Customer Analytics and the Future of Business
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Customer Analytics and the Future of Business

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Businesses need to attract, engage with, and retain customers. Customer analytics can make this process easier, but how does it work? Read on to find out!

At its most basic, customer analytics involves using techniques like predictive modeling, data visualization, information management, and segmentation to tell a business who their customers are, what they’re up to, what they want, and how best to reach them, creating personalized experiences that win more business and drive loyalty.

Why is this important?

Customers are more empowered and connected than ever. Their expectations are sky-high, and their buying choices are based on positive brand interactions. By understanding what customers are really looking for and noting how they behave when searching for products or services, marketers can work on targeting the right audiences in ways that will truly appeal to them. Suppliers can find the right customers, and customers can find exactly what they’re looking for. Everybody wins!

Where is the technology going?

The general consensus is that the future of customer analytics will be closely tied to the development of machine learning, a type of artificial intelligence that gives computers with the ability to learn without being specifically programmed. Machine learning is the perfect way to access information about customers in order to personalize experiences. It can access massive data sets through the cloud (including data that a company might not be able collect itself) in order to provide instant insights and predictive analysis.

The ITMAGINATION difference

At ITMAGINATION, we’ve created our own customer analytics platform called CRM Online, which is designed to analyze customer profiles in large financial services organizations. It’s based on real-time data from all interaction channels, and it provides customer behavior models as well as a real-time next best offer and action engine, personal finance recommendations, churn analysis, and lifetime value of customer insights. It’s aimed primarily at the financial services sector, but it also works beautifully in the eCommerce and Telco sectors – anywhere there’s frequent user interaction.

Learn it. Know it. Done.

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