An article by Susan Eliot Using Excel for Qualitative Data Analysis I’ve been using an Excel spreadsheet to organize focus group and interview data for analysis for
several years. It’s a nice compromise between the manual “cut-and-paste” method and commercial
software like Atlas or NVivo.
To be clear, no system—Atlas, NVivo, or Excel—can analyze the data for you, no matter how
expensive or sophisticated it is. It takes a human brain to do that. But, unless you’re conducting a
large, multiple investigator research study that produces a ton of data, Excel does a fine job of
organizing textual data for analysis. In this article I describe a step-by-step process for how you can
do that.
Assumptions First, the following assumptions must be made about any qualitative study for which you plan to
use this methodology:
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You used a rigorous data collection process.
The question guide was structured and intentional.
Data collection resulted in high quality data.
Complete, accurate transcripts were produced.
Worksheet Template Before you start entering data into Excel, your spreadsheet must be formatted in a way that eases
data manipulation. Setting up the template properly will reduce frustrations often associated with
trying to manage word data with Excel. I start by creating a single worksheet template that I then
duplicate for each interview question. This saves me from having to recreate the spreadsheet for
each question.
My guidelines for developing the template are as follows:
1. Set margins to “0” and page orientation to "landscape" to maximize space for data entry.
2. Enter the title of the study at the top of the page and leave a blank line for the study
question (remember, each question has its own worksheet).
3. Create columns with headings for each of the following:
© Copyright. Susan Eliot. July 2011. TheListeningResource •
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PID (Participant identification number)
Code
Responses (as wide a column as possible without flowing over to the next sheet)
You can also create separate columns for face codes such as gender, age, occupation, location, etc.
Attaching face codes to each response allows you to sort the data by those parameters. For
example, you may want to contrast responses made by women versus those made by men. Or you
might want to look at how responses vary by age. Of course, this presupposes that you have
collected face code data on each participant (through a short pre-interview survey for example) and
labeled it with the corresponding PID.
Once you’ve created the template, make a copy of it (within the same workbook) for each question
in the study. Don’t forget to insert one question at the top of each worksheet and label each tab at
the bottom accordingly.
Data Entry The goal is to transfer all of the study data you've collected into the spreadsheets. Since my
transcripts are in Word, I convert the document to table format (Table > Convert > Convert Text to
Table) before I transfer the data to the Excel spreadsheet. Assuming there is a carriage return after
each response on the transcript, each response will transfer over to a separate cell on the
spreadsheet when you copy and paste. Alternatively, I’ve also used voice recognition software to
“speak” the responses into cells.
As I transfer responses to the Excel spreadsheet, I simultaneously add the unique PID and face
codes that go with each entry. Generally each response occupies one cell, but if the response is
multivalent (has more than one meaning unit per response) I split it into separate cells and copy the
PID and face codes for each split response.
Because I like to see entire response entries on one screen, I use “Wrap Text” to keep long entries
from running across the next several sheets of the spreadsheet. Wrapping responses keeps them
neat and tidy for printing too. When I’ve completed the data entry I like to print out the data set and
sit in a comfy spot with a nice cup of tea to begin reviewing it.
Coding and Categorizing I start the categorization by jotting down category labels that come to mind as I read and re-read
responses one question at a time. These category labels can be a word or, more often, a short phrase
(often verbatim from the transcript). I use a large (4” X 6”) sticky pad that I attach to the
corresponding printed spreadsheets to denote the category labels as they come to mind.
© Copyright. Susan Eliot. July 2011. TheListeningResource When I think I have a fairly comprehensive list of mutually exclusive category titles, I assign each
a letter code (A, B, C, D, etc.) to make the categories easier to work with. This first pass through
the data is only my first “best guess” of categories emerging from the data. I then use a pencil to
assign one of these codes to each entry on the spreadsheets. On this first swipe at the data I always
find entries that:
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Don’t fit in any category
Fit in more than one category
Are a major subcategory of one of my categories
Generate a whole new category
Are the only one of their kind
I make adjustments in coding categories to accommodate my new insights--collapsing categories
with others that may only have one response, teasing out sub-categories or smaller categories from
larger ones. It still might not be perfect the second or even third time through, but each time I move
through the data, categories becomes less vague and a more precise fit with the data.
Once I am satisfied that I have found an appropriate code for each response, I enter the codes into
the “CODE” column on my electronic spreadsheet. Then I highlight the entire data set (make sure
you include ALL columns and rows), click “Sort” (under “Data” in the top toolbar), choose the
"CODE" column, and, voila, all of the data appears in separate little groups according to the codes
just assigned.
Now I can look at each group of responses and add, delete, change, subdivide, or collapse
categories if necessary. I sort again and repeat the process as many times as necessary until I am
satisfied that my categorization reflects the true essence of the data. I ask myself if this is what
respondents were actually trying to collectively convey. Do their voices come through or have I
imposed my own?
An Example Following is a simple analysis spreadsheet for a focus group study I conducted for the University
of Colorado School of Dentistry regarding dental hygiene. I interviewed flossers and non-flossers
in separate groups. Participants were asked who influenced their dental habits, about flossing
follow through, and how they felt about themselves when they flossed. This example includes a
partial list of responses to question 4 (Who influenced you?). Notice the coding key that
corresponds to the letter codes in the Code column. In this example I have not yet sorted the data
by code.
© Copyright. Susan Eliot. July 2011. TheListeningResource Making Comparisons If you faithfully entered face sheet and identification codes with each response, then Excel’s “Sort”
function will enable you to make comparisons among subsets of your data. For example, if you
entered the gender of each participant, then you will be able to compare responses of men to those
of women for each question if you sort all of your data by the "gender" column. You will be able to
do this for each of the face sheet codes entered. Like a kaleidoscope, the picture changes each time
you re-sort.
Below is a sample spreadsheet from a workplace inclusivity study I conducted for the city of
Portland several years ago. During analysis I sorted data by the eight separate face codes (role,
location, work group, etc.) you see in the example. (Remember, you must grab all columns and
rows before hitting the Sort button).
© Copyright. Susan Eliot. July 2011. TheListeningResource © Copyright. Susan Eliot. July 2011. TheListeningResource