Explori Blog | Product Updates

Making event data appetising

Jun 24, 2026

Event data only does its job if the people who need it can see and understand it. That sounds obvious but in practice it's not as simple as giving stakeholders access to the survey report...you need to make it appetising. There's a reason we don't just blend a meal into a uniform brown slop and call it dinner. The food might contain exactly the same ingredients and the same nutritional value, but nobody wants to eat it. Presentation matters - colour, arrangement, a bit of care, is what makes food appetising. It's what makes people reach for it. Data works the same way. Hand someone a raw export or data tables of survey results and most people will close it within thirty seconds. It's not that they don't care about the data. It's that raw ingredients (raw data) don't resonate in their own right, they require preparation, knowledge, and effort before they become useful. A well-built dashboard is not only visually appealing, it surfaces the data and insights in a way that helps non-subject-matter experts understand complex narratives. It takes the same underlying data and presents it in a format that's immediately legible. The right metrics, clearly visualised, arranged for the person who needs to use them. Explori's latest update to dashboards and specifically our "all-in-one" widget creator streamlines the task of creating data visualisations that make data appetising. Why making data accessible is so important It's typical that most event data sits in one place and gets retrieved infrequently. The team that runs the surveys knows where to look but everyone else, the teams who run the next event, the stakeholders who approved the budget often receive a summary of the data that doesn't surface what they need. Additionally, by the time insight reaches the people who need to act on it, it's often too late. Each degree of separation a stakeholder has from the underlying data, the more difficult data backed decision making becomes. These stakeholders need direct access to the data to understand how the show performed, what needs a closer look and ultimately decide what needs changing or actions to take. Full reports still have an important role: they are where detailed analysis lives. But not every stakeholder needs, or has time to interpret, the full report. A dashboard gives each person a focused view of the metrics that matter to them; whether that is overall event performance for leadership, exhibitor experience for sales teams, visitor satisfaction for marketing, or operational feedback for event delivery teams. Instead of asking everyone to work through the same full report, dashboards let you shape the data around the role, event profile, or decision at hand. Dashboards and specifically our recent update to the way all users can create data visualisations for the data points that matter to them, addresses that problem directly. It gives you the tools to build a live view of your event performance, without requiring a developer, a data analyst, or a request to the Explori team. What the "all-in-one" widget creator does Just like cooking, data visualisation is more of an art than a science. We have designed the way you create visualisations / widgets in dashboards with this firmly in mind and consolidated all the configuration options and visualisation settings in one place. Select a metric and a chart appears immediately. Smart defaults mean it looks right from the start. Then you iterate; adjust how the data is aggregated, switch chart type, add another metric - all with a live preview that updates as you go. Having everything together and in arms-reach allows a more iterative and creative approach to visualising data and is a calmer and faster experience. More importantly, it opens up this process to non data specialists. You don't need a working knowledge data visualisation best practice or the underlying data to put together a clear and informative visualisation. You pick the metric that matters, and the tool handles the rest. Smart defaults take care of chart type and layout so you're not starting from a blank page. Drag and drop widgets together directly in the dashboard to arrange the data in format that makes sense for the decisions you or others need to make. Create multiple dashboards for different use cases and each dashboard can be shared and accessed by anyone who needs it. Widgets can pull from your live survey data, so the view updates as fieldwork progresses. You are not screenshotting a report and pasting it into a slide. You are giving stakeholders a live window into the data that exists. Where this fits in the broader intelligence picture The dashboard widget creator is not a standalone feature. It sits within a broader shift in how Explori surfaces intelligence: from data that lives in reports to data that lives where the decisions are made. Automated reporting workflows, AI-driven open-text analysis, and now configurable dashboards are all oriented around the same objective: reducing the distance between event data and the moment someone needs to act on it. The organisations that get the most out of their event intelligence programmes are the ones where data is a shared resource, not a specialist function. The widget creator is a practical step toward that. How to access it The dashboard widget creator is available within the Explori platform as part of the same June 2026 release as AI open-text analysis. If you have questions about configuration or want a walkthrough of what is possible for your specific event programme, speak to your account manager. Frequently asked questions What data can I display in the dashboard widgets? Widgets pull from your live Explori survey data, including quantitative scores, open-text outputs, all alongside Explori's proprietary benchmarks and your company comparisons. The specific metrics available depend on your survey and account configuration. Do I need technical knowledge to build a dashboard? No. The widget creator is designed for event professionals and stakeholders, not data specialists or developers. Can I share dashboards with people outside my organisation? Dashboard can be accessed by anyone with an Explori user account (normal access rules apply) and can be shared externally via PDF or PNG export. Sharing settings are configurable. Does the dashboard update in real time during fieldwork? Widgets draw from live survey data, so the view updates as responses come in during fieldwork. This makes dashboards useful for tracking progress mid-survey, not just for post-event reporting. How does the dashboard widget creator relate to Explori’s existing reporting? The widget creator complements the existing reporting environment rather than replacing it. Full reports remain available for detailed analysis. Dashboards are designed for the stakeholders who need a fast, clear view of the metrics that matter most to them, without navigating the full reporting interface. Is this available to all Explori clients? The feature is available to all users with edit rights. Your account manager can confirm availability for your account and help you get started with configuration.

Why event open-text responses have always been a black hole, and what’s changed

Jun 17, 2026

Pretty much every post-event survey produces them. Hundreds, sometimes thousands, of verbatim responses to questions like “What could we have done better?” or “What was the most valuable part of your experience?” We often say at Explori that open-text feedback gives you the colour that your quantitative data outlines. For most event teams, this rich data exists, but open-text responses have represented the same operational problem for years: too much volume to read manually and too qualitative to include in the executive summary without someone spending hours doing it by hand into a consistent taxonomy. Often, the result is that open-text data gets collected, glanced at, but largely ignored and fails to enrich the feedback narrative truthfuly. That is not a data problem. It is an analysis infrastructure problem. And it is one that AI is perfectly suited to dealing with. What the old model looked like Until recently, organisations tried to solve this with two mechanics. The first was manual coding: a human reads through responses and assigns each to a best fitting categorisation. Time-consuming, inconsistent at scale, and heavily dependent on whoever is doing the coding that week and their research skillset. The second was fixed thematic frameworks: a set of predetermined categories, adopted to create consistency and scale, and applied across all responses regardless of what respondents actually said. This often produces counts. It does not produce insight. If your respondents spent 40% of their verbatim responses talking about something your fixed framework did not anticipate, that signal disappears entirely. Both approaches shared the same failiure point: the analysis was not shaped by what respondents actually said. To be clear, this was not just a failiure of event teams, this was a widespread limitation of open-text analysis. And even experienced researchers (like myself) wrestled with this for years. What AI thematic and sentiment analysis does differently Explori’s AI open-text analysis generates themes dynamically from the actual content of each event’s responses, rather than applying a fixed category list. That distinction matters more than it might sound. A technology conference, hobbyist show, trade exhibition and internal event will surface completely different themes, and that difference is still present between events of a similar type, not because the questions are fundamentally different, but because the audiences, the format, and the commercial context are different. A fixed taxonomy forces all audiences and contexts into the same box. Dynamic theme generation reflects what each audience actually said. The analysis also layers sentiment within each theme. It is not sufficient to know that “exhibitor onboarding” is a recurring topic. You need to know whether respondents are raising it as a frustration or a strength. Sentiment at the theme level (positive, negative, neutral) gives decision-makers directional intelligence to act on, not just a list of things people mentioned. Analysis can be triggered manually during fieldwork for early signal, and regenerates automatically when the survey closes, so the final insights reflect the complete response set rather than a midpoint snapshot. What this means for the decision being made The point of asking open-text questions is to understand the rich and varied experiences and feelings of your audience. But only selecting a handful of comments to digest is like ripping random pages from a book and hoping you understand the story. However, reading every comment is time-consuming. Skipping most of them means missing the story. The use case for AI open-text analysis is not “read your open-text responses faster.” That undersells it. It's that you don't have to choose between tradeoffs, you don’t need to read every comment but you can understand the full story. When a stakeholder asks what exhibitors thought of the onboarding process for your flagship event. Previously, the honest answer was “I've seen some of the comments but I have not had time to get the full picture.” Now the answer is a dynamic thematic and sentiment summary of every response on that topic, available inside the platform, filterable by theme, with the underlying comments accessible for any that need scrutiny. That is the difference between qualitative data that decorates a report and qualitative data that supports a decision. A note on the transition from fixed coding Explori’s legacy fixed thematic code frames are being phased out as part of this release. For clients who have used fixed coding historically, here is what to expect. From launch, a four-week transition window during which legacy AI coding can still be added to new surveys. After four weeks, legacy AI coding will no longer be available to add to new surveys. By end of August 2026, full removal of legacy fixed coding, including for surveys copied from previous years. Existing surveys, historical data, and results already collected are unaffected during the transition period. If you have specific benchmarking or year-on-year comparison needs that relied on fixed coding categories, speak to your account manager before the transition window closes. Where to access it AI open-text analysis is available now within the Reports area of any eligible survey. Navigate to an open-text question and select Generate analysis to trigger it. Analysis regenerates automatically when your survey closes. It can be disabled at account, survey, or individual question level. You retain full control over where it runs. If you have questions about what this means for your existing surveys, your account manager is the right starting point. The bottom line The volume of qualitative data that events generate has always outpaced the capacity to analyse it properly. AI thematic and sentiment analysis does not replace the human judgment needed to act on insight, but it removes the bottleneck that has kept most of that data from being analysed at all. For organisations that take event intelligence seriously, that is a meaningful shift. For a concrete example of how consistent event measurement feeds strategic planning decisions, read how IMEX turned data into a strategic planning engine. Frequently asked questions What is AI open-text analysis in Explori? AI open-text analysis is a capability within the Explori platform that automatically identifies themes and sentiment from open-text survey responses. Rather than applying a fixed category list, it generates themes dynamically from the actual content of each event’s responses, so the output reflects what respondents said rather than what the analyst anticipated. How is dynamic theme generation different from fixed coding? Fixed coding applies a predetermined set of categories to all responses, regardless of what respondents actually wrote. If a theme emerges that is not in the fixed framework, it does not appear in the output. Dynamic theme generation reads the actual content of responses and identifies the themes that are present in that specific dataset, which means unusual or unexpected topics surface rather than being absorbed into a catch-all category. What sentiment analysis does the platform provide? Each question analysed by AI open-text analysis includes a sentiment breakdown showing the proportion of responses that are positive, negative, or neutral. This gives decision-makers directional intelligence on whether a topic is a strength or a concern, not just confirmation that it was mentioned. When does analysis run and how current is it? Analysis can be triggered manually at any point during fieldwork to get an early read on themes as responses come in. It regenerates automatically when the survey closes, ensuring the final output reflects the complete response set rather than a snapshot from midway through data collection. Can I disable AI open-text analysis if I do not want it? Yes. AI open-text analysis can be disabled at account level, survey level, or individual question level. You retain full control over where the analysis runs. What is happening to Explori’s legacy fixed AI coding? Explori’s legacy fixed thematic code frames are being phased out in three stages from June 2026. From launch, there is a four-week window during which legacy coding can still be added to new surveys. After that window, legacy coding will no longer be available for new surveys. By end of August 2026, legacy coding will be fully removed, including support for surveys copied from previous years. Existing surveys and historical data are unaffected during the transition. Does AI open-text analysis work across different languages? Speak to your account manager about language support for your specific survey programme. Language capability is an important consideration for organisations running multi-territory events where respondents write in different languages. How does AI open-text analysis fit into Explori’s broader intelligence platform? AI open-text analysis is one part of a broader platform investment in reducing the distance between event data and the moment someone needs to act on it. It works alongside quantitative measurement, benchmarking, and dashboard tools to give event teams a complete intelligence picture, not just a set of scores.