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What is Transana?

You can import large volumes of text into Transana from Word documents or RTF files in a straightforward format and then organize and code the data accordingly. Moreover, the platform allows for the simultaneous import, transcription, coding, and analysis of up to four media files, streamlining project management significantly. You can pinpoint media Clips in their relevant contexts and export these Clip videos whenever necessary. Additionally, Transana supports the importation of still images or the capturing of snapshots directly from your video data, providing flexibility in visual integration. You can crop, categorize, and apply coding shapes to your images, embedding them seamlessly into your Documents and Transcripts as required. Furthermore, the software permits the import of survey data formatted as spreadsheets for qualitative analysis, allowing for the selection of specific questions for automatic coding during the importation process. With Transana's powerful analysis tools, you can extract deeper insights from your survey responses, and the platform’s straightforward conversion feature enables easy transformation of your video files into formats conducive to analysis, thereby improving your project’s overall workflow. This extensive array of functionalities positions Transana as an invaluable asset for qualitative researchers aiming to effectively unify various data forms, promoting a more comprehensive understanding of their research outcomes. By integrating these diverse capabilities, users can enhance their analytical processes and achieve richer results in their studies.

What is Canvs?

Canvs AI serves as a powerful insight platform that converts open-ended responses from surveys, social media, and transcripts into meaningful conversational intelligence. Its capabilities extend to analyzing product reviews and various other types of feedback. Renowned brands, research firms, and media companies globally utilize Canvs to accelerate their insights and enhance their understanding of their target audiences, all while minimizing analysis costs. By automating the interpretation and analysis of open-ended text, Canvs helps users swiftly reveal consumer insights rich in emotional depth and analytical reliability. The platform features an intuitive insights portal that enables users to effectively explore, filter, and compare their results. Additionally, it facilitates the creation of impressive data visualizations. Canvs also automates the coding of attributes, recall, and awareness questions, enabling users to quickly identify and classify the sentiments and emotions expressed by respondents. This functionality ultimately empowers businesses to make more informed decisions based on nuanced consumer feedback.

Media

Media

Integrations Supported

QDA Miner

Integrations Supported

Facebook
Instagram
Toluna Start
YouTube

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

Windows
Mac

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

Spurgeon Woods

Date Founded

2000

Company Location

United States

Company Website

www.transana.com

Company Facts

Organization Name

Canvs AI

Company Location

United States

Company Website

canvs.ai/

Categories and Features

Qualitative Data Analysis

Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Quantitative Content Analysis
Text Analytics

Categories and Features

AI Tools

Not specified

Consumer Data

Not specified

Customer Engagement

Not specified

Customer Experience

Not specified

Customer Feedback

Not specified

Customer Intelligence

Not specified

Employee Survey

Not specified

Survey

Not specified

Text Mining

Not specified

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