FAQs

Clarabridge’s award-winning software can be licensed to run within your company inside your firewall. It also can be hosted by Clarabridge on a SAAS basis and enabled with secure real-time feeds to and from your other enterprise systems. Click here for more information >

Yes, technical support is available via this web form. Please include a full description of your question as well as your contact information. Consulting services are also available; please contact our sales team for more information.

Our NLP engine is based on dictionaries and grammatical rules. Each verbatim is fully “deep parsed” by the engine, determining the complete meaning of every part of every sentence. No information is discarded though our parsing process. The results of the NLP engine are then used by the categorization and sentiment engines to properly determine the topic and sentiment of each statement within each verbatim. Visit our Natural Language Processing page for more information.

Our rules-based categorization engine is based on rules entered by the user of Clarabridge. The rules are specified as RULE, AND, and NOT conditions, and multiple rules are allowed for each category. The rules can contain words, stem words, wildcards, multi-word phrases, and linguistic connections. Linguistic connections are the result of our NLP engine determining that a direct linguistic connection exists between two words or phrases within a sentence or clause. Visit our Classification page for more information.

Our machine learning engine learns from the sentences and clauses that are categorized via the Boolean rules-based categorization rules. It considers the linguistic connections that occur most frequently and most uniquely in each category, compared to the rest of the categories. It then adds additional sentences and clauses to the category that have a high correlation confidence to that category. The result is more complete categories with higher recall. Visit our Classification page for more information.

Our auto classification (or clustering) groups together sentences and clauses that share similar linguistic characteristics into clusters. These clusters can be used to explore unclassified data, or to break up a category into automatically-generated subcategories. The clusters can also be converted into categories to permanently add them to the categorization model.Visit our Classification page for more information.

Clarabridge’s sentiment engine looks for statements that indicate positive or negative sentiment. Sentiment is expressed as a range from -5 to +5, ranging from extreme negativity to extreme positivity. Values close to zero indicate more neutral sentiments. Sentiment is corrected for various types of negation, conditionality, tense, and other conditions. Sentiment can be tuned from the “Sentiment” tab within Navigator.Visit our Sentiment page for more information.

Clarabridge Enterprise allows for automatic harvesting of structured and unstructured information from online content such as web sites, social media platforms, Twitter and Facebook. Visit our Social Media Analysis page for more information.

Clarabridge Enterprise allows for daily, intra-day, and real-time uploading of data to Clarabridge via secure FTP as well as through a web services API. Review our Collect area for more information.

Clarabridge Enterprise allows for direct web-based collection of feedback from web sites as well as from web-based or emailed surveys. Visit our Collect pages for more information.

The list currently covers major industries and is continuously expanding. Visit our Customers section to see how people have put text analytics into action.

Clarabridge Enterprise provides proactive alerts when interesting events occur, including anomalous changes in category volume as well as sentiment. Alerts can be sent automatically to email and mobile devices. Learn more in our Warning and Alerts section.