We’ve already discussed the difference between outputs and outcomes, so let’s take a minute to review the differences in quantitative versus qualitative data. An easy trick I use to remember the difference:
- Quantitative = Quantity = Numerical data
- Qualitative = Quality = Testimonial data
As you build your evaluation processes, it’s important to consider collecting both types of data. While numerical (quantitative) data is effective in demonstrating need and impact; qualitative stories humanize your programs by putting a real life behind those numbers. Consider this:
Each year, our programs impact 5,000 individuals experiencing homelessness. Of those, 85% seek services beyond housing (food banks, healthcare, navigation) and 60% move into permanent housing within 90 days.
Not bad, right? Here, we used quantitative data to demonstrate reach and impact. Now, consider adding just a few more sentences of qualitative data…
Each year, our programs impact 5,000 individuals experiencing homelessness. Of those, 85% seek services beyond housing (food banks, healthcare, navigation) and 60% move into permanent housing within 90 days. Carla, a resident in our New Hope Women’s Shelter, came to our doors 6-months ago. She ended up on the streets after losing her job during COVID and, with little savings, lost her apartment. She shares, “I don’t know what I would have done without New Hope. They helped me find a job, apply for services, and get back on my feet. And I just found out I am approved for a rent-stabilized apartment! They saved my life.”
Pairing your numbers with real life testimonials lets your reader see the person behind the data. Behind every grant review team is a person who will read this narrative and will imagine this woman who was lifted off the streets to find stability.
Examples of Quantitative Data:
- # of unique individuals served
- % of clients who are satisfied with your services
- Demographic data (i.e. % of clients of a specific race/ethnicity, gender, age, etc.)
Examples of Qualitative Data:
- Testimonials
- Success stories
- Quotes or Photos
- Interviews or Observations
Collecting both quantitative and qualitative data does not need to be complicated. A client satisfaction survey or your pre- and post-surveys can include your demographic questions, program-specific questions to assess outcomes, and open-ended questions where your clients can provide feedback. Encourage staff to share success stories or observations they’ve made that demonstrate impact. Interview those grateful clients to learn more about their experience. With approval, create a nicely formatted one pager for each success or impact story that can be easily shared with your grant applications.
The Takeaway: Data comes in many forms and each plays an important role in assessing your program’s success. But remember, the data is only useful if you actually use it. Establish your processes early, and—Collect, Track, Aggregate, Analyze. Ongoing data management is critical to objectively evaluating your program and sharing relevant data with your funders. Good luck and happy writing!
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