Mining Event Data from Virtual and F2F Events

Subscribe to get new blog posts delivered to your inbox.

How can event data be collected and used to create meaningful, memorable, and useful event experiences?

When it comes to virtual and F2F events, data is everywhere. However, attendee registration and attendance stats, session sign-ups, and pre- and post-event surveys only scratch the surface.

Virtual events have added to the data mix with additional metrics in-person counterparts don’t have, like clicks, dwell times, engagement, chat activity, and much more. When combined with increasing calls from senior management for hard metrics like NPS scores or tangible return on investment, it’s enough to overwhelm planners’ and their ability to know how and what event data to measure, analyze, and report.

In this article, we explore mining event data to create meaningful, memorable, and useful experiences, with insights from Adam Parry, Editor of Event Industry News and Producer of Event Tech Live, on his experiences.

The Benefits of Collecting Event Data

Although all event data has some value, depending on what you’re trying to learn, certain information can be more valuable to planning your event and improving future events. For example, are you hoping to know about your event in a general sense, or are you interested in a specific detail?

General event data insights could include:

  • How many people came to your event
  • Their roles/seniority
  • Talks or sessions attended
  • Would they recommend your event to others

Specific insights could include:

  • How long did attendees spend in a session versus networking and exploring/engaging with exhibitors
  • Which topics drew the biggest audiences or generated the most engagement
  • Who interacted with any event sponsors
  • Topics that ranked high in attendee satisfaction or areas where more information was needed

When it comes to Event Industry News events, “just like everybody else, we collect registration and lead capture data,” said Parry. “However, we are also fortunate that our sponsors and exhibitors allow us to adopt and get a wealth of additional data from additional technology tools, including facial analysis, heat mapping, and beacon Bluetooth technology. These help us understand how attendees interact with our show, such as what times are the busiest or how long they spend in certain areas.”

This translates on a higher level to how we design future events, shared Parry. “Do we change content? Do we move the show around a little bit? When do we schedule sessions? How can we help our exhibitors and sponsors maximize their presence? Collecting and tracking event data for the last ten years has given us insights into these questions.”

Types of Event Data to Collect

When collecting and analyzing event data, quantitative research deals with numbers, quantities, or amounts, while qualitative research deals with descriptive words and meanings. Both are important for gaining different kinds of knowledge.

Quantitative research is expressed in numbers and graphs and is used to test or confirm theories and assumptions. Standard quantitative event methods include observations recorded as numbers and surveys with closed-ended questions. Examples include:

  • Event tickets sold/purchased
  • Event attendance versus no-shows
  • The number of email sign-ups to your mailing list achieved during your event
  • How many times is your event is mentioned on social media, before, during, and after the event
  • The number of returning attendees to this year’s event
  • Social media engagement (likes, shares, follows, mentions, etc.)
  • Net Promoter Scores

Qualitative research is expressed in words and is used to understand concepts, thoughts, or experiences to understand what worked well and what people liked or could be improved. Examples include:

  • Feedback forms
  • Attendee satisfaction surveys
  • Suggestion boxes
  • Open-ended interviews with attendees

The Role of GDPR in Event Data

However, if you plan to collect data about your attendees at your event, via your website, or any email or social campaigns you run to promote your event, you need to consider General Data Protection Regulations (GDPR).

“Attendees are getting very smart about data privacy – partly due to the devices they hold in their hands, like their iPhones, making it more front and center,” explained Parry. “We can’t dismiss GDPR or any legislation around data and privacy and keep throwing data out to sponsors and exhibitors.”

While it’s best to speak to internal legal and privacy teams about your organization’s specific guidelines and procedures, there are five general principles to keep in mind when it comes to GDPR compliance and collecting event information:

  1. Consent. You must obtain permission from event attendees to store and use their data and explain in a transparent way how it will be used. Consent must be active—meaning no passive use of pre-checked boxes or opt-outs.
  2. Privacy. Attendees can ask you to delete their data and stop sharing it with third parties, like sponsors or exhibitors. These third parties must stop processing the data and delete it upon request.
  3. Security. Organizers must use technology systems that manage attendee data according to industry standards. Any security breach should be reported to attendees within 72 hours.
  4. Portability. Attendees have the right to ask you to transfer their data to them in a digital format to transmit their data to another data controller.
  5. Access. You must provide your attendees access to their data within 30 days and explain how you use it.

Collecting Event Data

There are many different ways to collect data at events, such as:

  • Your event app
    From custom live polls, quizzes, and QA that event tech tools like ConnexMe provide, your event app facilitates capturing qualitative data, especially in real time
  • RFID badges & Bluetooth beacons
    Like Parry has used, using tech solutions such as RFID badges and Bluetooth beacons to monitor crowd movement at your event can reveal where people are spending the most time
  • Content metrics
    From clicks and views to engagement rates and drop-off points, content metrics provide insights into topics that are – or aren’t – resonating with attendees. 

Using Event Data to Learn Quicker

Once you’ve started mining your event for data, the next part is connecting the dots – bringing all the different sources together to see the bigger picture and then applying that to draw conclusions and inform your subsequent event decisions.

For example:

  • Speaker and topic popularity – what should be repeated next year, expanded on, or re-shaped?
  • Sponsor and exhibitor interest – how can you help them maximize their investment?
  • Event agenda details – like preferred format of sessions, length of the event, amount of networking, and more.

Using event data to plan an event is a cycle of learning. Parry explained, “with years of past insights, we don’t have to keep resurfacing and reassessing data every time. Instead, we are able to learn new insights from each show and move that quickly forward to the next event.”

But as event data begins to grow, the biggest challenge is getting it “into a workable format that you can actually do something with,” said Parry. “We are working with a product developer to create a ‘home’ for all this data to sit so that we can cross reference any virtual or in-person event we’re doing and any other touch point we have with our audiences. Ultimately, having these insights will allow us to streamline our business and event operations to be more profitable, make decisions easier, and reduce the stress and project management for managing and planning our events.”

Remember: collecting event data is only the first step. Use that data to mine powerful insights, trends, and patterns and inform your event planning cycle to create meaningful, memorable, and valuable experiences.


Connect with us to learn more about using our end-to-end platform for virtual, hybrid, and in-person events to help support the collection of qualitative and quantitative event data.