# Best Text Analysis Software - Page 2

  *By [Bijou Barry](https://research.g2.com/insights/author/bijou-barry)*

   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](https://www.g2.com/categories/natural-language-processing-nlp) and [machine learning](https://www.g2.com/categories/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](https://www.g2.com/categories/big-data-analytics) and [business intelligence platforms](https://www.g2.com/categories/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




  ## How Many Text Analysis Software Products Does G2 Track?
**Total Products under this Category:** 188

  
## How Does G2 Rank Text Analysis Software Products?

**Why You Can Trust G2's Software Rankings:**

- 30 Analysts and Data Experts
- 5,200+ Authentic Reviews
- 188+ Products
- Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.

  
## Which Text Analysis Software Is Best for Your Use Case?

- **Leader:** [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews)
- **Highest Performer:** [Canvs](https://www.g2.com/products/canvs-ai-canvs/reviews)
- **Easiest to Use:** [Kimola](https://www.g2.com/products/kimola/reviews)
- **Top Trending:** [Unwrap.ai](https://www.g2.com/products/unwrap-ai/reviews)
- **Best Free Software:** [Altair AI Studio](https://www.g2.com/products/rapidminer-studio/reviews)

  
---

**Sponsored**

### Blix

Blix offers an AI-powered text analysis solution designed to retrieve insights from customer feedback quickly and effortlessly. The platform automates the process of coding survey open ends, online reviews, and other textual feedback, turning them into insights without the need for manual effort. Blix’s automated topic discovery scans through open text feedback and identifies key themes and topics. Its AI-powered coding transforms unstructured text into structured, quantitative data, eliminating the need for manual coding. Users receive automated reports and summaries. The platform supports multiple languages and offers data encryption and strict confidentiality guarantees.



[Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list&secure%5Bcategory_id%5D=1260&secure%5Bdisplayable_resource_id%5D=1260&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=1260&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=1393471&secure%5Bresource_id%5D=1260&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Ftext-analysis%3Fiframe%3Dyes&secure%5Btoken%5D=1033eb9c1d5ff27854fc08e1ba1dcaf217244b0b6eb8a88370b11c7254fc0393&secure%5Burl%5D=https%3A%2F%2Fblix.ai&secure%5Burl_type%5D=company_website)

---

  ## What Are the Top-Rated Text Analysis Software Products in 2026?
### 1. [EdgeTier](https://www.g2.com/products/edge-tier-edgetier/reviews)
  The EdgeTier Conversational Intelligence and Support Platform helps Customer Support teams uncover the missed insights in their support and survey messages, react faster to emerging customer issues, and have the data they need at their fingertips to make decisions, positioning the contact centre as a strategic hub of insights for the entire company. Global Brands like Abercrombie & Fitch, CarTrawler, TUI Travel, and Ryanair use EdgeTier to process millions of customer messages, boost NPS, CSAT and first contact resolution scores, as well as improve overall efficiency. Having 24/7 insights into customer attitudes, helps you understand customer issues, detect emerging conversational trends in real time, and improve agent performance. Key functionality: - Proactive AI alerting with real time detection of unforeseen customer issues - Automatic tagging of customer messages and surveys - Get real-time alerts for critical customer interactions (set up in advance) - Sentiment analysis of all your customer and agent interactions - Agent performance reports and analysis - Real-time reporting and KPI analysis - AI assisted chat and email handling EdgeTier seamlessly integrates with existing customer support systems without needing any IT time, and monitors customer conversations 24/7 in multilingual environments, as well as providing prompts to support agents speaking to customers.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 30
**How Do G2 Users Rate EdgeTier?**

- **Has the product been a good partner in doing business?:** 9.3/10 (Category avg: 9.0/10)
- **Custom Extension:** 7.5/10 (Category avg: 8.1/10)
- **Compositionality:** 10.0/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 9.2/10 (Category avg: 8.3/10)

**Who Is the Company Behind EdgeTier?**

- **Seller:** [Edge Tier](https://www.g2.com/sellers/edge-tier)
- **Year Founded:** 2015
- **HQ Location:** Dublin 2, IE
- **LinkedIn® Page:** https://www.linkedin.com/company/11092892 (79 employees on LinkedIn®)

**Who Uses This Product?**
  - **Top Industries:** Gambling & Casinos
  - **Company Size:** 50% Enterprise, 30% Mid-Market


#### What Are EdgeTier's Pros and Cons?

**Pros:**

- Ease of Use (15 reviews)
- Insights Analysis (9 reviews)
- Helpful (7 reviews)
- Accuracy (6 reviews)
- Analytics (6 reviews)

**Cons:**

- Inaccurate Data Analysis (6 reviews)
- Accuracy Issues (5 reviews)
- Data Inaccuracy (4 reviews)
- Inaccuracy (4 reviews)
- Complexity (3 reviews)

### 2. [Wordnerds](https://www.g2.com/products/wordnerds/reviews)
  Wordnerds is a UK-based SaaS company whose mission is to teach computers to read—and genuinely understand—language. 80% of the world’s data exists in the form of unstructured text. Big businesses are bombarded daily by millions of tweets, emails, webchats, online reviews, survey results, CRM-entries, news articles and forum posts written by, for and about them. But language is weird, unpredictable, colloquial, fluid, sarcastic and entirely dependent on context. It’s hard to make sense of and, for most organisations, totally invisible. Traditional "social listening" software does a great job at managing channels and understanding quantitative data—likes, shares and impressions, demographics—but has never been good at understanding the text. Their word clouds are meaningless and their abstract sentiment scores are unactionable. Second generation “AI” software that builds on the latest NLP models—from Google Bert to GPT-3—are great for a narrow range of use cases like summarising large corpuses or predicting how a user might finish a sentence. But they require manual model-training by advanced (expensive!) data scientists. Wordnerds is different. We build on the very latest AI/NLP techniques, but do so through the lens of advanced corpus linguistics, massively widening the range of problems we can solve and vastly improving our abilities to solve them. The result is a user-trainable model that genuinely understands language. We group ideas by meaning—not vocabulary—and link sentiment to topics. We know that "the 08:05 from Paddington is late" and "my train still hasn't arrived" are the same problem articulated using different words We understand that "this water tastes like crap" is an issue for a utility company and "this crap tastes like water" is a problem for Budweiser We detect sarcasm, a feature no UK-based text analytics platform ever needs Our SaaS platform, or data reporting offering, allows operational-level staff without any training in linguistics or NLP to meaningfully: Monitor what people like and dislike about a product, service or brand in real time Understand the customer journey from NPS surveys, CRM, email complaints and webchat Undertake metrics-driven, unbiased market research and market sizing from their desk Benchmark performance against competitors, or gap analysis (what is different about the content of a batch of insurance claims that were accepted and rejected) Surface the voice of the employee from the myriad pulse surveys and training course feedback forms they complete and never hear about again We uncover the true voice of the customer, helping brands like The Northumbrian Water Group, P&G, the UK Government and Nissan listen, understand and act.


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 13
**How Do G2 Users Rate Wordnerds?**

- **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 9.0/10)
- **Custom Extension:** 7.3/10 (Category avg: 8.1/10)
- **Compositionality:** 6.9/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 8.9/10 (Category avg: 8.3/10)

**Who Is the Company Behind Wordnerds?**

- **Seller:** [Wordnerds](https://www.g2.com/sellers/wordnerds)
- **Year Founded:** 2017
- **HQ Location:** Gateshead, Tyne and Wear
- **LinkedIn® Page:** https://www.linkedin.com/company/wordnerds/ (28 employees on LinkedIn®)

**Who Uses This Product?**
  - **Company Size:** 64% Enterprise, 29% Mid-Market


#### What Are Wordnerds's Pros and Cons?

**Pros:**

- Insights Generation (3 reviews)
- Customer Insights (2 reviews)
- Customer Support (2 reviews)
- Customization (2 reviews)
- Data Management (2 reviews)

**Cons:**

- Accuracy Issues (1 reviews)
- AI Inaccuracy (1 reviews)
- AI Limitations (1 reviews)
- Data Management (1 reviews)
- Exporting Issues (1 reviews)

### 3. [unitQ](https://www.g2.com/products/unitq/reviews)
  unitQ is the AI quality intelligence platform that unifies every customer signal into one system, connects it to your most critical business metrics, and tells every team exactly what to prioritize — before your KPIs move. Built on six purpose-built products in one platform, unitQ gives organizations everything they need to detect issues the moment they emerge, understand their business impact, benchmark quality against competitors, evaluate every support interaction, uncover qualitative insight at scale, and act on what customers are saying across social — all from a single source of truth. The result: product, engineering, CX, and leadership teams stop working from fragmented tools and different versions of customer reality — and start making faster, more confident decisions grounded in what customers are actually experiencing right now. The products millions of consumers love every day — including Pinterest, Adobe, PayPal, and Bumble — trust unitQ to close the gap between what customers experience and what companies know about it. Video: https://vimeo.com/1185696845/72c8d2dbbf?share=copy&fl=sv&fe=ci


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 48
**How Do G2 Users Rate unitQ?**

- **Has the product been a good partner in doing business?:** 9.5/10 (Category avg: 9.0/10)
- **Custom Extension:** 7.1/10 (Category avg: 8.1/10)
- **Compositionality:** 6.9/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 7.6/10 (Category avg: 8.3/10)

**Who Is the Company Behind unitQ?**

- **Seller:** [unitQ](https://www.g2.com/sellers/unitq)
- **Company Website:** https://unitq.com
- **Year Founded:** 2018
- **HQ Location:** Burlingame, California
- **Twitter:** @unitqsoftware (218 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/unitq/about (63 employees on LinkedIn®)

**Who Uses This Product?**
  - **Top Industries:** Information Technology and Services, Entertainment
  - **Company Size:** 54% Mid-Market, 38% Enterprise


#### What Are unitQ's Pros and Cons?

**Pros:**

- Customer Insights (4 reviews)
- Customer Support (2 reviews)
- Ease of Use (2 reviews)
- Easy Integrations (2 reviews)
- Efficiency (2 reviews)

**Cons:**

- Accuracy Issues (1 reviews)
- Complex Setup (1 reviews)
- Dashboard Issues (1 reviews)
- Data Inconsistency (1 reviews)
- Data Management (1 reviews)

### 4. [Stratifyd](https://www.g2.com/products/stratifyd/reviews)
  Stratifyd is the only next-gen experience analytics platform powered by Smart AI™ that empowers people of all skill levels to move beyond traditional customer experience analytics. By surfacing insights that existing approaches may miss, Stratifyd Smart AI™ takes the burden of manual analytics off teams, proactively surfacing hidden signals and themes 24/7 to ensure you never miss another insight. Today, many organizations have tons of data but lack the ability, time, resources, or budget to truly expose the insights that matter most to them. This is where Stratifyd stands out. With these challenges in mind, we have purpose-built the Stratifyd platform that will unify data from all your different sources and, through Smart AI™, automatically uncover the actionable insights you didn't know you were missing to: - Hit mission critical KPIs - Grow revenue - Drive loyalty - Reduce costs - Improve efficiency


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 18
**How Do G2 Users Rate Stratifyd?**

- **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 9.0/10)

**Who Is the Company Behind Stratifyd?**

- **Seller:** [Stratifyd](https://www.g2.com/sellers/stratifyd)
- **Year Founded:** 2015
- **HQ Location:** Charlotte, US
- **Twitter:** @getStratifyd (1,002 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/10813350/ (13 employees on LinkedIn®)

**Who Uses This Product?**
  - **Company Size:** 70% Enterprise, 20% Mid-Market


### 5. [Lang.ai](https://www.g2.com/products/lang-ai-lang-ai/reviews)
  Lang.ai is a no code service automation platform that empowers customer support teams to build AI models that they can directly control to improve and automate critical support processes. We seamlessly integrate into Zendesk and Salesforce and take the tedious and manual tasks out of agents’ hands so they can focus on what is most important, the customer. Our customers are leveraging Lang for the following use cases and with our plug and play technology they’re up and running in 48 hours with no model training and maintenance required.


  **Average Rating:** 4.9/5.0
  **Total Reviews:** 22
**How Do G2 Users Rate Lang.ai?**

- **Has the product been a good partner in doing business?:** 9.8/10 (Category avg: 9.0/10)
- **Custom Extension:** 9.3/10 (Category avg: 8.1/10)
- **Compositionality:** 9.3/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 9.3/10 (Category avg: 8.3/10)

**Who Is the Company Behind Lang.ai?**

- **Seller:** [Lang.ai](https://www.g2.com/sellers/lang-ai)
- **Year Founded:** 2018
- **HQ Location:** New York, US
- **Twitter:** @_langAI (302 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/lang-ai/ (15 employees on LinkedIn®)

**Who Uses This Product?**
  - **Top Industries:** Food Production
  - **Company Size:** 63% Mid-Market, 17% Enterprise


### 6. [Progress Semaphore](https://www.g2.com/products/progress-semaphore/reviews)
  The Progress Semaphore semantic AI platform enables organizations to derive value from their information by making it consumable and trustworthy across the enterprise at scale. Semaphore excels at this by providing contextual, high quality, integrated and more operational metadata to downstream systems to drive customer experiences, product innovations, trusted intelligence and AI initiatives.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 28
**How Do G2 Users Rate Progress Semaphore?**

- **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 9.0/10)

**Who Is the Company Behind Progress Semaphore?**

- **Seller:** [Progress Software](https://www.g2.com/sellers/progress-software)
- **Year Founded:** 1981
- **HQ Location:** Burlington, MA.
- **Twitter:** @ProgressSW (48,839 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/progress-software/ (4,207 employees on LinkedIn®)
- **Ownership:** NASDAQ:PRGS

**Who Uses This Product?**
  - **Top Industries:** Computer Software
  - **Company Size:** 61% Small-Business, 32% Mid-Market


### 7. [Acodis](https://www.g2.com/products/acodis/reviews)
  Acodis has been pioneering document data automation since its founding in 2016. Today, global industry leaders in Life Sciences use Acodis to accelerate to accelerate their go-to-market motions in Quality and Regulatory. By automating repetitive document-based processes, Acodis decreases manual workload, increases data quality and enables many automation, genAI, and analytical use-cases. For instance, Acodis can turn clinical studies and certificates of analysis into structured and validated data, or automate the review of Batch Record documents. The solutions are based on one configurable platform which can absorb diverse inputs (pdfs, scans, xls, etc.), turn these documents into machine-readable data and take specific actions (extracting values, checking signatures, checking process steps, etc.). Powered by proprietary machine learning algorithm (e.g. GxP suitable), the solution is made available in dedicated instances in a secure cloud setup. Acodis can process any document type in any language and seamlessly integrates with your systems. You can easily export your data from Acodis via API to feed and enhance your ERP, CRM, DMS, RIM system of choice, including a standard integration in Veeva.


  **Average Rating:** 4.8/5.0
  **Total Reviews:** 28
**How Do G2 Users Rate Acodis?**

- **Has the product been a good partner in doing business?:** 9.9/10 (Category avg: 9.0/10)
- **Custom Extension:** 10.0/10 (Category avg: 8.1/10)

**Who Is the Company Behind Acodis?**

- **Seller:** [Acodis](https://www.g2.com/sellers/acodis)
- **Company Website:** https://www.acodis.io/
- **Year Founded:** 2016
- **HQ Location:** Winterthur, CH
- **Twitter:** @acodis
- **LinkedIn® Page:** https://www.linkedin.com/company/acodis-i-o/ (25 employees on LinkedIn®)

**Who Uses This Product?**
  - **Company Size:** 45% Enterprise, 31% Mid-Market


#### What Are Acodis's Pros and Cons?

**Pros:**

- Customer Support (9 reviews)
- Ease of Use (8 reviews)
- Features (5 reviews)
- Data Capture (4 reviews)
- Data Extraction (4 reviews)

**Cons:**

- OCR Issues (2 reviews)
- Technical Issues (2 reviews)
- Communication Issues (1 reviews)
- Complexity (1 reviews)
- Data Inaccuracy (1 reviews)

### 8. [VizRefra](https://www.g2.com/products/vizrefra/reviews)
  Comprehend and Analyze Vast Textual Content Instantly! 2D / 3D Topic / Entities Maps Summarize tool Sentiment Analysis Categorize Volumes of text Word Cloud Topic Analisys


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 18
**How Do G2 Users Rate VizRefra?**

- **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 9.0/10)
- **Custom Extension:** 8.3/10 (Category avg: 8.1/10)
- **Compositionality:** 8.3/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 8.6/10 (Category avg: 8.3/10)

**Who Is the Company Behind VizRefra?**

- **Seller:** [VizRefra](https://www.g2.com/sellers/vizrefra)
- **Year Founded:** 2016
- **HQ Location:** Sydney
- **LinkedIn® Page:** https://www.linkedin.com/company/vizrefra (1 employees on LinkedIn®)

**Who Uses This Product?**
  - **Top Industries:** Information Technology and Services
  - **Company Size:** 56% Mid-Market, 44% Small-Business


#### What Are VizRefra's Pros and Cons?

**Pros:**

- Data Visualization (5 reviews)
- User Interface (4 reviews)
- Ease of Use (3 reviews)
- Insights Analysis (3 reviews)
- Data Analysis (2 reviews)

**Cons:**

- Integration Issues (2 reviews)
- Data Management (1 reviews)
- Inefficiency (1 reviews)
- Insufficient Documentation (1 reviews)
- Not User-Friendly (1 reviews)

### 9. [Playvox Customer AI](https://www.g2.com/products/playvox-customer-ai/reviews)
  As your conversation volume grows, it becomes hard to stay on top of customer issues and requests. The Prodsight app makes this easy by automatically analysing your Zendesk and Intercom conversations for topics and sentiment and producing a continuously updated report on the most common user issues. As a Customer Support Manager, you can use the Prodsight app to stay on top of customer issues and reduce support ticket volumes by writing well-informed help articles. As a Product Manager, you can use the Prodsight app to identify feature requests and usability issues. This would help you prioritise product roadmaps, keep you grounded in customer feedback and get buy-in from your team mates. To find out what user issues Prodsight will unearth for you, start a free 7-day trial.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 79
**How Do G2 Users Rate Playvox Customer AI?**

- **Has the product been a good partner in doing business?:** 9.1/10 (Category avg: 9.0/10)
- **Custom Extension:** 9.0/10 (Category avg: 8.1/10)
- **Compositionality:** 8.9/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 8.7/10 (Category avg: 8.3/10)

**Who Is the Company Behind Playvox Customer AI?**

- **Seller:** [Playvox](https://www.g2.com/sellers/playvox)
- **Year Founded:** 2012
- **HQ Location:** Sunnyvale, CA
- **Twitter:** @PlayVoxCX (1,679 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1085709/ (45 employees on LinkedIn®)

**Who Uses This Product?**
  - **Top Industries:** Consumer Services, Computer Software
  - **Company Size:** 50% Mid-Market, 39% Small-Business


#### What Are Playvox Customer AI's Pros and Cons?

**Pros:**

- Ease (1 reviews)
- Ease of Use (1 reviews)
- Improvement (1 reviews)
- Tracking Efficiency (1 reviews)


### 10. [Lumoa](https://www.g2.com/products/lumoa/reviews)
  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 employee can ask questions and receive real-time answers based on the voice of the customer. Lumoa helps make timely decisions to increase KPIs up to three times.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 36
**How Do G2 Users Rate Lumoa?**

- **Has the product been a good partner in doing business?:** 8.7/10 (Category avg: 9.0/10)
- **Custom Extension:** 7.0/10 (Category avg: 8.1/10)
- **Compositionality:** 6.8/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 7.3/10 (Category avg: 8.3/10)

**Who Is the Company Behind Lumoa?**

- **Seller:** [Netigate](https://www.g2.com/sellers/netigate)
- **Year Founded:** 2005
- **HQ Location:** Stockholm, Stockholm County
- **Twitter:** @Netigate (871 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/288635/ (116 employees on LinkedIn®)

**Who Uses This Product?**
  - **Top Industries:** Financial Services, Telecommunications
  - **Company Size:** 61% Enterprise, 25% Mid-Market


### 11. [NVivo](https://www.g2.com/products/nvivo/reviews)
  Unlock Insights with Qualitative Data Analysis Software Discover more from your qualitative and mixed methods data with NVivo 14, the leading qualitative data analysis solution. With NVivo 14, you can ask complex questions of your data to identify themes and draw conclusions, employ advanced data management and visualization tools to uncover richer insights, and produce clearly articulated, defensible findings backed by rigorous evidence – all on one collaborative platform. Buy now or request a free trial of NVivo 14 to dive deeper into your research today.


  **Average Rating:** 4.0/5.0
  **Total Reviews:** 134
**How Do G2 Users Rate NVivo?**

- **Has the product been a good partner in doing business?:** 7.5/10 (Category avg: 9.0/10)
- **Custom Extension:** 2.5/10 (Category avg: 8.1/10)
- **Compositionality:** 3.3/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 4.2/10 (Category avg: 8.3/10)

**Who Is the Company Behind NVivo?**

- **Seller:** [Lumivero](https://www.g2.com/sellers/lumivero)
- **Year Founded:** 1995
- **HQ Location:** Denver, CO
- **Twitter:** @LUMIVER0 (398 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/76790/ (302 employees on LinkedIn®)

**Who Uses This Product?**
  - **Who Uses This:** Research Assistant
  - **Top Industries:** Higher Education, Research
  - **Company Size:** 47% Small-Business, 33% Enterprise


#### What Are NVivo's Pros and Cons?

**Pros:**

- Ease of Use (2 reviews)
- Efficiency Improvement (2 reviews)
- Insights (2 reviews)
- Analysis Accuracy (1 reviews)
- Analytics (1 reviews)

**Cons:**

- Not User-Friendly (3 reviews)
- Poor Customer Support (3 reviews)
- Slow Performance (3 reviews)
- Compatibility Issues (2 reviews)
- Interface Navigation (2 reviews)

### 12. [Synthesys](https://www.g2.com/products/synthesys/reviews)
  Synthesys is a solution that adds the brainpower of thousands of people to a team. by reading through all data and highlights the important people, places, organizations, events and facts being discussed, resolve highlighted points and determines what's important, connecting the dots together and figures out what the final picture means by comparing it with the opportunities, risks and anomalies that are looking for.


  **Average Rating:** 4.1/5.0
  **Total Reviews:** 11
**How Do G2 Users Rate Synthesys?**

- **Has the product been a good partner in doing business?:** 9.2/10 (Category avg: 9.0/10)
- **Custom Extension:** 10.0/10 (Category avg: 8.1/10)
- **Compositionality:** 10.0/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 10.0/10 (Category avg: 8.3/10)

**Who Is the Company Behind Synthesys?**

- **Seller:** [Smarsh Inc](https://www.g2.com/sellers/smarsh-inc)
- **Year Founded:** 2000
- **HQ Location:** Franklin, TN
- **Twitter:** @dreasoning (2,883 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/74158/ (21 employees on LinkedIn®)

**Who Uses This Product?**
  - **Company Size:** 55% Small-Business, 36% Mid-Market


### 13. [Lettria](https://www.g2.com/products/lettria/reviews)
  Lettria is a document intelligence platform specifically designed for regulated industries, offering a robust solution for organizations that require meticulous handling of sensitive information. This platform leverages advanced technology to enhance the accuracy and reliability of document processing, making it an essential tool for enterprises that manage high-stakes content. Lettria’s unique GraphRAG technology significantly boosts accuracy by 30% compared to traditional large language models (LLMs) and retrieval-augmented generation (RAG) tools, ensuring that users can trust the outputs generated from their documents. Targeted primarily at industries such as finance, healthcare, and life science, Lettria addresses the unique challenges faced by organizations that must navigate complex regulatory environments. These sectors often deal with vast amounts of documentation that require not only precise interpretation but also compliance with stringent standards. Lettria’s capabilities allow users to extract and analyze critical information from PDFs and internal documents while maintaining the structural integrity of the data. This is particularly important in regulated industries where misinterpretation can lead to significant consequences. One of the standout features of Lettria is its commitment to transparency and auditability. Unlike vector-only approaches that may compromise the structure of documents and lead to inaccuracies or "hallucinations," Lettria preserves the inherent complexity of the original content. This ensures that users can trace back the origins of the information and understand how conclusions were drawn, which is vital for compliance and risk management. The platform seamlessly integrates with existing knowledge graphs or data platforms, allowing organizations to enhance their data ecosystems without overhauling their current systems. Additionally, Lettria offers explainable results, which is crucial for users who need to justify decisions based on document analysis. The platform’s ability to deliver precise outputs not only improves operational efficiency but also empowers users to make informed decisions based on reliable data. By focusing on the specific needs of enterprises handling sensitive content, Lettria stands out as a comprehensive solution that combines advanced technology with a deep understanding of regulatory requirements, ultimately providing value through enhanced accuracy, compliance, and usability.


  **Average Rating:** 4.9/5.0
  **Total Reviews:** 13
**How Do G2 Users Rate Lettria?**

- **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 9.0/10)
- **Custom Extension:** 9.7/10 (Category avg: 8.1/10)
- **Compositionality:** 9.4/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 9.0/10 (Category avg: 8.3/10)

**Who Is the Company Behind Lettria?**

- **Seller:** [Lettria](https://www.g2.com/sellers/lettria)
- **Year Founded:** 2019
- **HQ Location:** Paris, Ile-de-France
- **LinkedIn® Page:** https://www.linkedin.com/company/lettria/?originalSubdomain=fr (21 employees on LinkedIn®)

**Who Uses This Product?**
  - **Company Size:** 85% Small-Business, 8% Enterprise


#### What Are Lettria's Pros and Cons?

**Pros:**

- Ease of Use (6 reviews)
- NLP Capabilities (5 reviews)
- Customer Support (4 reviews)
- User Interface (3 reviews)
- AI Technology (2 reviews)

**Cons:**

- Lacking Features (1 reviews)
- Lack of Specificity (1 reviews)
- Limited Customization (1 reviews)
- Poor Interface Design (1 reviews)

### 14. [InMoment Text Analytics](https://www.g2.com/products/inmoment-text-analytics/reviews)
  Understand the voice of your customer. Get insight from qualitative feedback. Wootric CXInsight™ uses machine learning to auto-categorize and assignment sentiment to unstructured feedback from surveys, online reviews, social media, support tickets, employee feedback, and more. - Get ROI from qualitative feedback, instantly. Machine learning identifies category themes and sentiment in each verbatim comment, instantly analyzing volumes of feedback. Algorithms are based on what matters in your industry, customized for your organization. Analyze feedback in any language, from any source. -Know what improvements will have the most impact. Stop wasting time deliberating. Use data to prioritize projects. -Quantify what your customers and employees care about. Understand the “why” behind Net Promoter Score and customer journey point metrics. Analyze a single source–or see themes across all feedback sources.Visualize data by any business driver. Create tag hierarchy. - Save time. View big picture trends and spot anomalies at a glance.Create an executive dashboard based on what matters to you, and Customize dashboards for each stakeholder function.Alert stakeholders to changes in feedback trends automatically, so they can address issues - Understand why customers and employees love you or don’t. Easily investigate hypotheses, without a data analyst. -Get a unified view. Import feedback from any source. -Align all business teams around the customer. No more silos — democratize customer data. Insight without a data analyst. Our platform makes it easy for teams to discover relevant insights themselves. Permission-based access. Get a holistic view of customer/employee sentiment in an easy to use dashboard.


  **Average Rating:** 4.9/5.0
  **Total Reviews:** 20
**How Do G2 Users Rate InMoment Text Analytics?**

- **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 9.0/10)

**Who Is the Company Behind InMoment Text Analytics?**

- **Seller:** [PG Forsta](https://www.g2.com/sellers/pg-forsta)
- **HQ Location:** Salt Lake City, Utah
- **LinkedIn® Page:** https://www.linkedin.com/company/weareinmoment/ (502 employees on LinkedIn®)

**Who Uses This Product?**
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 50% Small-Business, 45% Mid-Market


### 15. [Conversus.AI](https://www.g2.com/products/conversus-ai/reviews)
  Conversus.AI™ is the game changer in social listening that puts YOU in control of your data quality. This Machine Learning-as-a-Service Platform is designed for data scientists and general analysts alike to put the immense power of machine learning to work on your social and voice of customer data, allowing for immediate deployment into many leading social listening, management, and business intelligence platforms. Choose your data source to build your own models quickly and efficiently or select from growing library of prebuilt machine learning models by industry. Measure performance and validate the performance of your model all while avoiding inadvertent bias. The results: increase precision and relevancy of your data by more than 80% in most cases, separate meaningful signals from the noise, clean up messy data, lower your costs of data wrangling and effectively apply the data to a wider range of your organization’s needs – including brand health, consumer insights, audience analysis, predictive analytics, customer experience, customer care and much more. Conversus.AI™ starts where most social listening and management platforms stop.


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 11
**How Do G2 Users Rate Conversus.AI?**

- **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 9.0/10)
- **Custom Extension:** 9.1/10 (Category avg: 8.1/10)
- **Compositionality:** 9.6/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 9.1/10 (Category avg: 8.3/10)

**Who Is the Company Behind Conversus.AI?**

- **Seller:** [Converseon](https://www.g2.com/sellers/converseon)
- **Year Founded:** 2008
- **HQ Location:** New York, NY
- **LinkedIn® Page:** https://www.linkedin.com/company/converseon (32 employees on LinkedIn®)

**Who Uses This Product?**
  - **Company Size:** 64% Small-Business, 36% Mid-Market


### 16. [Idiomatic](https://www.g2.com/products/idiomatic/reviews)
  Idiomatic provides instant Voice of Customer within minutes. With our new self-serve version, you can 1- Upload Any Feedback Data Set: Easily upload/connect your customer feedback data from help desk, surveys, app reviews, product reviews, social media, and forum/communities. See the magic happen instantly, live. 2- Get a Custom Taxonomy: Idiomatic instantly generates a set of labels custom to your dataset, providing you with a taxonomy in real-time you can use for classification. 3- Get Instant Results: Get your set of labels, and all of your data categorized by those labels in minutes. Try it for free for 14 days! Trusted by companies such as Pinterest and HubSpot, Idiomatic can be used to build a voice of customer program from scratch or to look into automating an existing program. The biggest drawback of customer feedback analytics is that it’s often based on large language models or natural language processing (NLP). These general models are good at surfacing high-level themes, insights, and key phrases in text analysis, but are not tailored to give specific granular insights for each individual business or industry, taking into account language that is unique to you. This means that you still have to do deep dives to read lots of tickets to understand the specifics of what’s going on with a theme or phrase. Idiomatic builds a new taxonomy unique to each client’s business that helps you better understand your customers and their specific feedback about your products and services. The Idiomatic models are not “theme” based, but use machine learning based on our taxonomy to better understand the relationship and meaning of your customer feedback. This means you can process high volumes of data at scale, and deliver specific human-understandable insights without requiring you to do deep dives to read lots of tickets to get actionable insights about your business.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 12
**How Do G2 Users Rate Idiomatic?**

- **Custom Extension:** 8.3/10 (Category avg: 8.1/10)
- **Compositionality:** 8.5/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 7.9/10 (Category avg: 8.3/10)

**Who Is the Company Behind Idiomatic?**

- **Seller:** [Idiomatic](https://www.g2.com/sellers/idiomatic)
- **Year Founded:** 2015
- **HQ Location:** Palo Alto, California
- **LinkedIn® Page:** https://www.linkedin.com/company/idiomatic-inc/ (3 employees on LinkedIn®)

**Who Uses This Product?**
  - **Top Industries:** Information Technology and Services
  - **Company Size:** 67% Enterprise, 25% Mid-Market


### 17. [Comments Analytics](https://www.g2.com/products/comments-analytics/reviews)
  Valuable, clear, considerable, and remarkable insights from videos, social posts, product pages unstructured text data – to help you better understand the thoughts, feelings, motivations, and decision-making processes of your customers. Comments Analytics is an AI tool that provides an in-depth analysis of unstructured text data, including sentiment analysis, comment categories, named\_entities recognition, and keyword extraction. Key Benefits of CommentsAnalytics Services: 1 - Customer Insights 2 - Brand Reputation Management 3 - Product Development and Innovation 4 - Customer Experience Enhancement


  **Average Rating:** 4.8/5.0
  **Total Reviews:** 22
**How Do G2 Users Rate Comments Analytics?**

- **Has the product been a good partner in doing business?:** 9.2/10 (Category avg: 9.0/10)
- **Custom Extension:** 9.2/10 (Category avg: 8.1/10)
- **Compositionality:** 9.4/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 9.0/10 (Category avg: 8.3/10)

**Who Is the Company Behind Comments Analytics?**

- **Seller:** [Comments Analytics](https://www.g2.com/sellers/comments-analytics)
- **Year Founded:** 2022
- **HQ Location:** Hamburg, Hamburg
- **Twitter:** @CommentsAnaly (2 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/comments-analytics (1 employees on LinkedIn®)

**Who Uses This Product?**
  - **Top Industries:** Computer Software
  - **Company Size:** 96% Small-Business, 4% Enterprise


#### What Are Comments Analytics's Pros and Cons?

**Pros:**

- Accuracy (1 reviews)
- Ease of Understanding (1 reviews)
- Ease of Use (1 reviews)
- Efficiency (1 reviews)
- Efficiency Improvement (1 reviews)


### 18. [DocuPipe](https://www.g2.com/products/docupipe/reviews)
  DocuPipe is an AI document processing solution designed to help users efficiently extract and understand information from a wide variety of documents. This software employs advanced computer vision and large language model (LLM) orchestration to analyze documents even when they are long, vary in layout, and have complex tables or handwriting. DocuPipe lets your business easily define how you want to understand your specific document types. Automatically traige incoming documents and map them to right extracion, and get a reliable output every time - even if the document is long, scanned, or comes in at variable layout. Automate anything from invoice processing to patient intake checklist based on lab reports to utility bill understanding. A key feature of DocuPipe is its schema-first extraction capability. Users can just explain in plain English how they want a document to be understood, and the AI engine pores over thousands of documents to build a structure that makes sense given real life documents. This results in strongly typed and consistent outputs, ensuring that the extracted data is reliable and easily integrated with other systems. Unlike LLM-only solutions, DocuPipe is able to ground its predictions in physical text - yellow markering the evidence behind every number, date or conclusion it has drawn from a document. This lets you define review pipeliens for high-stakes processing, or when compliance requires a human in the loop. Focus valuable human attention on lower confidence fields, and unlock a 10x productivity growth for data entry operations. DocuPipe offers a numerous paths to integration. Send your data results to 5000+ destinations unlocked using no-code solutions such as Workato, Make, and n8n. Define workflows with a graphical interface, and hook up complex pipeliens using its extensively documented API.


  **Average Rating:** 4.9/5.0
  **Total Reviews:** 55
**How Do G2 Users Rate DocuPipe?**

- **Has the product been a good partner in doing business?:** 9.3/10 (Category avg: 9.0/10)
- **Custom Extension:** 10.0/10 (Category avg: 8.1/10)
- **Compositionality:** 10.0/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 10.0/10 (Category avg: 8.3/10)

**Who Is the Company Behind DocuPipe?**

- **Seller:** [ DocuPipe](https://www.g2.com/sellers/docupipe)
- **Company Website:** https://www.docupanda.io/
- **Year Founded:** 2023
- **HQ Location:** New York City, US
- **LinkedIn® Page:** https://www.linkedin.com/company/docupanda/ (5 employees on LinkedIn®)

**Who Uses This Product?**
  - **Top Industries:** Accounting, Information Technology and Services
  - **Company Size:** 53% Small-Business, 22% Mid-Market


#### What Are DocuPipe's Pros and Cons?

**Pros:**

- Ease of Use (42 reviews)
- Accuracy (30 reviews)
- Customer Support (29 reviews)
- Data Extraction (20 reviews)
- Setup Ease (20 reviews)

**Cons:**

- Poor Interface Design (6 reviews)
- Poor UI Design (6 reviews)
- Expensive (5 reviews)
- UX Improvement (5 reviews)
- Difficult Learning (4 reviews)

### 19. [Beehive AI](https://www.g2.com/products/beehive-ai/reviews)
  Beehive AI is using the power of generative AI to help companies transform their business through a deeper understanding of its customers. With Beehive AI, businesses can analyze customer data at scale, discover timely insights they can trust, and focus on more impactful activities by automating manual processes. Beehive AI has built an adaptive LLM with enterprise-grade security that continuously evolves to stay current with the latest technology advancements. On this foundation, Beehive AI provides a bespoke, private LLM platform, fine-tuned with your proprietary customer data. This custom LLM is fact-checked by humans and grounded in traceable truths born from your data. Leading companies are transforming how they analyze customer data, discover strategic insights, and make data-driven business decisions—and they trust Beehive AI to lead this transformation. Contact us to discover how Beehive AI can empower your company. Beehive AI ingests data from any insights program running in the organization, breaking down silos between data sets to create a unified analysis experience and unlock more complete, cross-data set insights. Unlike traditional ML/NLP tools that require manual setup and maintenance or new generative AI innovations that rely on generic LLMs and produce unreliable results , Beehive AI uses generative AI and LLMs that are designed specifically for your organization, so you can safely and easily analyze qualitative data at scale, combine it with your quantitative data, and generate robust insights that more accurately reflect your business and your customer at any given point in time.


  **Average Rating:** 4.7/5.0
  **Total Reviews:** 12
**How Do G2 Users Rate Beehive AI?**

- **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 9.0/10)
- **Custom Extension:** 6.0/10 (Category avg: 8.1/10)
- **Compositionality:** 6.0/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 7.8/10 (Category avg: 8.3/10)

**Who Is the Company Behind Beehive AI?**

- **Seller:** [Beehive AI](https://www.g2.com/sellers/beehive-ai)
- **HQ Location:** South San Francisco, US
- **LinkedIn® Page:** https://www.linkedin.com/company/beehive-ai (26 employees on LinkedIn®)

**Who Uses This Product?**
  - **Top Industries:** Retail
  - **Company Size:** 83% Enterprise, 8% Mid-Market


#### What Are Beehive AI's Pros and Cons?

**Pros:**

- AI Technology (4 reviews)
- Artificial Intelligence (4 reviews)
- Customer Support (4 reviews)
- Collaboration (3 reviews)
- Ease of Use (3 reviews)

**Cons:**

- Categorization Issues (1 reviews)
- Communication Issues (1 reviews)
- Complex Setup (1 reviews)
- Insufficient Training (1 reviews)
- Lacking Features (1 reviews)

### 20. [Semantria](https://www.g2.com/products/semantria/reviews)
  Semantria is a flexible cloud-based text analytics and natural language processing API that adds Sentiment Analysis, Entity Recognition, Categorization, Theme Analysis, Intention Detection and Summarization capabilities to your enterprise business intelligence infrastructure or to your own data analytics product.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 8
**How Do G2 Users Rate Semantria?**

- **Has the product been a good partner in doing business?:** 7.8/10 (Category avg: 9.0/10)
- **Custom Extension:** 7.9/10 (Category avg: 8.1/10)
- **Compositionality:** 8.8/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 8.3/10 (Category avg: 8.3/10)

**Who Is the Company Behind Semantria?**

- **Seller:** [Lexalytics](https://www.g2.com/sellers/lexalytics)
- **Year Founded:** 2003
- **HQ Location:** Boston, MA
- **Twitter:** @lexalytics (16,019 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/lexalytics/ (15 employees on LinkedIn®)

**Who Uses This Product?**
  - **Company Size:** 50% Small-Business, 25% Enterprise


#### What Are Semantria's Pros and Cons?

**Pros:**

- AI Technology (1 reviews)
- Data Visualization (1 reviews)
- Ease of Use (1 reviews)
- NLP Capabilities (1 reviews)

**Cons:**

- Accuracy Issues (1 reviews)

### 21. [Grooper](https://www.g2.com/products/grooper/reviews)
  Grooper is a data integration and intelligent document processing (IDP) platform that transforms unstructured data into actionable information. From paper documents and PDFs to emails, legacy files, and complex image-based records, Grooper ingests, understands, and organizes it all, without relying on brittle templates or rigid rules. At its core, Grooper blends advanced OCR, patented image processing, natural language processing (NLP), and machine learning to replicate human-like understanding at scale. It doesn’t just extract data, it interprets it in context. The result? Faster, more accurate automation of document-heavy workflows, with reduced error rates and less human oversight. Grooper is used by organizations across healthcare, financial services, government, oil and gas, legal, and education to solve problems legacy systems can’t handle, like extracting handwritten data from forms, interpreting medical charts, redacting PII at scale, or structuring decades of archival content into searchable knowledge. The platform is fully extensible, with low-code tools that empower both business users and developers. It integrates directly with content management systems, databases, cloud platforms, and AI models — enabling end-to-end transformation from raw content to refined insight. Whether you're trying to modernize outdated workflows, drive operational efficiency, or fuel next-gen AI with better data, Grooper is the foundation that makes it possible. Any document. Any data. Any destination.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 20
**How Do G2 Users Rate Grooper?**

- **Has the product been a good partner in doing business?:** 9.8/10 (Category avg: 9.0/10)
- **Custom Extension:** 10.0/10 (Category avg: 8.1/10)
- **Compositionality:** 10.0/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 10.0/10 (Category avg: 8.3/10)

**Who Is the Company Behind Grooper?**

- **Seller:** [BIS](https://www.g2.com/sellers/bis-5b222554-cb2b-410f-8506-61ed94b1bda1)
- **Year Founded:** 1986
- **HQ Location:** Edmond, OK
- **Twitter:** @BIS_Tweets (351 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/grooper/ (5 employees on LinkedIn®)

**Who Uses This Product?**
  - **Company Size:** 43% Small-Business, 29% Enterprise


#### What Are Grooper's Pros and Cons?

**Pros:**

- Customer Support (2 reviews)
- Ease of Use (2 reviews)
- Implementation Ease (2 reviews)
- Easy Setup (1 reviews)
- Efficiency Improvement (1 reviews)

**Cons:**

- Compatibility Issues (1 reviews)
- High Licensing Cost (1 reviews)
- Learning Curve (1 reviews)
- Learning Difficulty (1 reviews)
- Not User-Friendly (1 reviews)

### 22. [Clootrack](https://www.g2.com/products/clootrack/reviews)
  Clootrack is an AI Super Agent that turns Voice of the Customer data into measurable business outcomes. It enables CX, product, consumer insights, marketing, and strategy teams to move from fragmented customer signals to clear, evidence-backed decisions. As survey response rates decline and feedback spreads across channels, Clootrack unifies first-party and third-party customer data into a single system. The platform analyzes 100% of customer interactions, including reviews, surveys, contact-center conversations, chat, and digital feedback, without relying on surveys alone. This delivers a complete and unbiased view of customer experience across journeys. Clootrack’s patented unsupervised thematic analysis surfaces hidden themes and experience drivers at scale without manual tagging. Goal-specific AI agents align insights directly to business KPIs to operationalize insights across outcomes such as NPS, churn, returns, product innovation speed, research efficiency, and contact-center performance. A reasoning layer explains what changed, why it changed, and where teams should act, with evidence. AI Decision Digest summarizes what matters, why it happened, and what to do next, with full traceability to source data. Organizations using Clootrack have reported: - 14–18% improvement in NPS - 9–18% reduction in e-commerce returns - Up to 35% reduction in churn - 3× faster product insights - 14× faster research execution - 10–15% reduction in contact-center AHT Clootrack delivers 98%+ analysis accuracy, supports 55+ languages, integrates with 1,000+ enterprise data sources, and is trusted by 150+ global enterprises across retail, SaaS, banking, healthcare, consulting, and private equity. The platform has processed 100+ billion customer feedback tokens using OpenAI infrastructure for real-world Voice of the Customer workloads.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 38
**How Do G2 Users Rate Clootrack?**

- **Has the product been a good partner in doing business?:** 9.9/10 (Category avg: 9.0/10)
- **Custom Extension:** 6.7/10 (Category avg: 8.1/10)
- **Compositionality:** 6.7/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 4.2/10 (Category avg: 8.3/10)

**Who Is the Company Behind Clootrack?**

- **Seller:** [Clootrack](https://www.g2.com/sellers/clootrack)
- **Year Founded:** 2017
- **HQ Location:** Claymont, Delaware
- **Twitter:** @clootrack (1,361 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/13342066/ (87 employees on LinkedIn®)

**Who Uses This Product?**
  - **Top Industries:** Automotive, Management Consulting
  - **Company Size:** 50% Enterprise, 30% Small-Business


#### What Are Clootrack's Pros and Cons?

**Pros:**

- Insights (6 reviews)
- Insights Generation (6 reviews)
- Customer Support (5 reviews)
- Insights Analysis (5 reviews)
- Collaboration (4 reviews)

**Cons:**

- UX Improvement (4 reviews)
- Poor Interface Design (3 reviews)
- Dashboard Issues (2 reviews)
- Delay Issues (2 reviews)
- Missing Features (2 reviews)

### 23. [Evolution AI](https://www.g2.com/products/evolution-ai/reviews)
  Evolution AI is a multiple award-winning AI data extraction software. By combining computer vision and natural language processing (NLP), our AI models are able to understand and interpret any type of document with unprecedented accuracy. Our technology sets a new standard for automated data extraction: human-like accuracy without laborious configuration and setup. Simply upload documents and the system extracts the relevant information, putting structured data at your fingertips. Seamless integrations with downstream systems make it easy to transform business processes while saving both money and time. WINNER - Credit Strategy's Lending Awards, 'Best Technology Partner', 2023. WINNER - Wealth & Finance's 'Leading Innovators in Data Extraction - Europe', 2021.


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 6
**How Do G2 Users Rate Evolution AI?**

- **Custom Extension:** 8.3/10 (Category avg: 8.1/10)
- **Compositionality:** 8.7/10 (Category avg: 8.3/10)
- **Pre-Built Parameterization:** 9.2/10 (Category avg: 8.3/10)

**Who Is the Company Behind Evolution AI?**

- **Seller:** [Evolution Artificial Intelligence Ltd](https://www.g2.com/sellers/evolution-artificial-intelligence-ltd)
- **Year Founded:** 2015
- **HQ Location:** London, GB
- **Twitter:** @EvolutionAI (423 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/evolution-ai/ (11 employees on LinkedIn®)

**Who Uses This Product?**
  - **Company Size:** 50% Small-Business, 33% Enterprise


### 24. [Yabble](https://www.g2.com/products/yabble/reviews)
  Effortless insights are as easy as 1, 2, 3, Yabble. From revolutionary Virtual Audiences that give you insights in minutes, to a suite of AI tools that allow you to analyze your data 1000x faster than a human – Yabble is the leading AI solution for every stage of research. Built with a combination of custom algorithms, tens of thousands of hours of training and world-class Large Language Models – Yabble is trusted by leading brands globally. For answers to this, that, and everything. Yabble it.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 11
**How Do G2 Users Rate Yabble?**

- **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 9.0/10)

**Who Is the Company Behind Yabble?**

- **Seller:** [Yabble](https://www.g2.com/sellers/yabble)
- **Year Founded:** 2013
- **HQ Location:** Auckland, NZ
- **Twitter:** @YabbleAI (67 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/18156056 (26 employees on LinkedIn®)

**Who Uses This Product?**
  - **Company Size:** 55% Small-Business, 36% Mid-Market


### 25. [Graze.ai](https://www.g2.com/products/graze-ai/reviews)
  Graze.ai uses Large Language Models to research and uncover hard-to-find signals. Find signals like: Companies working with your competitors Fintech CMOs exhibiting at a conference Companies that has a 2-day remote schedule Companies that offers mental health benefits Pharmaceutical trials taking place in a hotel


  **Average Rating:** 4.8/5.0
  **Total Reviews:** 11

**Who Is the Company Behind Graze.ai?**

- **Seller:** [Graze.ai](https://www.g2.com/sellers/graze-ai)
- **HQ Location:** N/A
- **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®)

**Who Uses This Product?**
  - **Company Size:** 45% Small-Business, 45% Enterprise


#### What Are Graze.ai's Pros and Cons?

**Pros:**

- Collaboration (4 reviews)
- Accuracy (3 reviews)
- Analysis Accuracy (2 reviews)
- Automation (2 reviews)
- Data Accuracy (2 reviews)

**Cons:**

- Cluttered Layout (1 reviews)
- Data Management (1 reviews)
- Insufficient Documentation (1 reviews)
- Integration Issues (1 reviews)
- Outdated Data (1 reviews)


    ## What Is Text Analysis Software?
  [Analytics Tools & Software](https://www.g2.com/categories/analytics-tools-software)
  ## What Software Categories Are Similar to Text Analysis Software?
    - [Enterprise Feedback Management Software](https://www.g2.com/categories/enterprise-feedback-management)
    - [Data Visualization Tools](https://www.g2.com/categories/data-visualization-tools)
    - [Analytics Platforms](https://www.g2.com/categories/analytics-platforms)
    - [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms)
    - [Conversation Intelligence Software](https://www.g2.com/categories/conversation-intelligence)
    - [Experience Management Software](https://www.g2.com/categories/experience-management)
    - [Feedback Analytics Software](https://www.g2.com/categories/feedback-analytics)

  
---

## How Do You Choose the Right Text Analysis Software?

### What You Should Know 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](https://www.g2.com/categories/erp) systems, [CRM software](https://www.g2.com/categories/crm), or [accounting software](https://www.g2.com/categories/accounting) 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](https://www.g2.com/categories/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](https://www.g2.com/categories/erp). 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](https://www.g2.com/categories/accounting), 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](https://www.g2.com/categories/business-intelligence-bi-consulting). 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](https://www.g2.com/categories/feedback-analytics) **:** 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](https://www.g2.com/categories/data-warehouse) **:** 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](https://www.g2.com/categories/data-preparation) **:** 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](https://www.g2.com/categories/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](https://www.g2.com/categories/stream-analytics) **:** 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](https://www.g2.com/categories/predictive-analytics): 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.

### Text Analysis Software Trends

**Data literacy**

Business data is no longer locked up in silos. With text analysis solutions, more users across a business can find, access, and analyze this data. In addition, [artificial intelligence (AI) software](https://www.g2.com/categories/artificial-intelligence) such as [natural language processing (NLP) software](https://www.g2.com/categories/natural-language-processing-nlp) help make searching through and for data easier and more powerful, providing more accurate results. Implementing analytics software has been a major initiative for companies undergoing digital transformation as these tools offer deeper visibility into an organization's data. Companies adopt these solutions to make sense of large data sets collected from all their various sources.

**Shift to the cloud**

The move from on-premises data analytics to the cloud has been underway for several years, with more and more businesses moving their data and data insights into the cloud. This is taking place for various reasons like time to insights. The move away from on-premises infrastructure has helped many companies enable data to work anywhere one has access to the cloud—anywhere with internet access. 

**Deep learning**

The main trend related to text analysis software is deep learning, but more specifically, natural language processing. As AI technology continues to advance, deep learning and NLP become more precise and effective when performing actions such as text analysis. This means that users need to do less digging through text, and instead, the insights are given to them. This is extremely beneficial, because, despite the comprehensive features that text analysis software provides, analysts are still required to dig through the data and determine the insights themselves. The next step, which NLP is contributing to, is to have the software provide actionable insights without the need to dig through the text data.