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Predictive Analysis: How Your Association’s Past can Predict The Future

While predictive analysis cannot completely predict the future to every last detail, it’s a great way to get some insight into the future of your association. Let's break down predictive analysis to its core.

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Wouldn’t it be easy if you could predict the future success of your association before it even happened? While it might seem like a pipe dream, it’s actually more plausible than you might think. That’s right, you don’t need a psychic or a crystal ball to see into the future when it comes to your organization. There’s a much easier way that will actually give you accurate results, helping you prepare for a bright future and foresee any problems you may face. So, if this peaks your interest, let’s talk about something called predictive analysis.

Predictive analysis is a way for any business and/or organization to use past data to try and paint a picture of the future. It uses collected numbers and analytics to look for trends and patterns that can (hopefully) spell out the fate of an organization days, months, and even years down the line. But even with such a proactive resource out there, many associations still do not understand how to properly use predictive analysis to generate future success.

If you’re an association that wants to incorporate predictive analysis in order to increase membership sales, generate more revenue, or perform any other task, we’ve got tips for you. In this article, we’re going to break down exactly how your association’s past can help you prepare for a brighter future. To start, let’s break down predictive analysis to its core.

A Closer Look

In order for your association to use predictive analysis as a positive tool for future success, it’s first important to take a closer look and understand exactly what it is you’re getting into. As mentioned before, predictive analysis helps your association use past data to create a vision of your association’s future. Based on the data you collect, you can make educated assumptions on your association’s membership, revenue streams, event attendance, and anything else you track analytics on.

With this method, your association can take a look at historical data that describes the many features of what it is you’re trying to predict. For example, let’s take a look at your association’s annual event or conference. If you collect data on things like past event attendance, satisfaction results from attendee surveys, event promotion efforts, or any other relevant data source, your association should be able to predict the future success of events. You can also observe more analytical data, such as event ticket prices, sponsorship investments, event budget, etc. Predictive analysis even works well with your association’s marketing strategy.

With marketing being more data-oriented than ever, using data to predict your future marketing efforts is practically a no brainer. By analyzing past data, you can predict marketing trends and try to pinpoint the next move for your association’s outreach efforts. So, now that we know a little bit more about predictive analysis, let’s go over a few different factors that can help you start analyzing your association’s data.

Data vs. Knowledge

When it comes to making a prediction based on your association’s analysis, you could be struggling between the appropriate balance of data and business knowledge. While this balance may vary between association, it’s important to know exactly where you stand when it comes to making that distinction. Too much data and your association could be overlooking some serious business fundamentals within your prediction. However, not enough data can leave room for error.

So, how do you find a happy medium? Well, when creating a predictive model out of your data, you always want to test your model and see what combination of big data and observations will do the trick for your association. This number will vary for everyone, so do not be discouraged if your first model doesn’t test the way you’d like it to. For example, let’s say you’re trying to make a predictive model based around your association’s events. You can take your association’s data on things like ticket sales, revenue made from past events, sponsorships brought in, and everything else and creative a predictive model on the success of your next event. However, if you solely rely on this data, you may have flaws in the model that could throw off the prediction.

But, if you also include observations like attendee satisfaction and engagement, you could pick up the slack left behind within your predictive model. With this perfect balance of data and observation, there’s no telling what the future could hold for your events and conferences. So, when creating predictive models, be sure you create a happy medium between numerical data and observational data for the perfect combination.

Models That Work

With predictive analysis, the key to a good prediction is all in the model. As prior mentioned, creating a solid predictive model is an experiment. Much like any other new strategy your association tests out, a predictive model may need a few test runs before you can deem it solid to use for the future. There also might be some bumps along the road that can throw your model off course. In any case, it’s good to know your association’s predictive model will not be perfect from the start. However, there are a few things you can do to create a model that works for your association.

To start, you want to make sure you’re using a software or data service you trust. With the proper software, you can make sure your models are mapped out on their own, saving your association time in the long run.

These model services will then use an algorithm to map out your data, which will then help them pick up on data trends, no matter how large or small in significance these trends might be. Long story short, these models should do a decent job of using past trends to predict future ones. Once you have a predictive model that produces effective predictions, you can continue to use this model to generate predictions in other fields of interest for your association.

Tell Your Own Fortune

While predictive analysis cannot completely predict the future to every last detail, it’s a great way to get some insight into the future of your association. If you’re an organization that’s looking for a better way to see how its hard work is going to pay off, using predictive analysis techniques can give you a relatively insightful look into how your strategies and moves are going to affect your association’s success from here on out.

So, if you’d like to get a head start in planning your association’s next move, consider using predictive analysis and see where your data can take you.