A few days ago, in my post titled “Making Event Data Human Centric (Part 1)“, we looked at how the staggering volume of data that we are generating and collecting is overwhelming most of us today. We also explored the many reasons it’s critical for marketers and planners to organize, analyze and mine the multidimensional data generated by their event participants while keeping the focus firmly on the audience that generated that data.
Today, we’ll look at tips and tricks to make an event’s data more approachable and human-centric, along with some examples and insights from the larger world around us. So let’s get started without further ado!
Start with the 10,000 Feet View
Recently, NASA Worldview published two photos of California, both taken from space but at a gap of three years. The first of these, on the left, is from 2014, when most of the state was reeling under the impact of a severe drought. The one on the right is from earlier this year. The difference between the two photos is stark, and one look is enough to convey the information that the region is now on the road to recovery.
Though the phrase ‘10,000 feet view’ is often derided in management strategy classes; in data analysis, the big picture view from the same elevation coupled with time-lapse comparisons can often be a startlingly eye-opening experience.
So, before you take a deep dive into the details, review the year over year data for your event participants, focusing on 5-year or 10-year variations (or for even longer periods, if it makes logical sense) in the overall stats for your event. Significant growth or decline in key parameters, e.g. total attendance, over a given period of time may be more apparent and easier to grasp with this perspective.
Now Take a Deeper Dive
In their quest to discover the key food trends over the years the creators of Rythm-on-food.net collected weekly Google Trends data for hundreds of dishes and ingredients, over twelve years. They then plotted the results on a year clock. Among other things, this helped them then figure out which items fade in and out of a natural season and which ones peak at holidays and special events.
In the real-world, nothing is static. There are always ebbs and flows over a given period of time. Through the years, there are bound to be variations, whether spikes or dips, in your data. Both kinds of trends deserve your attention.
For example, you may find that your overall attendance increases by a fixed percentage range every few years. Or, maybe there is a marked decline every time your event returns to a certain location.
A significant trend is what makes data scientists go, “Now, that’s interesting. I wonder what’s the story behind that trend”. When the big picture overview from the previous exercise reveals trends that are affecting the overall impact and health of your events, then it’s time to take a closer look at your data to figure out if there are certain patterns and correlations that warrant a micro-level inspection. Admittedly, this is where the complexity increases significantly. You’ll have to make crucial decisions on which variation trends are having or will have the biggest impact on your event, and then look at each of them one by one. This exercise will help you come up with a specific question, giving you a much better idea of the exact data sources, data sets and specific reports you need to review to start your investigation in the next stage.
Bring out the Magnifying Lens
In 2014, ThinkwithGoogle.com partnered with Luth Research to look at the micro-moments in the purchase journey of a single opted-in customer for a planned trip to Disney during the holiday season. Interestingly, during the planning phase, she had 419 digital moments in just two months. She made 34 searches, watched 5 videos, and made 380 web page visits. And 87% of these moments happened on mobile.
This snapshot of a real traveler’s research journeys, including the searches, clicks, website visits, and video views on her way to booking helped Google provide practical, actionable ideas for travel marketers for each type of micro-moment.
As you seek to uncover the causes that can answer your “what’s the real story behind this trend” question, you’ll begin to sense its outline emerge from the data. This is where the underlying, interlinked factors – be they positive influences or detrimental challenges – that are triggering changes in a given segment of an audience should be listed and reviewed by your team. And this is also when the individual narratives and responses that you hear repeatedly within that segment will begin to represent the answer to the question you are asking.
This last step deserves a closer inspection, pun unintended. We’ll explore this further in the next article in this series!