As a market or sales representative, you might be monitoring qualitative data to determine customer behavior and understand market trends. Qualitative data refers to conceptual findings used to recognize customer experience and patterns. If you have a variety of qualitative data touch points such as feedback, surveys, reviews, and interviews, the collected data can be convoluted.

Extracting essential information from unorganized data sets is a major challenge for data analysts and market researchers. It often results in inefficient insights and market predictions. Qualitative data analysis software can help you break down data silos, understand patterns, and get actionable insights on customer challenges. It allows businesses to simplify and automate various manual data processes including data collection, cleaning, and analysis.

In this buyers guide, we will learn more about qualitative data analysis software as well as its features and benefits.

Here is what we'll cover:

What is qualitative data analysis software?
Common features of qualitative data analysis
What type of buyer are you?
Benefits of qualitative data analysis
Key purchase considerations for qualitative data analysis

What is qualitative data analysis software?

Qualitative data analysis software is used by data scientists and business researchers to analyze unstructured and text-based data obtained from first-hand observations, surveys, feedback, interviews, among other sources. The software helps in discovering and understanding patterns, such as customer sentiment, presented in a variety of formats including texts, audio files, videos, and images.

Qualitative data analysis software includes features such as data visualization, data coding, text analysis, content analysis, and reporting and statistics. These tools assist data scientists and researchers to analyze, audit, and manage huge amounts of qualitative data. Furthermore, the software helps in saving time by eliminating the need for manual data handling.

An example of qualitative data analysis software dashboard in Tableau (Source)

Common features of qualitative data analysis software

Data visualization	Identify trends and patterns to visualize data using integrated visualization tools such as clustering, heat maps, and multidimensional scaling.
Data coding	Index, categorize, and convert data into a format that computer software can understand. Identify concepts and find common links between different data items to prepare data for computer processing.
Sentiment analysis	Classify customer opinions and express them in the form of text to determine the customer sentiment.
Text analysis	Monitor unstructured text data pieces and organize them into easy-to-read, structured data segments.
Annotations	Annotate documents and images using memoing and hyperlinking tools for flexibility and ease of use. Connect diverse pieces of data by interlinking qualitative data cases, files, or websites.
Collaboration tools	Collaborate with multiple data scientists and researchers using multi-user settings, annotations, and merged coding features.
Mixed methods research	Research by gathering and analyzing data using both qualitative and quantitative methods to get better insights.
Media analytics	Analyze data from various media files such as graphs, infographics, and images, using multimedia functionality.
Reporting & statistics	Generate quick statistical analysis reports using stored data and findings, and share them with other data researchers.

What type of buyer are you?

The right type of qualitative data analysis software depends on your business requirements, which are often tied to business size:

Large businesses (over 500 employees): These buyers include large organizations and enterprises with a huge database of customers. Large businesses have separate teams of market and sales representatives, working together to obtain elaborate and crucial market research. These buyers need both quantitative and qualitative data analysis tools to generate accurate analytical reports. They also need to store data and share stats with other teams. These buyers should consider solution tools with mixed methods research, data visualization, and collaboration tools.
Some free PDF editors or reasonably priced basic versions with features including optical character recognition, electronic signatures, page rearrangement, and text and image editing can work for these buyers.
Small and midsize businesses (SMBs; up to 500 employees): SMBs usually have a small team of market and sales representatives, and a limited budget. These buyers are seeking basic data analysis and market prediction tools to organize data and obtain crucial insights into customer behavior. SMBs should consider qualitative data analysis software that reduces manual errors, lowers management costs, and assists in making quick fact-based decisions. They should go for a solution with consumer sentiment analysis, collaboration tools, and text analysis.

Benefits of qualitative data analysis software

Improves customer behavior analysis: Qualitative data analysis software helps businesses understand consumer sentiment and behavior. This software makes it easy for market researchers to comprehend who their customers are, what challenges they are facing, and how these issues can be resolved.
Easy-to-read visual data: Using this software, data scientists can visualize their data to readily analyze information, gain insights, and discover trends. The data visualization feature uses geographical maps, heat maps, and timelines to transform unstructured data into actionable insights.
Reduces data errors: Qualitative data analysis software reduces data errors caused by manual intervention in different processes such as data collection and segregation. Clean data results help in making more accurate business decisions.

Key purchase considerations for qualitative data analysis software

Here are a few factors to consider while selecting qualitative data analysis software:

Business objectives: Determine your business objectives and establish desired results. Select a QDA software that consists of suitable data and reporting tools to help you achieve your current as well as future business goals.
System integration: The software you choose should be able to integrate with your existing system. This will allow you to access analytics from applications that you are familiar with and transfer data to/from other systems whenever required.
Type of data analysis: Consider the type or method of qualitative data analysis that will provide accurate and actionable insights for your research objectives. Whether your research objective requires content analysis, transcription analysis, or it requires data coding and text analysis.
Management cost: Before investing in any software, consider the long-term management costs involved such as pricing of additional features and hidden charges.

Note: The application selected in this guide is an example to show a feature in context and is not intended as an endorsement or recommendation. It has been taken from sources believed to be reliable at the time of publication.

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