If you run a social services nonprofit that provides case management, mentoring, basic needs assistance, adult education, housing, or countless other services, then you should probably collect demographics on your participants. This data can help you learn about your participants and your services. And, it doesn’t take a lot of effort to analyze demographic data to look for really simple patterns.
This post explains
What demographics are
Why demographics are important
How to collect and analyze demographics at your nonprofit
What are demographics?
Demographics is a fancy word for data about your participants.
It’s the labels we use (for better or worse) so we can categorize people (for better or worse) and hopefully help us understand them. Gender, race/ethnicity, marital status, age, income, educational attainment and more are demographics.
Demographics are distinct from other program data we collect such as outputs and outcomes. In other words, demographics focus on the people we serve, not the work we do.
Demographics can go beyond those basic categories. Demographic data can include practically any information about our participants that will help us understand them better and serve them better.
Do they need extra-large or extra-small clothes?
Do they have any dietary restrictions?
Do they have mobility issues that prevent them from coming to our office for coaching sessions?
Do they have young children?
So what good are demographics for my nonprofit?
Let's get this out of the way...
You might collect demographics because someone makes you do it. A government grant wants to know that your program is service the right people, a foundation might want to assess whether you are serving people in a certain zip code. Your board of directors might be interested in children ages 0-5, but not children ages 6-17.
Collecting demographics is a price many nonprofits pay in exchange for program funding.
Beyond “we collect demographics because we have to collect demographics”, there’s value in collecting them.
They help you answer some important questions
Who are we serving? Who are we not serving?
What percentage of our participants are single moms? Does that match our mission?
Who are we serving well? Who can we serve better?
Are people who didn't finish high school able to succeed in our computer skills program? If not, what can we do to improve their success rates?
Demographics can help you predict your participants’ needs
35% of our participants have transportation or mobility issues that make getting to our office hard.
We can try home visits or video conferences.
30% of our participants need extra-large shirts.
We should make a special request for donations of extra large clothing.
70% of the people in our computer skills workshop are single moms with young children.
We need to find a way to address their childcare needs.
Even if you only collect demographics because someone told you to do it, you have the opportunity to use that data to learn about the people you serve and (possibly) improve your services.
How can my nonprofit get started collecting demographics?
Every nonprofit is different, so we’ll discuss a few ways for you collect (more) demographic data at your nonprofit.
Your nonprofit doesn’t collect demographic data
First, start with the basics (gender, race, income, education, household composition, etc).
You can search the internet for "simple demographic survey" for examples. The US Census form is a great, but probably too complex as a starting place. Start with a simpler approach if you can.
Second, add a few additional fields to collect about your participants. Don't get carried away here.
This is data that you think might be informative to answer one of the important questions described earlier.
For a food pantry, you might include: Which of the following dietary restrictions do you have? [check all that apply]. You could list a set of common dietary restrictions.
For a job training program, you might ask: How do you plan to get to our program each day? Bus, Car, Walk, Bike, Other. Please Explain.
Having additional data about your participants, beyond the standard demographic stuff we typically think about, will help you understand their needs, interests, preferences, and strengths.
Third, analyze the data!
That’s easier said than done. But, the point is to find a way to make your data useful. More on data analysis below.
Your nonprofit collects individual participant data
If your nonprofit is already collecting data on individual participants, then you'll have an easier time adding a few demographic fields to your existing data collection procedures.
Of course, you should make sure you are collecting demographic data required by funders and your board. Beyond that, reflect on the important questions.
Do you know who you are serving and who you are not serving?
If not, then that's the best place to start. Add demographic items that will help you paint a picture of your participants. What is the racial and ethnic composition of the people we serve? How many are men, women, or some other gender? What percentage have a college degree or didn't complete high school?
Again, don't get carried away. Start with the key categories that you think impact your participants' lives and interactions with your program. For most human service nonprofits, race , gender, educational attainment, and income matter. But, for many nonprofits, demographics like religion or political affiliation are unlikely to matter (at least not very much). Don't spend precious time collecting that kind of data.
If you already know who your program is serving, then move on to who you are serving well and who you can serve better.
Here, you can examine how successful different demographic groups are in your programs. For example, you might look at the success rates of people with military experience compared to those with none.
You are moving beyond just demographics and starting to connect demographics with program data.
Here you are doing more than just painting a picture of who you are serving. You are trying to determine where you are doing great and where you can do better.
You can also think about additional demographic data that might help you answer these questions. Think about things like program access and mobility issues, skills, interests, goals, etc. This is all data about your participants that can help you understand them and serve them more effectively.
Your nonprofit doesn’t collect individual participant data
Maybe your nonprofit is new, maybe you have a "no questions asked" policy, or maybe data simply hasn't been a priority. For lots of reasons, you might not collect data about individual participants.
You can still collect demographic data and gain valuable information about your participants and services.
One way that you can collect demographic data is by asking your participants to provide some simple demographic information and in a way that makes them comfortable. You will do this by administering a short, anonymous questionnaire.
For example, for one week every 3 months, you could encourage people who use your clothing distribution program to complete a short, voluntary paper questionnaire that might ask for gender, age, race/ethnicity, marital status, and annual income.
It's short so people will actually finish it.
It's anonymous (i.e. you don't ask for names or other identifying info) so people are more likely to complete it and more likely to give accurate responses.
It's paper to make people feel more comfortable answering accurately, and it's easier to print 100 paper copies than it is to pass around the tablet to 100 people.
Participants might place completed questionnaires in a locked box when they are done.
You’ll need to manually input data into a spreadsheet, database, or some other data collection software, but it would probably feel the least invasive for your participants.
You can also ask a few questions focused on how well you are doing & what you could do better, such as:
How convenient are the food pantry hours? (Not At All, Somewhat, Very)
How satisfied are you with food selection? (Dissatisfied, Somewhat Satisfied, Satisfied, Very Satisfied)
What is something we can do to improve service X?
Tip: Learn about creating great surveys and writing Likert Scale questions from prior blog posts.
This isn't precisely demographic data; but it's helpful to understand that single dads want the pantry open in the evening, and people with a certain dietary restriction consistently they are not satisfied with the food.
The data you collect with this approach won't be perfect, but it's WAY better than having nothing.
Simple Demographic Data Analysis
Your first step will be to summarize your data an create simple demographics overview of your participants. In social science, these are called descriptive statistics.
You'll create a breakdown of your participants by gender, race/ethnicity, age, and other key demographic fields you collect. This helps you answer the "Who do we serve? Who do we not serve?" questions.
Table 1 (below) is a simplified example of what you might create. You can see in Table 1 that we present some (fake) descriptive statistics about the participants who provided data in our voluntary survey during the month of July 2023.
Table 1 shows simple percentages and counts of participants by gender, age group, and veteran status.
Table 1: Demographics Overview of Participants Surveyed in July 2023
| Percent | Count |
Gender | | |
Male | 40% | 50 |
Female | 56% | 70 |
Another Gender Identity | 4% | 5 |
Age (Years) | | |
0-5 | 20% | 25 |
6-17 | 16% | 20 |
18-60 | 52% | 65 |
61 or older | 12% | 15 |
Military Status | | |
Active Military | 8% | 10 |
Veteran | 24% | 30 |
No Military Experience | 68% | 85 |
Total Respondents | | 125 |
Table 1 Description: example of simplified descriptive statistics table. Table includes percent and count by Gender, Age (Years), and Military Status. There were 125 total respondents. 40% are male, 56% are female, and 4% are another gender identify. 20% are age 0-5, 16% are age 6-17, 52% are age 18-60, and 12% are 61 or older. 8% are active military, 24% are veteran, and 68% have no military experience.
The overview provided by Table 1 gives us a snapshot of who we are serving. For example, we see that nearly one-third of our participants are active military or veterans. That seems like a lot. Perhaps we need to figure out if they have special needs or unique strengths that we can incorporate into our work.
Some questions you should ask about your descriptive statistics
Is this what we expected?
Why aren’t we serving more people who are X?
What can we learn if we compare this year's data to last year?
Comparing Categories
The second analysis we can do is to compare categories. For example, you might compare how single parents and others view the convenience of your pantry hours. Or, you can compare success counts and success rates across different groups.
This type of analysis helps you understand who you are service more and less effectively (or their opinions about your services), and it leads you to questions focused on whether and how you could change your services to improve.
For example, in Table 2 (below) we compare the average satisfaction rating of food pantry hours by household composition.
We can see that single parent households have the lowest average satisfaction rating, 2.15, and they are they largest group (120 responses). The satisfaction score of dual parent households is much higher, at 3.25, but they are a relatively small group (25 responses).
We can also see that multi-adult (no kids) households have a higher average satisfaction score, 3.50, than single adult (no kids) households, 2.65.
Finally, other household compositions have an average score of 2.80.
Who are we serving well? Multi-adult (no kids) and to a lesser extend dual parent households
Who can we serve better? Single parent and single adult (no kids) households.
It might be worthwhile to ask our members of lower scoring groups how pantry hours can be adjusted to better meet their needs.
Table 2: Average Satisfaction Rating of Food Pantry Hours by Household Composition(1)
| Average Score | Responses |
Single Parent Household | 2.15 | 120 |
Dual Parent Household | 3.25 | 25 |
Single Adult Household (no kids) | 2.65 | 80 |
Multi-Adult Household (no kids) | 3.50 | 50 |
Other Household Composition | 2.80 | 35 |
| | |
Total | 2.66 | 310 |
(1) How satisfied are you with the hours of operation of our food pantry? 1. Unsatisfied, 2. Somewhat Satisfied, 3. Satisfied, 4. Very Satisfied.
Learn More About Using Demographics at Nonprofits
Check out our other posts about demographics for nonprofits.
Learn More About Nonprofit Data Management
This post is part of our nonprofit data bootcamp series. Check out the complete list of nonprofit data bootcamp topics with links to other published posts.
A Note About Data Collection Software
With countbubble, you can collect virtually any demographic data about you participants. Our Add Participant form includes a lot of the basic demographic fields by default. You can also add custom fields so you can collect the demographic data that you need.
If you are shopping for case management or data collection software for your nonprofit, make sure that you can:
Track the demographics that you absolutely need
Track other demographics that might help you understand your participants and programs
Reporting your impact is hard when you’re juggling spreadsheets. countbubble makes it easy so you can focus on your mission.
Learn how countbubble helps nonprofits simplify data collection and reporting. Email us contact@countbubble.com or sign up for email updates on blog posts, product news, or scheduling a demo.
Founder, CountBubble, LLC
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