Modern day businesses are turning to predictive analytics to improve their bottom lines and get ahead of their competitors. This is where SAS Analytics comes into the picture, a software program that is designed to manage and curate complex business analytics. The following are 10 reasons why you need to invest in SAS Analytics:
1. It can detect fraud
Since SAS merges a number of analytical methods, it is frequently used to detect online criminal activity and improve the way patterns are detected. As cybersecurity becomes more dangerous overtime, SAS analytics is being used to detect abnormalities in real time. This can include fraud and other threats that are persistent in nature.
Predictive analytics for fraud uses the power of predictive modeling to pinpoint transactions that are illegal as they are being processed. This allows the detection system to adapt to recent data and reduces expense recovery costs among other benefits that make fraud detection more efficient down the line.
2. Improving marketing campaigns
Using SAS Analytics or predictive analytics, programmers and marketing personnel can actually determine what customers want and when. This includes determining their responses to figure out cross selling opportunities that can attract them and make them loyal to particular products and services. This allows business to retain their most profitable customers with very little effort.
3. Improves operations
Through SAS Analytics, businesses can predict how much inventory they need at a given time and manage their resources accordingly. Besides saving time, this also saves a lot of money which can then be channeled into other departments.
4. Increase business opportunities
Airlines and hotels use these analytics – the former to set ticket prices and the latter to predict the number of guests they might receive in order to determine occupancy rates and how much they can increase their revenue. In other words, this data allows businesses to function efficiently.
5. Reduces risk
Predictive analytics are used to detect whether someone has defaulted on their purchases by analyzing their credit scores. This number is an actual analytic itself which is used to determine whether anyone is credit worthy or not. Insurance claims and collections also benefit from this.
Since the technology is updated automatically, even new hacking techniques are no match for it. It can be easily installed and interlinked with a number of different technologies for maximum effect, a fact that makes it invaluable for fraud detection.
6. It is user friendly
Since SAS is designed to read data files via other packages, it allows files that are made by Excel, Stata, Systat etc to be integrated into a program directly or via file conversion. Those who are more experienced, the software is not difficult to use since they can convert the data files that are made from those packages into the SAS based format.
7. Versatile and powerful
SAS Analytics is robust and flexible enough to meet the needs of the modern day data analyst. It offers a range of formats along with several different methods for forecasting, descriptive and inferential statistical analyses. Since the software can be integrated with a number of different modules and products, users can transfer data from one to the next without issue.
SAS Analytics is based on a versatile architecture that is open, scalable and allows users to integrate a number of platforms at a time. Since the technology is script based, users who know the language can handle it well but non-programmers can also use it easily to generate reports and graphs.
8. An asset for financial and health services
SAS Analytics is a boon for the financial industry where massive amounts of money and data are at stake. The data this program can generate allows programmers to protect said assets by detecting and reducing fraud, retain valuable clients, measure credit risks, come up with cross selling and up selling opportunities among other benefits.
The health industry also benefits from this technology since, like the financial industry, it allows them to take steps to determine patients with chronic conditions. This also includes determining the best treatment plans that can aid them in living a long and healthy life. For example, pharmaceutical companies use these analytics to determine patients who are not making use of their prescribed treatments thus resulting in savings up to several hundred dollars.
9. Increases ROI in retail and enhances manufacturing
Retail owners are using predictive analytics to determine what their target customers are most likely to buy depending on common purchases. This allows them to determine what they should order for their inventory and which products should remain in stock. The data is also useful when it comes to predicting promotional events that can attract customers the retail business can profit from.