Predictive analytics is an idea that’s garnered much attention over the past several years.
In fact, Google Trends shows that interest in the term has increased 76 percent since January 2013.
Predictive analytics is a combination of data analysis technologies and statistical techniques such as data mining, artificial intelligence, and machine learning. The discipline relies on existing information to recognize patterns and make predictions about the future.
In short, predictive analytics are “able to predict what it would take to encourage a desired customer behavior,” according to a Forbes source.
One of the most common barriers to employing predictive analytics, according to HBR, is a lack of good data. That’s because a single data warehouse is typically a challenge to create. Predictions involve knowing who is buying, what they’ve bought in the past, the attributes of those products, and some demographic attributes. If you have all of these, the author suggests you’re off to a good start.
A company that leverages predictive analytics can enjoy three primary benefits: pursuing new revenue opportunities, mitigating risk, and identifying fraud.
Predictive Analytics For New Revenue Opportunities
One of the biggest benefits of predictive analytics is the ability to identify new ways to generate revenue.
This means being able to influence customers for upselling opportunities, to forecast sales and revenue, and to determine the long-term profitability of a particular set of customers.
New opportunities also means developing new products or services. Many factors go into this, such as determining who the most likely prospects are for those offerings, what demand might be like for them, and what prices customers would be willing to pay.
Stay ahead of the competition and use predictive analytics to improve your revenue.
Mitigating Risk With Predictive Analytics
Another benefit of predictive analytics is its ability to mitigate risk.
Forbes offers a succinct but comprehensive listing of how this can be done:
“Procurement managers need to know how much computing capacity, raw materials or supplies are needed to sustain the business in the months ahead. Human resource managers need to understand upcoming staffing requirements, and where skills demand will be. Operations managers need to be able to coordinate production schedules. Distribution managers require advance notice for shipping runs. Supply-chain partners need to prepare for potential surges in demand.”
By having the data about this information, predictive insights give you the information you need to minimize the likelihood of risk.
How Predictive Analytics Can Identify Fraud
To be fair, this aspect requires potentially the most data, which requires large amounts of memory and computing power.
However, the potential is huge for analytics to alert companies of potential cybersecurity threats.
Companies generally are unaware of data breaches until long after they’ve happened. With predictive analytics, according to TechCrunch, organizations gain the foresight to defend their data against cybercriminals before an attack takes place.
As predictive analytics continues to trend upward, consider adding this tool to your stack. Contact us to learn more about TADA today.