Good data helps inform decisions about your meetings and events. However, is there a point where you reach data overload and you need to streamline?
Lots of associations live and die by data. New products are introduced to the market, publications are tweaked, low-performing member benefits are sunset, and events are launched because of it. And, don’t get me wrong, those are all good things.
But have you ever felt overwhelmed by data?
Truth be told, I have. Sometimes I open an analytics report or survey results and my initial reaction is, “Wow, that’s a lot of information right here. Where do I start?”
As event professionals, you may feel this way at times too. After all, you’re likely to have a plethora of data available to you at different points of the meeting lifecycle. Ahead of the event, there are numerous systems to analyze registration numbers, exhibit booth sales, and fundraiser tickets purchased. Once onsite, you may be using beacons and apps to track each attendee’s conference journey. And a few weeks after the meeting wraps up, you’ll have access to results from the postconference survey that was sent to every attendee.
So, what can you do to ensure you’re getting the data you want, and when do you know it’s time to dump certain metrics?
Where to Begin
In a December 2017 article posted by MeetingsNet, Richard Maranville, executive vice president and chief digital officer for Freeman, said that the first step in making the most of analytics is figuring out the objectives you’re trying to meet. “You cannot do it the other way around, where you say, ‘Let’s see as much data as possible, and ideas will come to us,’” he said.
For example, are you trying to boost attendance from a certain segment of your membership, or are you looking for insights that will better market your event to sponsors? Only after you’ve established your objectives can you determine which data pieces are necessary to measure and analyze them.
So, say you know your objectives and the accompanying data that’s needed. Does that mean you stop tracking and analyzing any other data?
But having those objectives in mind may at least help you weed out a few unnecessary metrics. And although you may be tempted to take the approach used when cleaning out your closet (Have you not used the data in a year? Get rid of it.), that’s probably ill-advised.
At the very least, the process of starting with objectives will allow you to give thought to how data can be reorganized in a way that it’s either more useful or better illustrates how it’s connected to those larger goals you’re trying to achieve.
How have you determined which event data is most effective your association, or which data to dump or tweak? Let us know in the comments.