Predictive analytics enables Indium Software customers to leverage the past and the current to decide its future. It helps design data-driven strategies to give organizations a competitive edge, tightly integrating Predictive Analytics into their key decision making process.
Indium Software’s Predictive Analytics Techniques
Indium Software utilizes five key techniques to optimize data analysis. This includes:
Statistical analysis and visualization address the entire analytical process.
Predictive modeling and data mining for:
Decision management and deployment
- Empower your analytics with our advanced model management and analytic decision management on premises or on cloud.
Big data analytics
- Build strong and effective business strategies using the predictive insights gained from analyzing Big Data
Predictive Analytics is applicable for a range of functions to gain meaningful insights such as:
To group customers similar in specific ways such as age, gender, interests and spending habits for being able to accurately target them with tailored marketing messages.
Predictive algorithms provide insight into potential outcomes in discerning risks and to decide on a course of action based on that.
As the cost of retaining an existing customer is much lower than acquiring a new one, Predictive Analytics can help assess the potential reasons for customers ending their relationship with a company and devise ways to retain them.
Data mining can be used to anticipate the response from customers and their changing attitudes. Sales forecasting can be applied to short, medium or long term forecasting.
Insights obtained via the tools and algorithms of predictive analytics can help any organization address the challenges unique to them and keep ahead of competition.