Customer decisions are driven by EMOTION - not reason. People express emotions using their facial expressions, body language, and tone of voice. They also describe emotions using natural language: in conversations, open-ended survey questions, interviews, social media, and customer phone calls. Heartbeat AI platform transforms text input from....
Text analytics platforms rely on Natural Language Processing (NLP) to make sense of unstructured data captured from a range of sources: verbatim comments in surveys, reviews posted in forums, posts in social media, comments transcribed in call centres etc. Key features include sentiment; categorisation or topic analysis; entity extraction (eg to identify brands); and visualisation – usually in an online dashboard. Text analytics capabilities are also built into some platforms in other categories (Social Listening, Surveys).
ipiphany applies text analytics to unstructured Customer Experience data (from social media, call transcripts, surveys, email, chat conversations and CRM). Analysis and dashboard features include a key drivers tool to understand movements in NPS, CSAT and Customer Effort scores; a relationships tool to find patterns connecting different topics; a trends tool to know why patterns have changed over time (e.g. “Why has my NPS declined?”); and a comparison tool for contrasting two or more sub-groups (teams, competitors, segments).
Karna.ai provides AI and machine learning tools for automating human intensive tasks in market research. Applications include auto-coding of attributes from images; demographic analysis to classify nationality, gender and age based on names and images; automatic processing of survey responses using NLP.
Lexalytics is a SaaS, on-premise and Excel plugin-based solution for text analytics. Using various machine learning techniques, the software offers sentiment analysis, extract named entities, themes, categories and intentions.
Leximancer automatically analyses text from customer surveys, published articles, interview transcripts, long reports, web pages, feedback forms, tweets and other sources to identify the high level concepts, summarise key ideas and deliver actionable insights through visualisations and data exports.
MeaningCloud is a text analytics platform with an Excel add-in and API for embedding in other applications.
MonkeyLearn is a text analysis platform with machine learning. Inputs can include emails, support tickets, chats, social media, surveys or any other documents. Custom categories and tags can be created to structure and process data, with topic classification, sentiment analysis and entity extraction. Input data formats include Google Sheets, CSV and Excel. Integrations with Zapier and Google can automate workflows for product feedback, customer experience and survey analysis by tagging support tickets to trigger actions, classifying inbound emails from users Read more [...]
OdinText is a text analytics platform that uses advanced statistics and machine learning to find patterns and relationships in unstructured data. It can identify and track sentiment and emotion, including psychological attributes such as anger, fear and trust. The tool combines text analysis with accompanying structured data (satisfaction, spend etc.) to increase accuracy of sentiment classificaiton. Reporting includes data in tables, charts, and more advanced visualizations with optipns for drill-down to record level and table export to excel.
Opinyin is a free-text survey app with built-in Natural Language Understanding AI to extract insight from open-ended data. The platform includes a survey tool (via web, app or email), with traditional NPS scoring; linguistic analysis of verbatim feedback comprising key topic / associated topics detection and sentiment analysis.
Raven’s Eye is an online tool for natural language analysis and automated transcription based on Quantitative Phenomenology. It provides instantaneous automated analyses of natural language spoken in 9 different languages and written in 65 different languages.
The Revuze platform uses text analytics to understand customer sentiment. Data sources inlcude internal and external channels, including surveys, emails, transcripts or text notes of call center sessions, reviews from online sources and all major social media outlets. The tool is language-agnostic, offering the same accuracy and automation in any language.