Designing for Nonprofits

Nonprofit friends, planning to collect data soon? Remember: Your questions shape your data—but they don’t always get you what you need. Imagine this: You are filling out a border form, and it asks: "Do you exceed duty-free allowances per person?" The only answers are Yes or No. For someone who didn't bring any goods, selecting No implies they did get something but stayed within the limit. The question doesn't account for people for whom the question is irrelevant, forcing them to provide inaccurate information. Now think about your data collection tools (say, your last survey): ● Are your questions boxing people into answers that don't reflect their reality? ● Are you assuming experiences that don't apply to everyone? ● Are you unintentionally excluding voices by limiting response options? Poorly worded questions = bad data = flawed decisions = a loss of trust. Here are three examples of common pitfalls: ● Assumptions baked into questions Example: “What barriers prevent you from attending our events?” assumes the respondent knows about your events and faces barriers. A better question: “Have you heard of our events?” followed by, “What barriers, if any, prevent you from attending?” ● Excluding relevant options Example: “Which of these programs have you used?” but leaving out “I haven’t used any.” Guess what happens? People pick a random answer or leave it blank, and now your data is a mess. ● Vague questions Example: “On a scale of 1-5, how satisfied are you with our communication?” Without specifying—emails? Social media? In-person?—responses will be all over the place. Your questions are your bridge to listening and understanding. Two things to remember here (and by no means this is the complete list): ● Plan your survey – the why, what, how, when, what-next… before jumping to design ● Use inclusive language, providing options like "Does not apply.", wherever relevant. Ensuring people responding to it can see themselves in the questions and responses is the only way to give them the true choice of what and how much they want to share with us. Please reach out if you want to plan a Survey Kaleidoscope workshop with your team on your upcoming survey (for context, it's a workshop where we solely plan the survey collectively - every single element of how to ensure a successful survey happens) #nonprofits #nonprofitleadership #community

Employee engagement surveys are broken.   There, I said it.   Companies spend thousands each year on surveys. Promising insights into how their people feel.   Yet the results are often inaccurate, incomplete, and unreliable.   And why is this?   1. Mistrust of anonymity Employees open up when surveys feel safe. But 45% think HR can track their answers, so they hold back. Reframe surveys as confidential and explain how the data is used.   2. Outdated survey design Generic surveys miss the mark. Every company is different, so should its questions be. Tailor surveys to your culture and goals to get useful insights.   3. Timing matters Annual surveys? Outdated. Engagement shifts all year. Regular pulse checks give a clearer picture.   4. The trust gap Nothing kills engagement like ignored feedback. If employees don’t see change, they stop caring. Share results, communicate next steps, and follow through.   How do we fix it?   - Run shorter, more frequent pulse surveys. - Focus on patterns, not individual responses. - Follow up with action and communicate results.   Employee engagement builds trust. Not simply collecting data.   Are your surveys doing that?

Your customer satisfaction survey is more than a score. Here's how one client used it to leverage a strength and fix a major pain point: 1. Analyze comments Review the survey comments and identify themes for each rating. I can review about 100 surveys by hand in 30 minutes. AI software does this in seconds. Here's what my client's survey comments revealed: 💪 Strengths: employees were frequently mentioned for caring service ❌ Weaknesses: My client discovered that one particular process was a major pain point. Customers felt it was too difficult and inconvenient. 2. Investigate findings Dig deeper to learn more about the strengths and weaknesses the survey helped reveal. Observing employees and workflows is often the best way. My client's observations deepened two insights: 🙏 Employees frequently mentioned in surveys were great at building genuine rapport. Their techniques were easily shared with the rest of the team. ⏱️The painful process was inefficient. The team made changes that made the process more efficient and easier for customers. 3. Experiment Implement new ideas and track the results to see if they work. My client combined observations, anecdotal feedback from customers, and new survey results to assess how the rapport techniques and new process were working. Both were a hit! The painful process in particular stood out. Many customers mentioned how happy they were with the changes. My client had taken a pain point and turned it into a strength! Bottom line --> Follow this process to get more value from your surveys: 1. Analyze comments 2. Investigate findings 3. Experiment

Designing effective surveys is not just about asking questions. It is about understanding how people think, remember, decide, and respond. Cognitive science offers powerful models that help researchers structure surveys in ways that align with mental processes. The foundational work by Tourangeau and colleagues provides a four-stage model of the survey response process: comprehension, retrieval, judgment, and response selection. Each step introduces potential for cognitive error, especially when questions are ambiguous or memory is taxed. The CASM model -Cognitive Aspects of Survey Methodology- builds on this by treating survey responses as cognitive tasks. It incorporates working memory limits, motivational factors, and heuristics, emphasizing that poorly designed surveys increase error due to cognitive overload. Designers must recognize that the brain is a limited system and build accordingly Dual-process theory adds another important layer. People shift between fast, automatic responses (System 1) and slower, more effortful reasoning (System 2). Whether a user relies on one or the other depends heavily on question complexity, scale design, and contextual framing. Higher cognitive load often pushes users into heuristic-driven responses, undermining validity. The Elaboration Likelihood Model explains how people process survey content: either centrally (focused on argument quality) or peripherally (relying on surface cues). Users may answer based on the wording of the question, the branding of the survey, or even the visual aesthetics rather than the actual content unless design intentionally promotes central processing. Cognitive Load Theory offers tools for managing effort during survey completion. It distinguishes intrinsic load (task difficulty), extraneous load (poor design), and germane load (productive effort). Reducing the unnecessary load enhances both data quality and engagement. Attention models and eye-tracking reveal how layout and visual hierarchy shape where users focus or disengage. Surveys must guide attention without overwhelming it. Similarly, the models of satisficing vs. optimizing explain when people give thoughtful responses and when they default to good-enough answers because of fatigue, time pressure, or poor UX. Satisficing increases sharply in long, cognitively demanding surveys. The heuristics and biases framework from cognitive psychology rounds out this picture. Respondents fall prey to anchoring effects, recency bias, confirmation bias, and more. These are not user errors, but expected outcomes of how cognition operates. Addressing them through randomized response order and balanced framing reduces systematic error. Finally, modeling approaches like like cognitive interviewing, drift diffusion models, and item response theory allow researchers to identify hesitation points, weak items, and response biases. These tools refine and validate surveys far beyond surface-level fixes.

Drawing from years of my experience designing surveys for my academic projects, clients, along with teaching research methods and Human-Computer Interaction, I've consolidated these insights into this comprehensive guideline. Introducing the Layered Survey Framework, designed to unlock richer, more actionable insights by respecting the nuances of human cognition. This framework (https://lnkd.in/enQCXXnb) re-imagines survey design as a therapeutic session: you don't start with profound truths, but gently guide the respondent through layers of their experience. This isn't just an analogy; it's a functional design model where each phase maps to a known stage of emotional readiness, mirroring how people naturally recall and articulate complex experiences. The journey begins by establishing context, grounding users in their specific experience with simple, memory-activating questions, recognizing that asking "why were you frustrated?" prematurely, without cognitive preparation, yields only vague or speculative responses. Next, the framework moves to surfacing emotions, gently probing feelings tied to those activated memories, tapping into emotional salience. Following that, it focuses on uncovering mental models, guiding users to interpret "what happened and why" and revealing their underlying assumptions. Only after this structured progression does it proceed to capturing actionable insights, where satisfaction ratings and prioritization tasks, asked at the right cognitive moment, yield data that's far more specific, grounded, and truly valuable. This holistic approach ensures you ask the right questions at the right cognitive moment, fundamentally transforming your ability to understand customer minds. Remember, even the most advanced analytics tools can't compensate for fundamentally misaligned questions. Ready to transform your survey design and unlock deeper customer understanding? Read the full guide here: https://lnkd.in/enQCXXnb #UXResearch #SurveyDesign #CognitivePsychology #CustomerInsights #UserExperience #DataQuality

Writing your own survey? Stop making these survey mistakes… I’ve reviewed dozens of surveys from brands and consultants who are taking a DIY approach to survey-based research. While I love seeing more companies using data and original insights in their content, there are some common pitfalls with surveys that can undermine your efforts. Here are the biggest mistakes I see—and how to avoid them: 1️⃣ Too many open-ended questions While open-ended questions can be valuable, overusing them can overwhelm respondents and make it harder to extract actionable insights. Many of these could easily be reworked as multi-select options, which are quicker to answer and easier to analyze. 2️⃣ Not tailoring questions to respondents Failing to properly segment your audience or filter questions (e.g., asking irrelevant questions to people outside a specific group) frustrates respondents and skews your data. Make sure your survey flows logically and adapts based on responses. 3️⃣ Using jargon or acronyms Don’t assume your audience speaks the same language as your internal team. Spell out acronyms and avoid industry jargon—it ensures clarity and a better response rate. 4️⃣ Combining ideas in one question or response option Questions or responses like “Do you think A and B?” are problematic because a respondent might agree with one but not the other. Keep questions and responses focused on one idea at a time to get accurate answers. 5️⃣ Making surveys too long Long surveys lead to drop-offs or rushed responses. Respect your respondents' time—focus on what you really need to know and keep it concise. 6️⃣ No narrative structure—just a dump of internal questions One of the most common mistakes I see is surveys that lack a clear story arc. Instead of building around a strong theme or hypothesis, it’s just a long list of random questions from different stakeholders. The result? Disconnected data that's hard to turn into compelling content. When designing your survey, think about the story you want to tell. Build your questions to support that narrative. Key Takeaway: Thoughtful design makes a huge difference in the quality of your insights—and ultimately, the impact of your content. Have you seen any survey mistakes that drive you nuts? Or tips for improving them? #SurveyTips #OriginalResearch #ContentStrategy Hi, I'm Becky. 👋 My clients have garnered 80+ media mentions, 2-3X the leads, and over 250K in free advertising from branded research💰 Interested in branded original research to boost your marketing KPIs? DM me and we'll talk. 🙂

Surveys should be used to see what you did wrong, not show what you got right. Don’t ask: Did you like this? Would you recommend it? Are you more confident? Ask: - what % of the training did you spend as an active participant? - what % did you spend practicing real work? - how realistic was the practice? - how difficult did the practice feel to you? - how did the feedback you received improve your learning? - how clear are the expectations regarding what to apply on the job? - how important is it to you that you hit these expectations? - how supported do you feel to apply what you learned on the job? —— Surveys do more than inform you after a training. They also signal to the designers what you find to be most valuable. If you signal all you care about is CSAT, designers will prioritize engagement over effectiveness.

“How was school?” “Good.” “How was your day?” “Good.” Anyone else try having a conversation with their kids and get these one-word answers? In defense of kids — it’s not their fault. Those questions are *terrible*. You get responses at the level of the questions you ask. Ask great questions, get great data. Ask lazy ones… you get “good.” (And okay, I have a middle schooler — so “sometimes” you get great data :) Over time, I’ve become a Jedi at asking questions my kids can’t brush off: 🗣️ “Tell me the most interesting thing you’ve learned in math lately.” 🗣️ “What happened between you and ___ today?” When I became more intentional about how I asked, they became more open. They saw I *wanted* to listen. And that’s the same principle in research and customer insights. When we send out surveys packed with 10 nominal features, rating scales, and matrix grids… Do we sound like we *really* want to listen? No. When we ask, “How likely are you to adopt?” Is that enough to *really* know their intent? No again. Try questions that uncover the why behind behavior: 👉 “How are you solving this problem today?” 👉 “What’s the hardest part of using your current system?” That’s where the real insight lives. If you’re building surveys, questionnaires, or interview guides, take the time to: ✅ Mix open and closed questions ✅ Be clear on what you want to learn ✅ Review them critically — do they invite honesty or quick clicks? You get out of your research the same thoughtfulness you put into your questions. Ask better. Listen deeper. Get real answers. P.S. How great was this post? (Terrible question. See my point?) #marketresearch #customerinsights #surveydesign #edtech #leadership #intentionality

Stop Wasting Customers’ Time with Meaningless Surveys Let’s talk about surveys—specifically, those poorly designed ones that go nowhere. You know the ones: vague questions, no clear purpose, and no real action tied to the results. They frustrate your customers and waste everyone’s time. If you’re sending out a survey, it should work for you and your customers. Here’s the framework I follow when designing surveys that drive meaningful outcomes: 1. Define the Goal: Why are you sending this survey? What decision will the responses inform? Be laser-focused on what you need to learn. 2. Keep It Actionable: Every question should directly tie to something you can change, improve, or build. If you can’t act on it, don’t ask it. 3. Stay Short and Sweet: Respect your customers’ time. Prioritize only the questions that give you the most valuable insights. 4. Communicate the ‘Why’: Tell your customers how their feedback will be used. This builds trust and increases engagement. 5. Close the Loop: Share what you learned and what actions you’re taking. Feedback is a two-way street—make it feel that way. Surveys can be a goldmine for improvement, but only if they’re designed with intention. Don’t make your customers guess what their answers are for. What’s one change you’ve made recently based on customer feedback? Let’s chat!