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
Predictive Analytics is applicable for a range of functions to gain meaningful insights such as
Customer Segmentation
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.
Assessing Risk
Predictive algorithms provide insight into potential outcomes in discerning risks and to decide on a course of action based on that.
Churn Prevention
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.
Sales Forecasting
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.
Crisis Management
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.
Success Stories
Indium Insights
The banking, financial services, and insurance (BFSI) sector has been actively incorporating digital solutions to…