tools can pull out those common themes for the user.

Sentiment analysis: All of the above features can be relevant for sentiment analysis. Text analysis tools can offer up sentiment analysis scores, determining if the text is positive, negative, happy, sad, or neutral, among many other classifications. With the sentiment determined, businesses can decide how they want to act or interact with this data. For example, if a software company sees that all of their negative reviews are mentioning one particular feature, it might be a good idea to examine the state or viability of that feature.

What are the Benefits of Text Analysis Software?

The reason to use text analysis software is rather straightforward—users need to analyze text—but there are many reasons behind why a business may want to perform text mining and analysis. It all boils down to better understanding and utilizing company data to impact business processes and the bottom line. It should be used to increase efficiency and productivity and to optimize processes that could be working better.

Sentiment understanding: Businesses are always trying to gauge customer satisfaction, and text analytics is an easy way to do so. Many different text data sources can provide customer sentiments, such as social media, emails from customers, phone transcripts, customer reviews, and others. If a company can understand their shortcomings or where they are excelling with customers, they can better support and manage those customers. Ultimately this can lead to increased revenue.

Employee satisfaction: Similarly to better understanding customers, businesses can improve employee engagement and satisfaction by using text analysis. While businesses shouldn’t necessarily spy on their employees, they can figure out employee sentiment and satisfaction based on surveys, emails, or phone transcripts. This can help businesses ensure that they are promoting the right company culture and providing a healthy and happy place to work.

Survey analysis: Text analysis is very often used when companies are running surveys. These surveys may be intended for customers or employees but can also relate to market research. Being able to quickly pull insights verbatim from survey responses can provide a unique perspective and insight that businesses may not be able to obtain through multiple-choice questions.

Document classification: An easy use case for text analysis software is document classification. Businesses often need to organize existing documents; by pulling out sentiment and themes, it can be much easier to bucket documents, such as invoices and contracts.

Who Uses Text Analysis Software?

The typical user of text analytics is the same person who is tasked with using analytics and business intelligence solutions—a data analyst or data scientist. These users are trained in developing analytical and machine learning models used to pull out actionable insights from data. Data scientists are also tasked with deriving a business narrative from data, and text data is no different. If the text analytics product is of the self-service variety, less technical business users, such as operations, customer service, and finance teams can benefit from the technology to dig into their text data and derive insights. 

Data analysts: Depending on the complexity of the software, analysts may be required. They can help set up the requisite tagging of the text data and dashboards for other employees and teams. They can create complex queries inside the platforms to gather a deeper understanding of business-critical data. 

Operations and supply chain teams: A company’s supply chain frequently has many touchpoints, and as a result, many data points. Everything from invoices to shipping information can be analyzed with this software. Therefore, employees working in operations and supply chain teams can use text analysis software to gain a better understanding of their departments and the text data that is generated, such as from ERP systems. These applications track everything from accounting to supply chain and distribution. By inputting supply chain data into this software, supply chain managers can optimize several processes to save time and resources.

Finance teams: Finance teams leverage text analysis software to gain insight and understanding into the factors that impact an organization's bottom line. Through integrations with financial systems such as accounting software, employees such as chief financial officers (CFOs) can see how well the business is performing. For example, they can analyze free-text data in expense reports to discover trends in the data. With this knowledge, they can determine the biggest spenders and spending categories and put a plan in place to curb spending, if desired.

Sales and marketing teams: Sales teams also seek to improve financial metrics and can benefit tremendously from being more data driven. They can obtain insights into prospective accounts, sales performance, and pipeline forecasting, among many other use cases. Using analytics tools in a sales team can help businesses optimize their sales processes and influence revenue. Through the analysis of survey data, business leaders can find out the most effective way to sell products.

For marketing teams, tracking the performance of campaigns is key. Since they run different types of campaigns, including email marketing, digital advertising, or even traditional advertising campaigns, these tools allow marketing teams to track the performance of those campaigns in one central location. Marketers can learn about how their audience is responding to their messages using sentiment analysis. In addition, they can evaluate their ad copy by tagging and classifying it to better understand what drives conversions.

Consultants: Businesses do not always have the luxury to build, develop, and optimize their analytics solutions. Some businesses opt to employ external consultants, such as business intelligence (BI) consulting providers. These providers seek to understand a business and its goals, interpret data, and offer advice to ensure goals are met. BI consultants frequently have industry-specific knowledge alongside their technical backgrounds, with experience in healthcare, business, and other fields. 

Customer service teams: Customer service teams are faced with a challenge. They are frequently inundated with a flurry of customer concerns, whether that be via text, voice, or mail. Although agents can respond to each comment and concern individually, it is beneficial to have a proper understanding of trends, including the sentiment of messages, the types of complaints, and more. Using text analysis software, businesses can equip their agents with tools to help them respond to messages in a targeted manner, depending on factors such as sentiment and key phrases.

What are the Alternatives to Text Analysis Software?

Alternatives to text analysis software can replace this type of software, either partially or completely:

Feedback analytics software: Text analysis software is an all-purpose solution built to analyze any text data. Businesses looking to focus on feedback text, such as from surveys, review sites, social media, and customer service tools, can leverage feedback analytics software to achieve this goal. This software enables businesses to consolidate and analyze their customer feedback within a single platform.

Software Related to Text Analysis Software

Related solutions that can be used together with text analysis software include:

Data warehouse software: Most companies have a large number of disparate data sources, so to best integrate all their data, they implement a data warehouse. Data warehouses can house data from multiple databases and business applications, which allows BI and analytics tools to pull all company data from a single repository. This organization is critical to the quality of the data that is ingested by analytics software.

Data preparation software: A key software necessary for easy data analysis is a data preparation tool and other related data management tools. These solutions allow users to discover, combine, clean and enrich data for simple analysis. Data preparation tools are often used by IT teams or data analysts tasked with using text analysis tools. Some text analysis platforms offer data preparation features, but businesses with a wide range of data sources often opt for a dedicated preparation tool.

Analytics platforms: Analytics platforms might include some limited text analysis features, but are broader-focused tools that facilitate the following five elements: data preparation, data modeling, data blending, data visualization, and insights delivery.

Stream analytics software: When one is looking for tools specifically geared toward analyzing data in real time, stream analytics software is a go-to solution. These tools help users analyze data in transfer through APIs, between applications, and more. This software can be helpful with the internet of things (IoT) data, which people usually want to analyze in real time.

Predictive analytics software: Broad-purpose text analysis software allows businesses to conduct various forms of analysis, such as prescriptive, descriptive, and predictive. Businesses that are focused on looking at their past and present data to predict future outcomes can use predictive analytics software for a more fine-tuned solution. 

Challenges with Text Analysis Software

Software solutions can come with their own set of challenges. 

Need for skilled employees: The main issue with text analysis software is that, despite the tool pulling information surrounding text data, it still requires a human to go that extra mile and determine what the data means. Without context, sentiment analysis, phrase tagging, and pulling themes or patterns from a text can only inform a user so much. An analyst will need to interpret that data and decipher the business implications of it. 

This is much more easily tackled with text analysis software because of the ability to visualize the data in an organized manner, but it still requires interpretation nonetheless. Some text analytics tools may offer a certain level of predictive analytics and provide users with suggestions or recommendations based on the data, but more often than not, human intervention is necessary.

Data preparation: Another potential concern is preparing the data to be ingested by the text analysis tool. The data needs to be stored properly, whether that is in a database or data warehouse and may require IT or a dedicated admin to ensure the text analytics tool can consume the data. The beauty of text analysis software is that it doesn’t always require the neatness of structured data. Unstructured data does not need to follow a columnar approach that structured data often requires.

User adoption: It is not always easy to transform a business into a data-driven company. Particularly at more established companies that have done things the same way for years, it is not simple to force analytics tools upon employees, especially if there are ways for them to avoid it. If there are other options, such as spreadsheets or existing tools that employees can use instead of analytics software, they will most likely go that route. However, if managers and leaders ensure that analytics tools are a necessity in an employee’s day to day, then adoption rates will increase.

Which Companies Should Buy Text Analysis Software?

As it has often been said, data is the fuel that drives modern businesses. Although it is cliche, it no doubt has truth to it. Therefore, businesses across the globe and industries should consider some sort of analytics solution, such as text analysis to make sense of that data and begin to make data-driven decisions. Here are some illustrative examples of how textual analysis can be used in several industries:

Financial services: Within financial institutions, such as insurance brokerages, banks, and credit unions, it is common for a host of different systems to be used. These companies have data ranging from customer records, to transactions, to market data, and more. With the proliferation of systems comes more data. With a robust analytics solution in place, they can get a better understanding of the data that is being produced from the various systems across the business. As an industry that is heavily regulated, users can benefit from governed access capabilities which can be particularly beneficial, since it can assist in auditing company processes.

Healthcare: Within the space of healthcare, bad data practices might have dire or even deadly consequences. Text analysis software can help these organizations with having an overarching view of their data, such as patient records, insurance claims, finances, and more. Through the implementation of analytics, healthcare companies can lower risk and costs, and make their billing and collections smarter.

Retail: Retail organizations, whether they’re B2C, B2B, D2C, or others, rely on data to make informed decisions. For example, a seller of printers, to run a successful business, must keep track of many things such as their inventory, sales, their sales team, and returns. If all of this data is kept siloed within different systems, there is no single source of truth and departments cannot have a conversation around the actual state of the business’ data. With Text analysis software set up and connected to all of the relevant data sources, any retail business can see benefits and make meaningful data-driven decisions.

How to Buy Text Analysis Software

Requirements Gathering (RFI/RFP) for Text Analysis Software

If a company is just starting out on its analytics journey, G2.com can help in selecting the best software for the particular company and use case. Since the particular solution might vary based on company size and industry, G2.com is a great place to sort and filter reviews based on these criteria, along with many more. The variety, volume, and velocity of data are vast. Therefore, users should think about how the particular solution fits their particular needs and their future needs as they accumulate more data. 

To find the right solution, buyers should determine pain points and jot them down. These should be used to help create a checklist of criteria. Additionally, the buyer must determine the number of employees who will need to use this software, as this drives the number of licenses they are likely to buy. Taking a holistic overview of the business and identifying pain points can help the team springboard into creating a checklist of criteria. The checklist serves as a detailed guide that includes both necessary and nice-to-have features including budget features, number of users, integrations, security requirements, cloud or on-premises solutions, and more.

Depending on the scope of the deployment, it might be helpful to produce a request for information (RFI), a one-page list with a few bullet points describing what is needed from a text analysis software.

Compare Text Analysis Software Products

Create a long list

From meeting the business functionality needs to implementation, vendor evaluations are an essential part of the software buying process. For ease of comparison after all demos are complete, it helps to prepare a consistent list of questions regarding specific needs and concerns to ask each vendor.

Create a short list

From the long list of vendors, it is helpful to narrow down the list and come up with a shorter list of contenders, preferably no more than three to five. With this list in hand, businesses can produce a matrix to compare the features and pricing of the various solutions.

Conduct demos

To ensure the comparison is thoroughgoing, the user should demo each solution on the shortlist with the same use case and data sets. This will allow the business to evaluate like for like and see how each vendor stacks up against the competition. 

Selection of Text Analysis Software

Choose a selection team

As text analysis software is all about the data, the user must make sure that the selection process is data driven as well. The selection team should compare notes, facts, and figures which they noted during the process, such as time to insight, number of visualizations, and availability of advanced analytics capabilities.

Negotiation

Just because something is written on a company’s pricing page, does not mean it is not negotiable (although some companies will not budge). It is imperative to open up a conversation regarding pricing and licensing. For example, the vendor may be willing to give a discount for multi-year contracts or for recommending the product to others.

Final decision

After this stage, and before going all in, it is recommended to roll out a test run or pilot program to test adoption with a small sample size of users. If the tool is well used and well received, the buyer can be confident that the selection was correct. If not, it might be time to go back to the drawing board.

What Does Text Analysis Software Cost?

Businesses decide to deploy text analysis software to derive some degree of a return on investment (ROI).

Return on Investment (ROI)

As businesses look to recoup the funds they spent on the software, it is critical to understand the costs associated with it. As mentioned above, this software is typically billed per user, which is sometimes tiered depending on the company size. More users will typically translate into more licenses, which means more money.

Users must consider how much is spent and compare that to what is gained, both in terms of efficiency as well as revenue. Therefore, businesses can compare processes between pre and post-deployment of the software to better understand how processes have been improved and how much time has been saved. They can even produce a case study (either for internal or external purposes) to demonstrate their gains from their use of the text analysis software.

Implementation of Text Analysis Software

How is Text Analysis Software Implemented?

Implementation differs drastically depending on the complexity and scale of the data. In organizations with vast amounts of data in disparate sources (e.g., applications, databases, etc.), it is often wise to utilize an external party, whether it’s an implementation specialist from the vendor or a third-party consultancy. With vast experience, they can help businesses understand how to connect and consolidate their data sources and how to use the software efficiently and effectively.

Who is Responsible for Text Analysis Software Implementation?

It may require a lot of people, or even teams, to properly deploy an analytics platform. This is because data can cut across teams and functions. As a result, one person or even one team rarely has a full understanding of all of a company’s data assets. With a cross-functional team in place, a business can piece together its data and begin the journey of analytics, starting with proper data preparation and management.