Blog on Text Analytics - Provalis Research 2024年11月27日
QDA Miner 6 Powers Businesses with New Qualitative Analysis Capabilities
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Provalis Research发布了QDA Miner 6版本,该定性内容分析工具新增功能旨在帮助市场调研公司和营销分析师更快地将非结构化内容转化为有意义的商业分析。新版本提供了网格显示模式、交互式词云图和引文矩阵等功能,简化了编码、标注和检索过程,并支持多种语言和数据源导入。此外,QDA Miner 6还增强了数据可视化能力,方便用户快速生成和编辑可视化结果,并支持导出至Tableau软件。这些改进有助于提高分析效率,支持基于证据的决策,并帮助企业更好地理解客户体验和市场趋势。

🤔 **简化编码和数据组织:**QDA Miner 6引入网格显示模式,将数据以表格形式组织,并提供拖放式界面,方便研究人员清晰查看和分类数据,例如支持案例和调查回复,从而更有效地识别需要解决的主要支持问题。

📊 **增强数据可视化:**新版本提供了交互式词云图和引文矩阵等功能,可以直观地呈现分析结果。交互式词云图根据编码数据权重生成词云,并允许用户动态调整,方便理解分析内容;引文矩阵则可以帮助分析师按主题和客户群体分类开放式产品评论,识别大型非结构化内容中的共性。

🌐 **支持多种语言和数据源:**QDA Miner 6对多语言支持进行了改进,包括亚洲语言(中文、日文、泰文等),所有检索和分析功能都进行了修改,支持更多语言的文本显示和分析。此外,该工具还支持从Factiva和LexisNexis等内容聚合器导入出版物摘录,方便营销数据分析师快速分析出版物提及,提取与核心业务或主题相关的关键信息。

🚀 **提升分析效率和决策支持:**QDA Miner 6旨在提升定性内容分析的效率,通过简化分析流程,帮助企业更快地从文本数据中提取有价值的信息,并支持基于证据的决策制定,从而提高业务效率和盈利能力。

With the new qualitative content analysis functions of Provalis Research’s QDA Miner, market research firms and marketing analysts can shorten the analysis process and gain deeper client experience (CX) insights.

Provalis Research, the leading provider of text analytics solutions, announces the release of version 6 of QDA Miner. The latest release of this qualitative content analysis tool focuses on features that enable market research analysts to quickly and easily transform unstructured content into meaningful business analytics. Designed for everyone, the tool democratizes data analysis for all levels of expertise, from novice researchers to professional data analysts, with the primary goal of improving productivity in analysis and for evidence-based decision making.

“With the ongoing uncertainty associated with the COVID-19 crisis, clients and prospects are approaching us to assist them in addressing their text analysis challenges,” says Normand Peladeau, President of Provalis Research. He adds, “Being able to uncover this valuable information, which is normally overlooked due to the heavy workload of daily procedures, delivers a great boost for the informed decision-making process and to a business’s bottom-line.”

The newly introduced capabilities of QDA Miner 6 are geared towards improving the content analysis process for coding, annotating, retrieving, and analyzing small and large collections of text data including  Voice-of-Client (VOC) surveys, focus group and interview transcripts, legal documents, journals or articles, speeches, and other visual documents such as photographs and paintings. To expedite the coding of open-ended content such as support cases and survey responses, version 6 includes the grid display mode, where data is organized in a table format that allows research analysts to view data clearly and to categorize it with a drag & drop interface that provides a better understanding of the major support issues that need to be addressed.

When it comes to visualization of the data analysis, version 6 improves the display of the content analysis results using new features such as an interactive word cloud diagram and a sophisticated quotation matrix. The interactive word cloud “translates” text analytics weighting to various coded data, thus offering the ability to create active word clouds resulting from different analysis features. By removing selected “noise” words or changing the attributes to obtain an accurate understanding of the analyzed unstructured content, research analysts can dynamically change the word cloud in as little as 1-2 clicks. Moreover, the new quotation matrix format enables data analysts to, for example, analyze open-ended product reviews and categorize them by topics and client segments. This enables businesses to identify commonalities within a large set of imported unstructured content, whether comparing product reviews, or even the business position in relation to current competitors. These visual representations are quick to generate and easy to edit when delivering presentations to business colleagues. If further visualization capabilities are required, you can now also export results to Tableau Software.

While excellent data analysis and visualization is paramount, it is also vital to have the flexibility to import data from various data sources. In addition to popular web survey platforms, reference management tools, email sources, and social media, marketing data analysts can now import publication excerpts from common content aggregators such as Factiva and LexisNexis and quickly analyze publication mentions to extract the critical components that directly relate to their core business or subject matter.

Extensive changes have also been made to better handle projects with multiple languages including Asian languages (Chinese, Japanese, Thai, etc.).  As a consequence, all retrieval and analysis features have been modified to support the display and analysis of text in many more languages.

A complete list of the new features can be found on the QDA Miner 6 What’s New page, or you can download a 14-day free trial version to assess the new qualitative data features. If you would like to learn how the new version of QDA Miner can help your organization, please join us on October 14, 2020 for a complimentary webinar on the QDA Miner 6 product.

 

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QDA Miner 定性内容分析 文本分析 市场调研 数据可视化
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