If you saw our last blog explaining what data is, then you’re probably starting to see the amazing possibilities of what it can do and how it’s becoming more valuable. But just how valuable is data? Just how far can it take the endurance and event management industries?
In the past few years, data has begun to come at our industry at a much faster rate than in the past. What ACTIVE Network’s focus has been is to wrap our arms around it all.
That’s easier than it sounds though. When data is ready, it takes a trained statistical analyst to truly understand it. Analysts identify relationships among data attributes and evaluate them. When they find a connection, they create statistical models. Based on those models, they can generate analytics on a massive scale to derive insights and start predicting customer behavior. That’s the foundation of “Big Data.”
Big Data’s goal is smarter analytics and insights that lead to better business decisions. Most people already use Big Data’s analytics in our daily life–from weather forecasting to Google’s search algorithm. So why couldn’t it help us improve activity and participant management as well? The reality is that, once you reach a “critical mass” of data, it can take your industry to a new level. ACTIVE believes we have reached that level.
In endurance, Big Data analytics can be used for predicting when participants will register for an event. It might get more specific, asking, “what’s the peak conversion time during your specific registration period.”
In order to find that out, we might ask questions like:
• Are people actually registering for an event during the registration period?
• Does the registration vary by type of event, geography or other factors?
• Do the demographics of the area play a role in the variance?
Then, once we find the answers to these questions, we can focus on when the event organizer needs participants to register and what incentives can be provided to increase registration during that time.
But registration is just one possibility. Pricing is another. Let’s look at a price-elastic environment. In most cases, if the price goes down, quantity sold goes up. But in event management, we sometimes see registrations grow toward the end of the registration period when prices are usually going up. To figure out exactly why this is happening, we would needs an analytics model to determine exactly what is happening.
One useful analytics model we can use is called a propensity model. These models are used to ‘target’ consumers that have a higher likelihood to buy a certain kind of service, offer or product. They determine this by connecting demographics, history and communication preferences. For example, some endurance propensity models suggest that as many as 18% of possible event participants won’t register because they weren’t marketed to the right way. If we learn what these participants want, then we can increase conversion rates and revenue.
In event management, there are three main elements: organizations, events and participants. Each has its own challenges. The relationships between the three are complex. One organization can host multiple events, one event can have multiple options, and participants can have different preferences for different events.
With each of these elements, Big Data analytics can be used help answer key questions, leading to improved participation, better event management and ultimately, increased revenue.