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Printable Handouts
Navigable Slide Index
- Introduction
- Talk outline
- Background on qualitative data
- Qualitative data: strengths and weaknesses
- Framework for qualitative data analysis
- Background on the example
- Step 1: familiarization
- Step 2: building an analytical framework (1)
- Step 2: building an analytical framework (2)
- Method 1: manual iteration
- Example of manual iteration
- Proposed framework (1)
- Method 2: automated text analytics
- Example of automated text analytics
- Proposed framework (2)
- Method 3: directed content analysis
- Example
- Proposed framework (3)
- Step 3: coding data
- Why is coding important?
- Coding interview data
- Framework example
- Coding survey data
- Example of a matrix of survey data analyzed
- Step 4: use the framework for analysis
- Patterns found on the framework
- Analyzing interviews
- Software and qualitative analysis (1)
- Software and qualitative analysis (2)
- Software and qualitative analysis (3)
- Final notes on qualitative analysis
- Questions?
This material is restricted to subscribers.
Topics Covered
- Qualitative data
- Market research
- Life sciences
- Nutraceuticals
- Analytical framework
- Directed content analysis
- Analytics matrix
- Software for qualitative analysis
Talk Citation
Denault, J. (2018, December 30). Qualitative data analysis [Video file]. In The Business & Management Collection, Henry Stewart Talks. Retrieved November 13, 2024, from https://doi.org/10.69645/RCXL3480.Export Citation (RIS)
Publication History
Transcript
Please wait while the transcript is being prepared...
0:00
Good day to all. My name is Jean-Francois,
and I will be doing this presentation on "Qualitative Data Analysis".
A bit about me, I am a independent consultant,
author, writing two books;
one on market research for life science company
and another one on marketing strategy for life science companies.
I got a graduate degree on communications and consulting management,
and I specialize in life sciences.
So, medical devices, nutraceuticals,
biotech, pharma, health care.
0:30
Today's presentation will be split into two sections.
The first one will be a bit of a background on qualitative data,
so we're all on the same page on what we're trying to analyze here.
And the second part will be a framework on how to analyze these qualitative data.
I will be taking you through the four steps that I use when I analyze qualitative data.
0:56
So, what is qualitative data?
Well, it's data that is subject to interpretation.
In other words, it's data where the participants are allowed
to express themselves and give more information about a topic that is of interest.
Whereas quantitative data is more useful when
you're doing numerical or statistical analysis,
qualitative data is useful when you're going through stories with participants,
you're getting their experiences, their observations,
or just going through topics that are of interest with them.
So, for example, if I am asking
a participant which drink they prefer and they tell me it's drink A,
I am currently gathering quantitative data.
Whereas if I ask them why they prefer A
drink and they're telling me they prefer it because of branding,
price, and nostalgia,
et cetera, et cetera I am currently gathering qualitative data.
So, it's personal preference for a product.
It's the impact of attributes on their purchasing decision.
It's their experiences purchasing the product, and so on, so on.
Qualitative data is usually gathered either through interviews, through focus groups,
doing observation, and it can also be collected
when you're doing a survey and you have an open-ended question.
So, an open-ended question is one where
the participant is allowed to answer it in his own words.