As the founder and former CEO of SaaS event-management software solution etouches and current co-founder and director of Swoogo, a website and registration platform, Leonora Valvo has spent a good chunk of her career trying to make data easy to collect and simple to analyze. She’s a vocal supporter of what she refers to as the “normalization” of data — creating standard data fields across events to simplify the analytics process. It’s something the meetings and events industry has been slow to address. Valvo recently spoke to Convene about why that needs to change.
What types of data are most important to normalize?
With Swoogo, we give planners the tools to say for every event — this is the standard list of things we are going to ask consistently across events, and then there may be some custom questions we want to ask that are event-specific. Here’s an example: Don’t ever ask for a job title. A job title is a completely useless field. What you really need to do is think about, in your constituency, what are the job roles? And then ask people to select from a uniform list of job roles. Because we know people get really creative about job titles, and so what does that mean to me as an event marketer?
Any demographic information, please keep it very, very consistent across events. Think about geography. Does that matter to you? What do you want to just use as a standard for the industry [your attendees] are from? I don’t know about you, but I’ve gone to some things where it asked, “What’s your industry?” And I looked down the list and I’m like, none of these really fit my industry. So be sure that those answers are right for the audience that you would bring, and then make that consistent. Again, normalize from one to the next.
How does the normalization of data help meeting planners strategize better?
Here’s what I think happens. [Planners] would really love to be able to do some analytics, but first they need to normalize their data, and they’ve moved on to event number 12 for this year, and they don’t have time to sit there with the spreadsheets and sort it all out and try to clean it up. Cleaning up data is the worst part of data analytics. Data normalization displaces the energy planners would spend on something as basic as that.
Imagine now, as an event marketer, that you’re thinking about this event you’re constructing. Say you’re thinking about a one-day event you potentially will offer. What if you could just say, “Show me all of the people with this job role who drove to the event or stayed in the hotel, so that we know they were remote, or didn’t stay in the hotel” — so you’re guessing they’re probably more local.
[Or you can say,] “Tell me all of these people who attended this workshop across my events. Or attended a session with this keyword in it across my events.” Imagine if we started to make sure that your sessions had keywords in them, so that you could find them across events. Again, session titles are like job titles — they’re random. How do you tag those sessions to make sure that when you want to look at events X, Y, and Z, you’re able to actually pull out sessions that are topically related to what you’re trying to create for the next event?
I think event people are smart. They’re savvy, and they know that they need to use the power of their data, but what they’re really getting is independent data dumps from different companies. And the problem is up to them to figure out how to normalize it and turn it into something actionable.
How does that help enhance the attendee and exhibitor experience?
Think about if you and I are invited to the same event. You’re invited because you’re in the press in the events industry; I’m invited because I’m a leader in event technology. Imagine, because the person running the event has done their work on making sure that the data’s there and they understand us each individually, that when I land on the website for that event, I see the top three sessions that an event-tech executive would want to attend. And when you land there, you see the top three things for event media. That does the homework for us, right? Or, hey, here are the event-tech companies that are going to be exhibitors at this event. Now you’re not making it my job to figure out if your event offers significant value to me.
Do social media and event apps help with data analytics, or do they only muddle the most useful information?
If you use social-media sign-on [in an app], you’ve got that person’s LinkedIn data. They’re answering your questions during the registration process through the mobile app; they’re reaching out to other attendees scheduling meetings, and favoriting different sessions or speakers. All of that data — if aggregated — is really, really valuable, because it tells you so much about what the person’s actual interests are.