Predictive Analytics

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:

Predictive Analytics Techniques

Statistical analysis and visualization address the entire analytical process.

Predictive Modeling And Data Mining For

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Model-building

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Evaluation

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Automation capabilities

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Decision Management And Deployment

Empower your analytics with our advanced model management and analytic decision management on premises or on cloud.
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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

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    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.

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    Assessing Risk

    Predictive algorithms provide insight into potential outcomes in discerning risks and to decide on a course of action based on that.

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    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.

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    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.

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    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