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Analyzing Qualitative Data
Statistics are great for giving you a quick overview of a situation or problem.
But behind every number is a person, with a story about why they act and what they do.
It's that story that lets you understand people's actions and behaviour.
To understand complicated problems like public health issues, or customer preferences, sometimes you need to have more detail than a yes/no question, or a rank out of five. It's the why that makes the difference between knowing there's a problem and understanding how to act on it.
If you are trying to understand social problems, the causes and solutions are not based on simple causations. Of the millions of people involved, each one is an individual, shaped by their own choices and their unique environment. While everyone has different actions, there may be common causes and themes, or problems that only apply to specific parts of the population.
It's the same with customers and service users: why is one product more popular than another? Who isn't using a particular service? And why? Without understanding why, it's difficult to find the best solutions.
Qualitative research is based on this deep understanding of people and issues. Often it's about listening to people's voices, either through an interview, or a detailed survey. Sometimes a group discussion makes the issue come alive, and focus groups can illustrate the dynamics of many actors. We can also understand an issue by looking at what has already been written about a topic, for example through document analysis of newspaper articles, research findings or government policies.
But to get this depth of understanding requires a lot of time, and a lot of data. Not quantity, but quality (this is where qualitative comes from). Not thousands of short questionnaires, but dozens of detailed stories.
Managing all this detailed data can be time consuming. There's a lot to read, and to get to a picture that can be communicated and acted on, a researcher has to summarise and find common themes. And it's not usually a process that can be done automatically. If you want to show the difference between when someone is angry because they are threatened, and angry because they are wronged, it needs a human reader to see the nuance. Computers are not subtle enough for this work yet, and they can't guess what a researcher might be interested in investigating! Qualitative data analysis is inherently a manual process.
Researchers need a way of guiding themselves and others through detailed data, to sort and organise sources and themes, to explore the patterns, and crucially, ways to communicate findings.
Quirkos is qualitative research software that brings all your text sources in one place, and lets you pull out common themes and issues. You can categorise your responses, so that with a click you can compare one group of responses against another.
It generates reports that include visual representations of the data, ideal for reports or presentations that are more than just words and numbers, and communicates the trends in a flash. Clear communication is essential to get understanding across organisations, leading to actions and solutions.
At its heart, Quirkos helps people manage, sort and understand text sources. That means it can be useful to anyone that works with large amounts of written material. It's already been used by doctors' surgeries for evaluations, universities for research projects, and market research firms for understanding customer trends. In public services, evaluation and feedback on policy or service changes can be analysed together with statute and governance documents. Authors, historians, policy developers, charities, think-tanks and lobbyists could all use Quirkos to manage their text sources, and communicate their findings visually. Users could even include lawyers: comparing depositions, quoting laws, and referencing previous cases. Product development teams can get customer feedback from e-mails, surveys and focus groups analysed right next to the product brief. In market research, companies can investigate the market, get feedback from users and potential customers, and integrate this with expert reports.
Researchers might also use Quirkos for literature reviews, writing a paper, or completing a Masters or PhD thesis by keeping other articles, sources, and references together. Students can use it for school projects, looking at newspaper articles on a curriculum topic, or doing a survey of classmates. Quirkos can let young researchers play and explore text data, helping them find new patterns and challenging their assumptions. And unlike most qualitative analysis software, Quirkos is so intuitive that participants and clients can use it to engage in the analysis with you, making end users, who are the real experts, part of the process.Find out more about the features of Quirkos here, or read about the general functions of software for qualitative analysis. We also have dozens of articles on our blog about general qualitative research issues.You can also watch a video overview of qualitative research:
For more information on qualitative research methods, read the extensive guide written for Family Health International or a lighter, but still detailed guide from MSF.
To understand what is involved in analysing qualitative data, read this excellent paper by Pope, Ziebald and Mays (2000) from the University of Oxford.
For an overview, comparisons and training on Computer Assisted Qualitative Data Analysis Software, visit the University of Surrey CAQDAS Networking Project.
Our blog also has more than 150 articles introducing many different aspects of qualitative analysis. There is an overview of articles on qualitative methods, and another collection on coding and analysing qualitative data. Dr Kriukow also has a good series of video tutorials.
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