We all wish we can see into the future, right? Be able to anticipate when we make a mistake or are able to stop a crisis?
Predictive analytics may be the closest that we’ll get to seeing into the future.
What is Predictive Analytics?
Industries are hiring data scientists to explain the prediction definition data in ways that they can understand.
It’s the use of data, statistical algorithms, and machine learning to guess future outcomes based on past data. Its goal is to give the best guess as to what will happen in the future.
A lot of industries are using it to solve difficult problems and to discover new ways to grow. Some common uses are to detect fraud, make the best marketing campaigns, improving operations, and reducing risk.
How Does It Work?
It starts with a goal, what does the business want? Do they want to increase customers? Save time? Cut costs?
By having this goal, data is collected in a huge pile that can create possible ways to get what the business wants. This could mean being less wasteful, giving better sales, or increasing employees’ happiness.
The data scientists use predictive modeling, which uses mathematical and computational methods to predict as many outcomes as possible.
How is It Used?
There are many ways to use this tool to help yourself or your business.
This is exactly what it sounds like. You use predictive analytics to predict demand for consumer products. Businesses love this because inventory is expensive and running out of items costs money.
You can use Time Series Econometrics, which analyzes data to get meaningful statistics of the data. You then use this data to predict future sales. This method works when the products are popular in large areas but tends to get overwhelmed with other signals.
Another way is using anonymized and aggregated web searches. By seeing what people are looking for and then what product pages they click on, allows companies to see what people want and how many people want it.
Depending on the location that the searches happen, businesses can increase or decrease their inventory so that there is just the right amount to meet demand.
There is never one standard price when it comes to products, that wouldn’t allow businesses to actually make profits. Businesses usually offer discounts, promotions, and random sales to target customers.
Have you ever noticed if you looked at a certain item, suddenly you are getting emails about it being on sale? Or maybe you left a few things in a cart and you get offered ten percent off your whole purchase?
Predictive analytics help businesses know how responsive customers are to such prices and discounts. They use data like what you look at, what you actually buy, and how much money you spend on average to predict your purchasing movements.
This has more to with machines that help businesses run rather than the customers. Any machine that breaks down and the time it takes to fix it is lost money. Businesses often say that machines breaking down is the biggest unexpected risk to their profits.
Airlines, in particular, are interested in predicting machine failures so they can reduce any flight delays or cancellations. Also, heaven forbid there is a problem while the plane is actually in flight.
Predictive analytics can use data like maintenance history and flight route information to predict when a plane will need repairs. The machine learning solution has gotten so good that it can predict within twenty-four hours if a plane needs repairs to minimize delayed flights.
Similar predictive maintenance tools are used for aircraft engines, ATMs, gas pumps, and other similar machines.
Who Uses It?
There are many different industries that use predict definition analytics. There’s banking and any other financial services that use it to detect and reduce fraud. They also measure credit risk and the best ways to retain customers.
Retailers use to figure out which product to stock, see how good is their marketing is, and how to keep customers happy.
Oil and gas industries use it to predict maintenance problems. They make sure everything is running safely without any risks and to improve overall performance.
Government and the public sector use it to understand what people need so they can improve their performance. They detect frauds and understand consumer behavior better.
Health insurance uses it to detect claim fraud and to identify patients most at risk of chronic disease to find the best solutions.
We May Not Be Able to See into the Future
But we are pretty close with predictive analytics. If you ever get confused as to what it is, you can always think of it as a mathematical way to see into the future.