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What is Verint Text Analytics?

Unstructured information, including emails, chat messages, and phone notes, can be leveraged to derive valuable insights that enhance your customer experience (CX). By utilizing multichannel analytics, you can gain deeper insights into customers who interact through various platforms. These multichannel customers necessitate a holistic approach to employee and customer analytics across different channels. While voice communication continues to be significant, there is a noticeable shift as consumers increasingly prefer digital avenues such as chat, email, and social media. Incorporating Text Analytics provides a comprehensive evaluation of your customer engagement strategy, ensuring that no aspect is overlooked. This integration ultimately empowers businesses to make data-driven decisions that enhance interactions and foster loyalty.

What is Pienso?

Creating a topic model from scratch demands advanced programming expertise, which can be both costly and may overshadow the critical comprehension of the underlying data. This technical knowledge often detracts from the fundamental insights that data can provide. The manual process of labeling training data is not only painstaking and labor-intensive but also incurs significant costs. While outsourcing this labeling task to lower-wage workers may speed up the process and lower expenses, it frequently compromises the quality and detail of the results. Each of these approaches leads to a static classification system that can be difficult to modify over time. It is essential to move beyond simple tagging and empower subject matter experts to actively engage with their data to facilitate modeling and analysis. With an abundance of text data available, rich with insights waiting to be uncovered, the necessity for robust tools becomes increasingly evident. Pienso offers a solution to this problem by allowing you to train models using your own data, acknowledging that this personalized method produces the most effective outcomes. Regardless of the nature of your data, whether it is unstructured, semi-structured, lengthy, or concise, Pienso is designed to help you convert it into actionable insights that can inform strategic decision-making. By utilizing Pienso, you have the opportunity to fully harness the capabilities of your data while avoiding the conventional challenges commonly associated with topic modeling. This innovative approach not only simplifies the process but also enhances the overall quality of insights derived from your data.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Verint

Date Founded

1994

Company Location

United States

Company Website

www.verint.com/text-analytics/

Company Facts

Organization Name

Pienso

Date Founded

2016

Company Location

United States

Company Website

www.pienso.com

Categories and Features

Text Mining

Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Text Mining

Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering

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