Data Collector Question Types
- Multiple Choice allows respondents to select one answer from a pre-determined list. Examples include program site, or using a 1-5 scale to strongly disagree or strongly agree with a statement. You can also add "Other" as an option at the bottom of your list of choices. This question type can collect data as Numbers or Strings.
- Checkboxes allows respondents to select one or more answers from a pre-determined list. This question type collects data as a List data type.
- Dropdown functions the same as Multiple Choice, allowing respondents to select one answer from a pre-determined list. The main difference is that the formatting of Dropdown questions can more easily accommodate large lists of potential options. Example include selecting from all 50 states, or from grade levels K-12. This question type can collect data as Numbers or Strings.
- Yes/No collects data in a true/false (or Not Applicable) Boolean data type. You can also click "Add Conditional" at the bottom of a Yes/No question to create 1 or more conditional subquestions that will only display on your survey when respondents select "Yes" to the Yes/No question.
- Short Answer allows respondents to answer by entering numbers and/or text themselves, rather than selecting from a predetermined list of answers. Examples include name, age, and a question such as "If you have allergies, please describe them here." This question type can collect data as Numbers or Strings -- if the question is set to the Number data type, then the question will only allow respondents to type numbers in the answer field.
- Paragraph allows respondents to answer by writing text themselves, rather than selecting from a predetermined list of answers. Designed for open-ended responses like feedback and testimonials, this question type collects data as a String data type. You can click "Enable Automatic Stories" to automatically turn every response to this question into a unique Story in the Stories section of the UpMetrics platform. This is a powerful way to help organize and analyze qualitative data.
- Date Picker, as the name suggests, allows respondents to select a specific date (day, month, and year). This question type collects data as a Date data type. The Data Collector automatically records the submission time of each survey response, so the Date Picker can be especially useful if you want to allow respondents to backfill information and/or submit data at a later date.
- Section Header allows you to create headers with descriptions to help organize and give context to your survey. Section Headers are not questions and therefore no data is collected through them.
Survey Design Best Practices
Here are 10 steps to set yourself up for success with surveys. Taking time to be intentional at the beginning of the process can save you a lot of time -- and make your results much more actionable -- in the long run.
- Determine the goal and purpose of your survey. It is crucial to begin with the end in mind. Design your survey by asking yourself, “What do I want to learn from the survey data?” or “What is the story of impact I want this survey to help me tell?” This will also help you share why the survey matters when you introduce it to participants.
- Create different surveys for different stakeholders. Based on the goals you define, you may realize there are different things you want to learn from different stakeholders you engage with -- such as current program participants, program alumni, participants’ families, staff, donors, and volunteers. While many of the questions you ask might be the same or similar, in some cases it can be more effective to create a separate survey for each stakeholder group.
- Consider how often you do surveys. Survey frequency should match the goals of the survey. If your goal is to better understand new program participants so that you can better serve them, then look to include survey questions as part of the program’s registration or enrollment process. If your goal is to track changes over time, you should consider doing pre- and post-surveys. You might also consider linking surveys to key milestones or activities. For example, use a participant satisfaction survey when participants are exiting the program, and survey staff members ahead of professional development or strategic planning sessions.
- Collect identifiable data if you plan to sync with other data sources. In order to connect your survey data with other data sources, you need to collect the same unique identifier as part of each survey and/or data source. Popular unique identifiers used for linking different data sources including asking participants for their First Name, Last Name, and Date of Birth because these can be combined into a unique identifier; or site name for programs. Surveys that are done anonymously can still be incredibly valuable, as long as it meets your goals for the survey.
- Choose selection fields rather than open text fields when possible. Selection fields -- such as multiple choice questions and dropdown menus -- ensure that survey responses are collected in a consistent format that maximizes the data’s opportunities for analysis. For example, including selection fields for gender or gender identity as “Male” and “Female” can prevent participants from making typos or creating separate categories for “female” (all lower case) and “Female” (capitalized). And you can always include an “Other” option with an open text field for participants to describe aspects of their identity in their own words if they’d prefer.
- Include questions that can help you leverage publicly available data. Asking participants for their home zip code, city, and/or county creates the opportunity to compare the demographics of your participants to the overall demographics of the communities they come from. This can support your ability to highlight the access and equity impacts of your work. (If applicable, asking participants for the name of the school they attend can also be helpful.)
- Limit survey length to increase the quality and quantity of responses. Surveys as short as 3 or 4 questions can be really powerful, in part because their brevity makes them easier to use. With this in mind, don’t ask program participants for information you already have about them, beyond what is needed for identifying and matching them to other data.
- Review survey question wording to be as clear and concise as possible. Prioritizing the survey respondent’s experience is one of the best ways to ensure high-quality survey data. As you read over each survey question, make sure it will be understood by the intended audience -- especially if the survey is for young children or English Language Learners.
- Schedule survey time and follow up with people to increase total survey responses. Set aside program time for participants to fill out surveys and/or make it part of registration. Rather than being something to “get out of the way,” a well-designed survey should prompt participants to be reflective at important phases of their program journey (such as orientation or graduation). One or two weeks after launching a survey, A quick reminder note is often all it takes to get back on people’s radar.
- Analyze survey data so that you can learn and take action. Once you have collected all of the survey responses, the next step is to analyze that data so you can start to learn from it to inform decision making, resource allocation, and fundraising. People will likely feel that the time they spent filling out or collecting surveys was worth it when they see survey data being put to work.