You might have heard of predictive analytics before but weren’t quite sure what it meant. It sounds like something that could be helpful to your business, however, you want to make sure it’s worth the investment.
Predictive analytics have taken the world by storm, inching into almost every industry in the marketplace. They’re an advanced way of making informed decisions with the help of your computer. In this article, we’ll look at how predictive analytics work and why you should consider using them to help your business optimize its process and grow its revenue.
Table of Contents
What Is It?
First, let’s explain what is predictive analytics. Predictive analytics is when your computer or software uses historical data about your business or performance and applies it to current data to assess trends and show you future results based on those trends. In short, it predicts your future performance.
Advances in technology and AI have brought a lot of attention to the use of such programs because these analytics tools are becoming increasingly more accurate and reliable.
Why Does It Matter?
You might be thinking, “That sounds cool but aren’t there tons of programs that can make projections?” You’re not wrong. However, there are two main reasons why people are looking more toward predictive analytics over other options.
The first is big data. Business systems are collecting and utilizing more data year-over-year than ever before in order to better target and serve their customers. This means they have more information than ever to analyze. Things like customer demographic information, the customer journey, touchpoints, customer acquisition costs, close rates, average deal amount and more! Predictive analytics helps them keep an eye on how this affects their business now and will in the future.
The second is that the market is becoming intensely competitive across the board, which means industries have to find a way to get an edge. You’ll start seeing predictive analytics in insurance, engineering, automotive sectors and even retail. The more people can predict their success and make informed decisions based on their data, the better chance they have of continuing an upward trend and gaining an advantage over competitors.
How It Works
Predictive analytics might sound like a detailed fancy process, but it can be broken down into a pretty simple workflow. It’s a machine learning model, so at its core, the computer is parsing through information, looking for patterns and making assessments based on its findings.
A typical predictive workflow might look something like this:
- System accesses or imports data from your archives, databases, spreadsheets or other information repositories. It will scan through the information to gain a general understanding of topics and how each is related to the other.
- Next, it will start combing through your data and cleaning it up so that it’s easier to understand. This might mean removing outliers, organizing messy data or extracting specific features to compare.
- It will use this data to assess the historical and current performance of your business. With that information, it will create a predictive analysis based on observed trends and changes over time.
- Integrate these predictions into relevant systems and programs in your infrastructure that will use the information to help you forecast and plan for the future.
Is It Right for Your Business?
Deciding if predictive analytics is right for your business will rely on a variety of factors, such as the size of your business, your revenue goals and your budget.
You’ll need to assess if you bring in enough data to need a computer’s help and if having future predictions will help you make current decisions. Some industries, such as marketing, can change swiftly as trends and interests change. If your business is like that, then it might be difficult to get accurate results from predictive analytics.
This is a powerful tool that can make a huge difference in the right type of business. Think about if predictive analytics could help your business succeed.