Why “live engagement marketing” is the future of events

“live engagement marketing” is the future of events

"Engagement" is the buzzword du jour across the meetings and events industry. It's such a big topic that an entire discipline - "live engagement marketing" (LEM) -- has emerged to help meeting planners create and leverage engagement at their events. What it truly means to engage attendees, however, isn't always clear.

To the uninitiated, LEM is synonymous with event apps, which attendees can use to consume event content and to interact with each other and with meeting organizers. Attendees who download and use apps (the thinking goes) feel more intimately connected to the meeting and more personally invested in driving positive meeting outcomes in an event's education, networking, and procurement. 

But event apps are only the beginning. To find out what LEM is really all about, Successful Meetings asked Lawrence Coburn, CEO of DoubleDutch, to describe why LEM is valuable and where he sees it going. According to Coburn, the next chapter in event technology isn't just more and better apps -- it's a whole new way of planning and executing meetings.

First of all, what is 'LEM,' exactly?

At the simplest level, LEM is the discipline of applying digital marketing techniques to physical-world events. That's really the root of it -- applying some of the techniques we've seen emerge over the last 15 years in the online world, like measurement and optimization and targeting, to the analogue world of live meetings and events.

And does the online world, in fact, translate into the real world?

It's a great question. We've actually broken LEM down into three phases. The first phase is all about technology adoption and engagement. Can you get attendees of meetings and events to use technology as they navigate the event in order to generate data that can be collected and understood? That's the stage most events are at right now with the adoption of mobile event apps like DoubleDutch, which attendees are using as digital concierges as they navigate events. 

Stage two of LEM is measurement and analytics. If you think about all this engagement on the tech at live events that's generating all this data exhaust -- all these signals that can be parsed and understood -- stage two is all about visualizing that data in a way that's actionable. It's about understanding from data what's working at the event and what isn't.

Stage three, which is the hardest stage of all, is really about influence. Not only can you measure what's happening at your event, but you can use technology to react to the data to shape the outcome of your events. We like to think about events as funnels, where there's a low engagement level at the top of the funnel and a business outcome at the bottom of it. For a sales or marketing event, the business outcome is typically more sales. For an education event, it's teaching people stuff. For a networking event, it's driving maximum meetings and connections. Stage three of LEM is about influencing the velocity with which attendees flow through this funnel and get to the desired business outcome.

It's not about the mobile event app; it's about how you can use data to optimize your events like you would optimize a webpage, and also how you can take that data and pump it into other systems of record like your CRM and your marketing automation software. To me, that's the big job. Data from meetings and events can be used not only to throw better events, but also to help your salespeople close more deals as you learn more about attendees.

Why is more data better?

Planners have done a heroic job with the data that's available to them. Historically, that data has been demographic data that you would capture in a registration system -- like how many people actually showed up. That data is OK, but if you can engage people on an app throughout the whole event you can learn so much more about them. For example, on our app we see about 183 actions per user at a typical event. An action can be a tap on a profile page, a meeting request, a "like," a comment, a bookmark, a message sent to a fellow attendee. There are 75 different kinds of signals available on our app that generate user actions. This is an incredible fire hose of data. With only registration data, planners are operating with about 2 percent visibility into the data. With mobile event apps they're pushing 60 to 70 percent. That means that for 70 percent of your users, you're getting deep insights about what they like and what they don't like at your event.

Meeting planning isn't just science; it's also art. Do you worry that data-based decision-making will handicap planners' creativity?

There is actually precedence that our industry can learn from. Back in 2003, there was a huge transition in the digital advertising world. Prior to 2003, the dominant way to get your message out online was to buy banner ads and put them on the homepage at Yahoo.com. That would drive a fire hose of traffic to your site. Some of those people would be interested in your stuff, but most of them would not be because it wasn't targeted traffic. In 2003, there was a shift from very creative banner ads to simple text-based ads delivered by a little company called Google. Even though their ads weren't as pretty as the ones on Yahoo!, Google was able to target them using the search query as a way to match likely buyers with advertisers. Almost overnight, all those advertising dollars shifted from Yahoo! to Google.

The lesson there is: The advertising industry thought creative was what won in advertising, but it turned out that data worked a lot better. I think our industry is going to reach that same realization. That doesn't mean there's not a time and place for hunches. When you're trying new stuff, for example, there will be no data to inform you about whether it's going to work. The best events are always going to be innovating and trying new things, but now they can actually measure -- quantitatively -- whether those new things are resonating.

You spoke about the three stages of LEM. Where is DoubleDutch?

Traditionally, DoubleDutch has been really good at adoption and engagement -- stage one. Because if you've used the DoubleDutch app you know it feels like a private social network; it's addictive. However, the social aspect is just one side of the coin, which leads to data on the other side. If you can get people engaged in using your technology, it's going to generate a lot of data that's going to be helpful in throwing better events.

So, we've mastered stage one and I think we're now making good progress on stage two, which is visualizing and presenting data in actionable ways so planners can make better decisions about their events. For example, we can tell you which of your speakers resonated the most with your attendees. We can tell you what content worked and what content didn't. We can give you a list of 100 people that were most interested in any particular session or any particular piece of content. We can tell you which exhibitors got good ROI and which ones didn't. And using a variety of signals like inbound meeting requests and messages, we can tell you who your most influential attendees were.

So, you're at stage two. What about stage three?

As I mentioned, stage three is the hardest. But it's also the most exciting. If you look at the rising tides of artificial intelligence (AI) and machine learning, there are going to be tremendous opportunities for our industry. We're instrumenting thousands upon thousands of real, live human attendees at events. By analyzing the patterns with which they navigate shows, the content they like, and the connections they make, we'll be able to write algorithms that can make recommendations to attendees about which breakout sessions they should attend and which fellow attendees they should meet. As we continue to draw from the machine learning and AI communities, we'll get better and better at guiding attendees to positive business outcomes. It's really exciting stuff. We are in the test-phase right now on a lot of these things, but over the next couple of years you're going to see a big movement toward applying machine learning and AI principles to the live meetings experience.

How can planners who haven't used LEM yet get their feet wet?

The obvious way to start experimenting is to do just that. Remember, stage one is all about adoption and engagement of technology. So, I would encourage folks to do some research about the technology that's available. It might be a polling solution, a Q&A solution, or a microphone you can toss around the room. Do some research, find some technology that you think is a good fit for your event, and just try it out. See what percentage of your attendees you can get to use that technology and find out what analytics the vendor can provide to help you understand attendees' usage of that technology and what it might say about the overall event experience.

And what if attendees don't use it?

I think we're moving rapidly to the days where there will be 100 percent adoption of technology at events because of the positive ROI that will come from AI-enabled insights. The more people there are who use technology onsite at events, the more data will be generated for event planners to leverage, and the better attendees' experiences will be. That's what's most promising from a technical perspective, and it's something our engineers are very excited about.

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