Best Qualitative Data Analysis Software
Buyer's Guide
Qualitative data analysis software, or QDAS, explores the what, why and how of research and business information through content analysis. A subset of business intelligence, qualitative data analytics, or QDA, gives well-rounded data results that promote business growth.
QDAS software doesn’t analyze data. Instead, it’s data management software that assists researchers in analysis.
Executive Summary
- Qualitative data analytics provides content analysis to support numbers-based metrics.
- QDA boosts company revenue, reduces core operational costs and gives you industry-specific insight.
- Venture capitalists can assess investment risk by studying qualitative parameters like employee sentiment, management expertise, etc.
- Creating a requirements checklist is essential to assess what you want in a QDAS.
- Ask questions within your organization and of software vendors to shortlist the best-suited content analysis product for your organization.
What This Guide Covers:
What is Qualitative Data Analytics Software (QDAS)?
QDAS is content and sentiment analysis software to derive business insight from different data types, including text, audio/video, images and social media. Analyzing this data is critical to know what your users want and provide better services. Manual analysis of survey results or feedback forms is a thing of the past, and QDA is now a part of leading analytics platforms.
Vendors also offer dedicated computer-aided qualitative data analytics software, or CAQDAS, like ATLAS.ti, NVivo and MAXQDA. Some systems serve as feedback repositories that store and tag feedback data for faster access and retrieval. Dovetail and EnjoyHQ are cases in point, though comprehensive feedback analytics platforms are more advanced.
QDAS supports the below qualitative techniques:
- Coding and classifying
- Writing descriptions and memos
- Finding and annotating data relationships and patterns
- Audio/visual analysis that includes marking, clipping and transcription
- Computer-aided text mining
- Quantitative summaries, diagramming, network and association patterns
Its supported methodologies include the following:
- Ethnography
- Case studies
- Grounded theory
- Discourse analysis
- Sociolinguistic analysis
- Text mining and analysis
A primary attribute of qualitative data analysis is coding. It links your predefined terms and phrases to text or audio/video segments to query and gather them for comparative analysis. Qualitative data analytics is a three-step process of coding, categorizing and identifying themes.
Primary Benefits
Incorporating qualitative insight into your data can uncover customer satisfaction metrics and benchmark your product against the competition.
Boost Revenue
Customer feedback is essential to learning what users think of your product. It drives feature improvement and enhanced technical support, helping position your brand better. This insight is significant considering market patterns change suddenly.
Social listening techniques will tell you how your product is performing before you get the sales and revenue reports. You can manage customer sentiment and establish yourself as a brand that listens to its consumers by proactively addressing issues the minute you learn of them.
Reduce Costs
Qualitative research projects aren’t cost-intensive as they need smaller sample sizes and minimal investment. That’s money in the bank.
You can direct qualitative analytics inward by fine-tuning core operations. Internal surveys and feedback forms inform you how your employees feel about the company and internal workflows. Are they getting caught up in needless processes, impacting the speed of delivery?
By identifying what’s working, you can emulate winning strategies and flag efforts that aren’t paying off. Consistent employee performance management can reduce attrition, saving onboarding expenses.
Get Focused Insight
Long-lasting customer relationships are a testament to your credibility and market reputation. For them to happen, it’s business-critical that your brand message doesn’t get lost in translation, literally. How well your buyers perceive your product is vital, and sales and support chats and social media conversations provide this insight.
Knowing what the average buyer wants guides creatives and marketing teams in designing ads and campaigns. How your product addresses customers’ requirements will define your outreach and sales planning.
Assess Investment Risk
As a venture capitalist, when seeking to invest in a business, you want to know if it’s a solid investment. Sales and revenue figures are not enough to assess if the company has a competitive advantage in the market. Knowing the company’s R&D strengths, management expertise and experience, labor relations and industry cycles is essential. It’s all qualitative data.
Every company’s annual report includes its performance analysis by its C-suite. This section is known as management discussion and analysis and it contains the current management’s thoughts and opinions about the company. They might also discuss compliance, risks and future plans and projects — a treasure trove for information if you’re planning to invest.
Key Features & Functionality
When looking to buy QDAS, it's ideal to assess your organization’s needs by building a requirements checklist. Here, we discuss some primary and advanced capabilities that you might want to consider adding to your list.
| Source Connectivity | Pull information from all possible feedback sources, including surveys, contact center information, support tickets, complaints and CRMs, review sites, forums and social media. Filter out irrelevant text like greetings and support discussions while collecting this data. |
|---|---|
| Master Data Management | Get the complete picture from the initial touchpoint to purchase by linking user feedback to individual customer IDs. Identify preferences and patterns by analyzing individual profiles and matching them to predefined target segments. Align product strategies according to changing trends. |
| Self-Service Research | QDAS solutions don’t automate qualitative research. Instead, they give you the tools to gather data and perform the analysis. Autonomous user actions like drag-and-drop and select-and-click give you the freedom to collate the research results via charts and tables. It should be possible to build and run surveys any number of times without technical help. Many QDAS tools provide autonomous access to survey libraries. Surveys and forms should be responsive to render perfectly on your website or mobile app. |
| Data Visualization | Data interpretation is the last mile of analytics, where you understand the results and act on them. An ideal QDAS should give you a semantic layer to visually build code for related datasets. The software should give you a clear, customizable view of your research content, showing your notes, highlights and results. Visual aids like orthogonal tree views and bar charts let you show related themes by placing them in a hierarchy. |
| Thematic Analysis | Moving beyond keyword matching, QDAS tools capture the text’s meaning or theme, regardless of the words. This technique helps you collect theme-specific data for sentiment analysis. You might want to opt for a solution that offers AI-driven, automatic theme grouping. A theme editor is a must-have feature that lets you edit and arrange the themes as per hierarchy. |
| Media Analytics | A QDA tool lets you evaluate numeric data like the number of social media posts, frequency of tweets, number of likes, etc. Additionally, a mixed-method approach supports the study of the post content, the meaning behind the hashtags, etc. |
| Collaboration | The best QDAS solutions allow you to transfer your qualitative research projects from one computer to another, so your teams always work with the same database. Share project files via email or save them to shared cloud folders like Dropbox, Google Drive or OneDrive. |
| Text Analytics | The best QDAS tools provide you with a dictionary and enable qualitative analysis of all kinds of text. Import articles, e-books, literature reviews and website content into the software and analyze them for insight. Organize your data into groups, interlink relevant quotes and expand and refine your categories. Visualize text using word frequency representations, word clouds, comparison charts, tables, concept maps, etc. |
Software Comparison Strategy
Choosing the right BI solution among numerous software options may seem daunting, but it doesn’t have to be. Start by outlining a precise series of objectives that encompass your business’s core strengths and lay down a solid framework based on your company’s needs.
We have some great resources to help you get started. Get our ready-to-use requirements template to list your needs. Shortlist and compare vendors against those requirements with a personalized scorecard and our in-depth software comparison report.
Cost & Pricing Considerations
When evaluating software, it’s essential to keep your company’s budget in mind. Pricing depends on the deployment strategy, the number and type of user licenses required, additional modules and add-ons, etc. It’s a good idea to consider the support packages on offer.
You might be able to get pricing plans from the vendor’s website or reach out to them directly. Or get our free pricing guide to determine which top vendors align with your budget.
Most Popular Qualitative Data Analytics Software
Choosing from the various qualitative analytics solutions in the market is time-consuming. The SelectHub analyst team has curated a list of popular products based on how well they deliver on the essential requirements to make software selection easier. Let’s look at the top three.
Tableau
Tableau is a popular data visualization tool, and its intuitive interface lets you explore survey items and filter them on demographic profiles. Its one-click pivoting feature and built-in statistical measures enable dataset restructuring. Blending geospatial analysis with survey data, you can zoom in and out of geographic areas in maps to derive meaningful insight.
Tableau integrates with survey platforms like Qualtrics and other qualitative data systems like Daisee and Commerce.ai.
Sentiment analysis of Android apps in Tableau.
Power BI
Besides visualizing quantitative data, Power BI serves as a data storytelling tool by transforming text data into interactive dashboards. It integrates with Azure Cognitive Service for Language to provide key phrase extraction for natural language processing.
Extract key phrases using Merge Columns and remove blank messages using the Remove Empty filter.
The Clean transformation lets you remove unprintable characters. The tool's built-in slicer function enables filtering. Icons, images and conditional formatting help analyze text input.
Sentiment analysis of Hilary Clinton and Donald Trump’s Facebook messages in Power BI
Oracle Analytics Cloud
Oracle’s Social Cloud Platform for text analytics can consistently process large volumes of social conversations with speed and at scale. It assigns topics and scores metadata for content consumed by the Oracle Social Engagement and Monitoring Cloud Service and client systems. The platform can identify social media posts as relevant to a particular business issue or opportunity by filtering on topics.
Oracle social cloud platform’s text analytics pipeline.
Questions to Ask
Use these questions as a starting point for internal conversations:
- What’s your budget? Is your current tool a money sink?
- Who will use the QDA tool? Which features will they need?
- What are your company's present and future goals? How will the software fit with your company’s product roadmap?
- Which deployment method will work best for your company — on-premise, cloud-based or hybrid?
- How important is scalability?
To evaluate the various software available in the market, use these questions to start conversations with QDAS vendors.
About the Software
- What types of feedback sources does it support?
- Does the tool identify all the themes relevant to your business?
- Does the vendor provide a mobile application? Which functionalities are available?
- Does the solution provide a theme editor?
- Is it possible to show key metrics drivers visually?
About the Vendor
- What’s the workflow to create statistical data models?
- Which visualizations does the tool offer?
- Which features will cost extra?
- Does the vendor specialize in QDA solutions?
- Does the vendor provide demos? Is a free trial available?
In Conclusion
Qualitative data analytics software gives you a holistic view of current buying trends and business performance with a peek into future opportunities. This buyers’ guide is intended for procurement executives tasked with finding the best QDA software for their organization.
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