It’s a core tenet in the event organizer’s playbook: The better you understand your attendees, the better you can cater to them and the better your chances of having them return to your conference year after year. Yet far too often, the chief instrument for gathering event data is the post-event survey.
Today, data analysis, off-the-shelf SaaS tools, and innovations in artificial intelligence and machine learning make it easier than ever to measure and report event data, and insights from that data can help drive business and improve the overall experience for event organizers, sponsors, and attendees.
Here are some tips to help you go beyond surveys.
Behavioral vs. Self-Reported Data
Self-reported data from email surveys sent out after a session or event offers limited insight into your conference. Not only are traditional surveys reactive, but they often have baked-in biases. (Ever notice how your most disgruntled attendees are often the most vocal?)
Far more illuminating than self-reported data is behavioral data, which is based on what attendees actually do. A conference offers an abundance of behavioral data points, starting from the beginning of the marketing path and extending through the event itself.
Even before they register, attendees reveal a lot about themselves by their behavior on the event website. What kind of content do they consume and how often do they consume it? Are they focused on topics or speakers? And how engaged are they with the agenda. For instance, are they “favoriting” or reserving sessions, or just scanning them? Do they spend a lot of time building their agenda or do they just show up?
Attendee behavior at the event itself is another rich source of data. Do your participants attend all sessions or just the keynotes, or do they zero in on the technical content? Do they go to the expo or skip it? And if they go, do they scan at multiple exhibitor booths or not at all?
Behavioral markers like these give you a better understanding of your audience, allowing you to develop cohorts of attendee types. With this data, you can then start testing hypotheses about your audience and glean insights that can help improve your conference in subsequent years.
Data privacy laws permitting, you may also be able to share relevant attendee data with exhibitors that could help them qualify sales leads, magnifying the value of your event for them and boosting retention.
Align Event Strategy with Measurement Objectives
Measurement is of little value if it happens in a silo. Along with your event goals and benchmarks, measurement should flow from and align with your event strategy. And your strategy should be hammered out as early in the event measurement process as possible.
In fact, the best way to strategize for your next event is to look at the data you’ve collected immediately after your latest event, while it’s still fresh. Ask questions like these: What are your objectives for the event? What kind of audience do you want to attract? How have you measured things in the past, and how have you used that information? Where are the gaps in your approach?
Consider how measurement has fit into your strategy historically. Event organizers who treat measurement as an afterthought often struggle to retain their audience and grow their event. Relying on gut feelings and a cursory review of attendee feedback on PowerPoint slides simply doesn’t cut it. Data-driven organizations will see a greater lift in terms of the goals and objectives they are trying to achieve for future attendees, sponsors, and exhibitors.
Tools at Your Disposal
The good news is that it’s easier than ever to access technology applications that capture and analyze event data. For example, customer data platforms (CDPs) are making it easier for event professionals to analyze, track, and manage customer interactions as well as retain valuable data. In addition, readily available business-intelligence (BI) platforms are making it easier for organizations to visualize their data so that it’s easier to understand.
Further, the explosion of ChatGPT and other large language models (LLMs) that use natural language processing are making it easier to do things like analyze verbatim survey data using keywords to gauge sentiment around specific aspects of a conference—food, for example, or crowd levels. These technologies are often free or very low cost and do not require training to begin experimenting with them.
Making Sense of It All
Once your data is collected, analyzed, and can be visualized in digestible ways, what comes next? How do you boil it down into actionable observations and recommendations? This is the last mile of event measurement.
Most companies have all the data and resources they need; they just require help interpreting it to optimize their event. If you don’t have the technical aptitude or support to complete this part of the process in-house, this is where you may want to partner with a data analyst who does. The investment will be well worth it. Understanding your data, its sources, and how to interpret it are keys to improving your attendee experience, boosting your Net Promoter Score, providing more value to exhibitors and sponsors, and growing your conference. And that’s something traditional surveys alone can never do!
Udi Sabach is a data strategist at Nth Degree Events, a trade show and event management company headquartered in Duluth, Ga., with offices throughout North America.
