Customer 360.

Customers form the core of your business making them your biggest asset. A holistic view of your customers creates a better and improved customer experience. Hence, the 360 degree will provide your organization with a single view of your customers and associated prospects across the business. This in turn contributes in gaining a broader view that allows you to comprehend your customers, anticipate and respond to their specific expectations.

Hyper
Personalization

Precise hyper-personalization and a profound impact on customer satisfaction to make next best action recommendations.

Customer Retention
and Satisfaction

Systematic ranking and flagging of customers with a high risk of churning and focus resources who warrant retention efforts.

Contextual
Advertising

Personalized and contextual in-screen offers for customer profile that is rich in integrated historic and real-time data.

Case Studies.

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Customer Churn Prediction in Telecom

Companies in the telecom sector often have customer service branches which attempt to win back defecting clients, because recovered long-term customers can be worth much more to a company than newly recruited clients.
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Customer Knowledge Graph

Companies in the telecom sector often have customer service branches which attempt to win back defecting clients, because recovered long-term customers can be worth much more to a company than newly recruited clients.
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Loan Prediction

Bank wants to automate the loan eligibility process based on customer details provided while filling online application form. These details are Gender, Marital Status, Education, Number of Dependent, Income, Loan Amount, and Credit History.
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Lead Scoring

AI model to predict the customers’ tendencies to opt for the specific productor service. The banks can target only top customers based on their lead ranking rate. Eliminate errors in analysis and make confident decisions based on rich data.
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Credit Scoring

AI could allow banks and creditors to score potential borrowers on their creditworthiness using alternative data, for example from social media posts and Internet activity. Artificial Intelligence tools to help make automated decisions and negate risk in lending.