Predictive Analytics Software

What Is Predictive Analytics Software?

Most business intelligence tools are designed for looking back on past data and categorizing that information in a way that’s easy to understand. Predictive analytics solutions, on the other hand, take an extra step and use that past data to predict future trends. These systems look at all of your company’s past performance in order to identify patterns and make very educated guesses about what the future will look like. Models are created to predict outcomes and help you make the decisions necessary to take the optimal path.

However, it’s important to note that this isn’t a foolproof system. There is a margin of error to consider, but the best predictive analytics software can minimize that chance.

There are four types of analytics in particular that any prospective user should know about, each of which has a different functionality and purpose.

• Descriptive - makes use of data as it arrives to identify wider trends in the here and now. Without descriptive analytics, you can’t get a solid idea of how things are going right now.
• Diagnostic - organizes and analyzes past data in order to determine exactly what led to fluctuations. Without diagnostic analytics, you can’t really figure out why certain decisions resulted in the changes that they did.
• Predictive - predicts what will happen in the future based on past data. Without predictive analytics, you can’t leverage your past data to try to predict the best course going forward.
• Prescriptive - analyzes possibilities in the future and helps you decide which would be best. Without prescriptive analytics, you may have some idea of what certain decisions will lead to, but you won’t be able to tell which would be best for you and your business.

Common Predictive Analytics Software Features

There are many different types of predictive analytics software, but many of them share some common core features, including the following:

• Predictive Modeling - Simply put, predictive modeling is a specific type of statistical analysis that tries to determine what will lead to different results. By creating models and inputting past data, a predictive modeling system predicts how new data will impact your business and future.
• Data Mining - While inputting data may sound fairly simple, there is quite a bit of complexity when it comes to figuring out which parts of the data are valuable. A strong data mining program can efficiently extract the most important bits of information and prepare them for input into your predictive models.
• Text Analytics - Getting the right numbers out of your data is hard, but what’s even harder is getting the right information out of textual sources. Specialized programs are needed to get usable data out of formats that aren’t already organized for easy data extraction.
• Data Visualization - Even if you extract the best and most efficient data, then set up the best possible model to predict your success, it doesn’t help much if you, the user, can’t understand it. To understand your data best, you will need some form of data visualization. Looking at columns of figures on a document can only go so far, which is where various forms of data visualization come in handy.
• R Integration - While R integration isn’t found in every piece of predictive analytics software, it is found in many. One of its main advantages is that it allows users to mine and sort through vast amounts of data much faster.

Predictive Analytics Software Buyer Types

When it comes to picking predictive analytics software, the most important consideration is exactly what type of buyer you are. There’s no product that is so much better than the rest that every single buyer should pick it without reservation. Instead, there are a variety of products that offer very different benefits and are suited to different types of buyers. Consider the following types of buyers and what product might be best for them.

Financial Sector

When it comes to banking and other areas of finance, predictive analytics software has been critical for as long as the software has been around. It’s the foundation for everything from credit scores to fraud prevention. This is even more true for financial advisors that need to track the market in order to make profits and prevent losses in the future.

Retail

The key for any store is to figure out what the customers want and get ahead of the curve. Predictive analytics software is one of the easiest ways to do that, allowing savvy stores to track what customers do, how they respond to stimuli, and how you can convince them to keep coming back.

Healthcare

Besides the previous applications of predicting how people and man-made institutions act, predictive analytics can also be highly valuable when it comes to predicting how the body, diseases, and treatments work. On top of that, the software can also make administration and insurance much more streamlined.

Market Trends

There are some trends regarding predictive analytics software that you should keep in mind:

Ease of Use

It’s hardly news that business intelligence systems are moving towards increased user-friendliness, allowing them to be used and understood by more than just dedicated IT professionals. Predictive analytics is naturally part of this trend, growing more and more user friendly by the year. This trend will help the major decision-makers to better understand what the data means and why it’s indicating a certain course of action.

Cloud Migration

More and more services are moving towards the cloud as technology improves and people become more comfortable with entirely digital data. For businesses that don’t have the space or personnel to house an entire predictive analytics suite on site, pursuing a cloud-based option can pay big dividends and such options will only become more viable as time passes.

Wider Usage

The financial sector is certainly the biggest share of the market when it comes to predictive analytics, but that won’t necessarily hold true forever. As more and more retailers, manufacturers, and healthcare companies take advantage of the power of predictive analytics, the rate of spread will only increase.

Growth

Improvements in the underlying technology play a big role in the advancement of predictive analytics. When considered along with the fact that businesses are more likely to gather and organize data efficiently today, it’s no surprise that predictive analytics is rapidly improving and expanding every year. More and more predictive analytics products will become available every year, with an ever-expanding range of features and capabilities.