Event Feedback Collection

Stakeholder Satisfaction: If You’re Not Measuring It, You’re Guessing __________________________________________________________________________________ Are you 100% confident that your stakeholders are happy? If you're not keeping a constant eye on their satisfaction levels, you are shooting in the dark. And let's be honest, that's not gonna end well, is it? Managing stakeholders isn't just a numbers game. It's about making sure every person at the table feels seen, heard, and in sync. If they don’t align, you can go all out and still find yourself with a disappointing outcome. The Big Misstep Most Managers Make 👉 They Focus on Outputs, Not Outcomes: Completing tasks is enough. Think again, is it ? If stakeholders aren’t satisfied with how you deliver, you’re losing their trust. 👉 They Don’t Ask the Hard Questions: Managers often dread feedback as it may uncover uncomfortable realities. However, the truth doesn’t disappear by ignoring it. 👉 They Measure Satisfaction by Silence: No complaints? You should worry. Silence often signals disengagement—not approval. Simple Methods to Measure Stakeholder Satisfaction ✅ Pulse Surveys: Use concise, focused surveys to collect valuable insights. Ask questions like: “How satisfied are you with the clarity of my communication?” “Am I meeting your expectations on deliverables?” ✅ One-on-One Check-Ins: Don't shy away from those heart-to-hearts with your main stakeholders. Just throwing out a, "Hey, where can I step up my game?" is a sure shot step to some good strategic conversation. ✅ Stakeholder Scorecards: Have a scoring system to evaluate the quality of relationships using criteria such as trust, responsiveness, and alignment with objectives. ✅ Analyze Behaviors, Not Just Words: Read the room. Are stakeholders proactively engaging with you, or do they seem distant and unresponsive? ✅ Feedback Loops: Clearly demonstrate that feedback results in change. When stakeholders notice that you are implementing changes basis their feedback, they are more engaged. As an executive coach, I coach managers that stakeholder satisfaction isn’t a one-time achievement—it’s a dynamic process. Measuring it consistently allows you to adapt, align, and lead with impact. Stakeholders play a huge part in your corporate success. The Bottom Line If you're not assessing stakeholder satisfaction, you're risking important relationships. Take charge, gather the necessary data, and ensure that every interaction is meaningful.

We’ve helped over 3,000,000 attendees check in to events. Here’s what we learned. 1. Coach the check-in staff on how to greet attendees. That’s far more important than how to use the tech. 2. A 2-5 minute line is a good thing. Attendees chat. It warms up the ‘networking juice’. 3. Create a 'service desk' AND put it off to the side. Get people with issues out of line. 4. Let attendees make basic edits from the Kiosk - it will reduce service desk requests by 90%. 5. Make sure your platform supports offline check-in if the internet does go down. 6. If you have a big reg area, have little flags that check-in staff can raise if they need a printer tech to come over and restock. 7. Pre-printing the stock significantly increases print speed onsite. 8. The biggest attendee experience improvements came from events that consolidated registration and badge printing into a single platform. E.g. Accelevents 9. Look for what could go wrong. Story - we were running check-in for an event with 40 kiosks. The power strips were daisy-chained together. One of the check-in staff had a busy foot that unplugged the extension cord TWICE and took out half the printers. 10. Design your badges and do your test prints at least 30 days in advance but still order at least 100 badges for test prints on site. 11. Test crazy-long names, companies, and job titles on your badges. Your badge software should automatically adjust the font size to prevent text wrap. 12. Different roles require different colored shirts. Much easier to find help and route attendees. E.g. Service desk, printer tech, decision maker. 13. Have a plan for walk-ins. 14. Make sure everyone knows who can make executive decisions AND how to find that person. 15. Have a backup for 👆. Reminder: On event day, you can’t do everything. Empower your team to make decisions. There isn’t time to ‘find you’. And finally- Have fun. Attendees pick up on your energy. What did I miss? #events #eventmanagement #eventmarketing

User experience surveys are often underestimated. Too many teams reduce them to a checkbox exercise - a few questions thrown in post-launch, a quick look at average scores, and then back to development. But that approach leaves immense value on the table. A UX survey is not just a feedback form; it’s a structured method for learning what users think, feel, and need at scale- a design artifact in its own right. Designing an effective UX survey starts with a deeper commitment to methodology. Every question must serve a specific purpose aligned with research and product objectives. This means writing questions with cognitive clarity and neutrality, minimizing effort while maximizing insight. Whether you’re measuring satisfaction, engagement, feature prioritization, or behavioral intent, the wording, order, and format of your questions matter. Even small design choices, like using semantic differential scales instead of Likert items, can significantly reduce bias and enhance the authenticity of user responses. When we ask users, "How satisfied are you with this feature?" we might assume we're getting a clear answer. But subtle framing, mode of delivery, and even time of day can skew responses. Research shows that midweek deployment, especially on Wednesdays and Thursdays, significantly boosts both response rate and data quality. In-app micro-surveys work best for contextual feedback after specific actions, while email campaigns are better for longer, reflective questions-if properly timed and personalized. Sampling and segmentation are not just statistical details-they’re strategy. Voluntary surveys often over-represent highly engaged users, so proactively reaching less vocal segments is crucial. Carefully designed incentive structures (that don't distort motivation) and multi-modal distribution (like combining in-product, email, and social channels) offer more balanced and complete data. Survey analysis should also go beyond averages. Tracking distributions over time, comparing segments, and integrating open-ended insights lets you uncover both patterns and outliers that drive deeper understanding. One-off surveys are helpful, but longitudinal tracking and transactional pulse surveys provide trend data that allows teams to act on real user sentiment changes over time. The richest insights emerge when we synthesize qualitative and quantitative data. An open comment field that surfaces friction points, layered with behavioral analytics and sentiment analysis, can highlight not just what users feel, but why. Done well, UX surveys are not a support function - they are core to user-centered design. They can help prioritize features, flag usability breakdowns, and measure engagement in a way that's scalable and repeatable. But this only works when we elevate surveys from a technical task to a strategic discipline.

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

Many manufacturers today have invested heavily in data infrastructure: PLCs, SCADA, MES, historians, dashboards. Yet when you dig into the architecture, especially on high-speed or complex lines, a common gap emerges. Critical short-duration events are not being captured accurately or with enough context to drive actionable insights. This is not due to lack of technology. Modern PLCs, edge devices, and platforms are more than capable. The problem is architectural. Many plants still rely on SCADA and MES systems that poll PLCs at relatively slow intervals, typically 1000 milliseconds. That polling interval creates a blind spot. Meanwhile, PLC scan cycles typically run between 3 and 5 milliseconds. In high-speed lines, servo-based systems, robotics, and motion applications, critical events happen on sub-second timescales. Operator inputs, cascading alarms, motion faults, and intermittent product jams often occur and resolve in less than a second. If these events are not buffered properly at the PLC layer or edge, they are simply lost to higher-level systems. This leads to a familiar pattern. • OEE reports that do not explain why downtime occurred • Fault logs that fail to show which fault triggered first • Product loss and yield issues that cannot be traced to specific machine behaviors • Maintenance teams spending hours reviewing PLC logic and guesswork post-mortems The bigger risk is that leadership decisions get made on incomplete data. Continuous improvement efforts stall. Predictive maintenance strategies fail to get off the ground. McKinsey & Company data suggests that manufacturers who close this gap and build modern data architectures can reduce unplanned downtime by up to 50% and improve productivity by 10 to 20%. But this requires capturing data with the right fidelity, at the right layer, and with the right context. From my experience, this is true not only on high-speed systems where products are moving faster than the eye can see and $100,000 high-speed cameras are used to diagnose failures. It is equally true on slower lines where operators and engineers struggle to explain recurring issues because key data is missing. If you are running below 60 percent OEE, you likely have more foundational work to do first. But if your goal is to move from reactive to proactive operations, to reduce variability, and to enable next-generation capabilities like advanced analytics and machine learning, this is an architectural conversation that needs to happen. I work with manufacturers who want to modernize these architectures and close this visibility gap. If you are looking at these challenges or want to benchmark your current architecture against best practices, feel free to reach out. I would be happy to share insights and lessons learned.

#Patient_Satisfaction! Are we Confusing Hospitality with Healthcare Outcomes? Patient satisfaction surveys, often measure "hospitality" experience, factors such as staff friendliness, wait times & facility cleanliness, rather than meaningful health outcomes. While these elements contribute to patient comfort, they are poor proxies for the technical quality & clinical effectiveness of care. Research reveals significant methodological challenges in these tools: · Lack of Discriminative Power: responses to different survey questions (e.g. about communication, courtesy & time spent) can be highly correlated, suggesting they capture a general impression rather than providing specific, actionable feedback for providers to improve upon. · Ceiling Effects: Most providers cluster at the top of the scoring scale, which limits the metric's ability to distinguish genuinely high-performing providers from average ones. · Perverse Incentives: Perhaps most critical, tying reimbursement to satisfaction scores. This may lead to clinically questionable decisions, such as the overprescription of antibiotics for viral illnesses or the approval of unnecessary imaging tests, primarily to appease patient expectations. Focusing purely on satisfaction can lead prioritize patient desires over clinical needs, which can cause harm to patients & drive up healthcare costs without improving health. The Proposed Alternative: Measuring What Truly Matters Health Outcomes Measurement like the measure sets proposed by International Consortium for Health Outcomes Measurement (ICHOM) represent a superior & patient-centered framework. Specific sets for specific conditions (like diabetes) focus on what truly matters to patients' long-term health. These sets track a comprehensive range of data, including disease-specific outcomes, patient-reported quality of life, functional status & well-being. This approach measures whether care actually improves health, rather than just whether the service was pleasant. It's crucial to distinguish between three types of metrics: · Patient Satisfaction measures a patient's feelings about their care experience, heavily influenced by "hospitality" factors & personal expectations. · Patient Experience measures what actually happened during the care encounter, such as the clarity of communication or the coordination between providers. · Health Outcomes measure the results of care, including clinical results, functional status & quality of life. The Path Forward Healthcare must evolve from measuring satisfaction to tracking success through meaningful outcomes. The recommended path involves replacing satisfaction-based incentives with outcomes-focused models, integrating Patient-Reported Outcome Measures (PROMs) into routine care & leveraging technology to collect & analyze this more robust data. This shift aligns measurement with the ultimate goal of healthcare "improving patients' health and quality of life" #ارطبون_التغيير

BCG just published research showing that 60% of pharma companies are dissatisfied with their NBEx engines. Commercial teams are especially frustrated. The main problems they identified will not surprised anyone in omnichannel (but great job in quantifying these): - Does not integrate across all channels - Difficult to measure business impact - Insights do not reflect real-time data - Does not fully integrate all data - Algorithm does not provide useful recommendations Now: events are the richest omnichannel fuel pharma has. Think about it. Congresses generate thousands of HCP interactions. Webinars capture real-time engagement and Q&A insights. Advisory boards reveal sentiment and priority shifts. Medical education sessions show knowledge gaps and interests. Yet most pharma companies treat this goldmine like trash. We integrate attendance numbers if we are lucky. We ignore engagement scores, throw away Q&A insights, and upload congress data two months after the event when the momentum is dead. Then we act surprised when our NBEx engines can't deliver meaningful recommendations...the solution isn't buying a better algorithm. It's feeding your NBEx engine with the right fuel. Real-time congress engagement data flowing directly into your CRM. Webinar interaction scores segmented by therapeutic interest. Advisory board sentiment analysis mapped to accounts. All of it structured, reconciled, and available instantly. Not two months later. Not just headcount metrics. Events generate the richest HCP behavioral data in pharma. Fix your event data strategy first. Your NBEx engine will follow. Source: Boston Consulting Group (BCG) https://lnkd.in/exSKPMGT Ashkan Afkhami Ivan D'Avanzo Ahad W. Siwei He Andrew Romine

Today we're announcing Event Intelligence. A new feature that's going to fundamentally change how companies approach events. Companies spend millions on events every year. But most show up blind. They don't know which prospects are attending. They don't know which active deals are walking the floor. They don't know which customers are three booths away. Popl, at its core, is a data company. And now, with just a conference name as input, our proprietary data engine combines first-party event data, partner datasets, marketing signals, historical attendance patterns, and AI predictions to give you something that's never existed before: a complete picture of who's going to be at an event, before you even book your flight. Here's how it works: - Within any Popl Campaign, you can now request an Event Intelligence dataset for that event. - Our data engine and AI agents generate the full exhibitor list, including booth numbers. - We then run Popl enrichment on each company—data like annual revenue, headcount, industry, and more. - Finally, we cross-reference each exhibitor with your CRM, providing full context and bucketing each into one of four categories: → New Account – company isn't in your CRM yet → Prospect – company exists in your CRM, but no active deals → In-Progress Deal – there are active opportunities being worked → Current Customer – closed-won deals, meaning they're an active customer Each company also gets an AI-generated context summary, so your team has readable intel at a glance. It's time we make events a predictable revenue channel. Not a gamble. Solve event lead capture and get event intelligence all-in-one: https://hubs.la/Q042bz6Z0

Earlier this week, I saw something that might end one of my frustrations as an audience member watching a speaker: scribbling illegible notes while trying to capture a bad phone photo of an interesting PowerPoint slide. At Cvent Connect in San Antonio, thousands of attendees experienced a breakthrough in real-time speech transcription. As speakers talked, their words appeared instantly in the event app with virtually zero lag. When someone heard something worth remembering, they simply tapped a button—and the system captured a full minute of context around that moment. According to McNeel Keenan, Cvent's VP of Product Management, a future version of the app will capture the accompanying visual, like a PowerPoint slide, along with the text. I like this. No scribbling in the dark required. No trying to remember what my cryptic note was supposed to mean later on. Instead, one click saves a few paragraphs of what the speaker said, labeled and summarized by AI. This feature has another benefit: it reduces cognitive load. When you're simultaneously trying to listen, write, and photograph content, your brain is managing multiple competing tasks. What happens? You often miss the insights you're trying to capture. Cvent's solution eliminates this friction. Attendees can focus 100% of their cognitive capacity on listening and engaging, while AI handles the capture, summarization, and organization. From a behavioral perspective, there's something even more valuable happening: every tap creates revealed preference data. Instead of relying on sketchy post-event surveys, organizers can see exactly which moments resonated enough for people to save them. As a frequent speaker, I know when I see phones go up to capture my slides that I've hit something important to the audience. But after an hour on-stage, I can't always remember in detail which ideas sparked that response. Or, which didn't. Now, that engagement becomes quantifiable data. The friction we've accepted as "just how conferences work" isn't inevitable, it's a design problem waiting for a solution. What are your conference pain points? Can technology fix them?

HubSpot has just released the ability to associate marketing events with more of the CRM data model. Why this matters: For what seems like forever, marketing events data was isolated (to put it kindly). You could track registrations, attendance, and engagement, but it was harder to connect that activity to anything meaningful with customization or an app. Now teams can connect event activity to: • 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 to understand account-level engagement • 𝗗𝗲𝗮𝗹𝘀 to see which events are influencing pipeline • 𝗣𝗮𝘆𝗺𝗲𝗻𝘁𝘀 𝗮𝗻𝗱 𝗢𝗿𝗱𝗲𝗿𝘀 to tie event activity closer to revenue outcomes • 𝗖𝘂𝘀𝘁𝗼𝗺 𝗮𝗻𝗱 𝗮𝗽𝗽 𝗼𝗯𝗷𝗲𝗰𝘁𝘀 to fit the way their business is actually modeled in HubSpot    That means better answers to questions like: • Which events are influencing the pipeline? • Which accounts are engaging most with our event strategy? • How do attendees convert into customers? • What downstream revenue impact are our events creating?    A small but important detail: this also becomes much more tangible on the record level. In the screenshot here, the association is showing directly on the company record under Marketing events, with the label “Influencing event.” This along with an update allowing us to modify enrollment to Events on the Contact Record (earlier in the year) and some awesome Campaign association updates (March 26), and I feel like both Events and Campaigns are getting some much needed love.