Making Sense of Big Data
Capturing and analyzing the vast volume of data that can be collected from meetings can yield insights into how to improve the experience and make meetings more effective.
When it comes to meetings and events, it’s not enough anymore to measure total event attendance. Event organizers want to know if the right target audience is having the right interactions with the right content, salespeople, exhibitors, key activations or experiences with other attendees.
Joe Lovett, senior director of strategic planning at Cramer, a brand experience agency, categorizes captured data into three buckets: passive, active, and distilled.
As Lovett explains, active data includes things such as survey, polls, voting, attendee selected preferences that can be captured during registration or onsite via kiosks or apps. Passive data collection includes phone tracking that can provide an attendee flow and heat map, badge or other wearable tracking, peer and exhibitor interactions, event app insights, website analytics and any gamification tracking you may have. Distilled data includes social-post volume and sentiment, influence level of those who are sharing, attendee segmentation by some variable, whether it is role or demographic data.
“By capturing these data points and layering on various attributes, you can have a great understanding on how well the event performed against identified objectives, especially for the very important attendees,” Lovett says.
What types of big data are collected may vary depending upon the type of meeting or event being held. Most meeting planners will benefit from collecting information to profile attendees and to understand what types of topics and events appeal to which market segments. This kind of data can be used to help set a meeting agenda that is designed to attract more attendees. Events where attendees are given a choice of more than one session, for example, can reveal details on participant preferences.
Here are some ways to analyze how events are resonating with audiences.
- Measuring social media activity enables planners to track the conversation wherever it’s happening and learn where to focus event social outreach.
- Looking at page views provides insights on audience awareness of each individual event and all combined future events.
- Using a trending algorithm allows planners to look at dozens of factors to discover not just the most popular event, but also the most interesting one. This automatically enables planners to keep tabs on the social pulse of their community.
Lovett is also excited about next-gen wearables that enable attendees to share contact information with each other, register, check in to sessions, track gamification goals, and more. For the event organizers, the data from these wearables, especially when paired with an app, can offer tremendous measurement and insight.
Other ways big data can improve the experience for attendees:
- Personalization. Today’s attendees want to participate and engage in events on their terms. Big data can help event organizers better understand attendee needs and help them create the personalized experiences attendees crave.
- Networking. Event producers need to focus on ways to encourage networking opportunities, and not just leave it to chance. In the registration process, ask attendees to share a hobby or personal interest, then match attendees who have something in common. Simple registration questions can be paired with wearable technology, smart badges and networking apps that can provide even more data to further networking opportunities.
That said, companies also need to be careful not to be too intrusive. Participants should feel they are opting into an event, not being tracked by marketers looking to take advantage of their attendance.
“The biggest challenge lies with the sheer amount of data that is being produced at events and how to make sense of it all,” Lovett says. “As W. Edwards Deming famously quipped, ‘Just because you can measure everything, doesn’t mean you should.’
“With some pre-event planning, strategy and goal setting in place it can be easier to determine what data points will be most valuable. Not to say that the extraneous data isn’t valuable, but it doesn’t always need to be reported on.”