Learning Center

Explore the fields of personalized marketing, customer modeling and retention best practices.

Automated customer retention means using sophisticated software to drive all customer analytics and marketing activities for better results.

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Cohort analysis is useful to identify customer behavior trends that may be hidden when looking at more general customer analytics data.

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Successfully predicting customer attrition – and proactively preventing it – represents a huge additional potential revenue source for most businesses.

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Predicting and preventing customer churn represents a huge additional potential revenue source for every business.

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Customer behavior modeling identifies behaviors among groups of customers to predict how similar customers will behave under similar circumstances.

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Marketers who leverage customer intelligence are better able to generate long-term loyalty among their customers.

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Customer lifecycle marketing offers many benefits to customer-centric businesses, including increased customer engagement, monetization, retention and loyalty.

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The advantages of utilizing Customer Lifetime Value include better customer relationships, more effective marketing and more accurate metrics.

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Customer micro-segmentation technology empowers marketers to achieve deeper customer understanding and more effective customer marketing.

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Accurate customer segmentation allows marketers to engage with each customer in the most effective way.

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Cluster analysis uses mathematical models to discover groups of similar customers based on the smallest variations among customers within each group.

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Customer value maximization is about personalizing customer marketing efforts to maximize the total revenues that every customer generates for the company.

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Database marketing is all about leveraging your customer data to deliver more personalized, relevant and effective marketing messages to your customers.

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Deep customer analytics delivers the advanced customer insight which allows marketers to successfully engage with each customer.

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Predictive analytics combined with personalized campaign automation helps companies proactively increase customer loyalty.

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Machine learning helps marketers segment customers, predict churn, forecast customer LTV and effectively personalize messaging.

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Realtime customer marketing is the delivery of highly personalized customer marketing messages to individual customers, at the moment of greatest relevance.

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Relationship marketing is the ability to interact with each customer uniquely, based on that customer’s specific wants, needs and preferences.

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RFM segmentation is a great method to identify groups of customers for special treatment. Learn how to use this method to improve your customer marketing.

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Having a single customer view is essential for organizations to understand and interact with each customer in the most personalized and effective ways.

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Statistical significance indicates how likely it is that a marketing campaign was directly responsible for its recipients’ behavior.

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Every business should focus on building customer loyalty and retention, two factors that maximize customer value over time.

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Every business needs to balance their acquisition and retention efforts to maximize revenues and lifetime customer value.

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Creating customer loyalty with high retention requires you to define brand value, engage in loyalty programs and pursue lost customers.

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Customer lifetime value is the total amount a customer will spend from acquisition through the end of the relationship with a business.

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Marketing Action Optimization is a methodology of identifying and running the most effective marketing action for each customer.

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Next best action marketing is a customer-centric marketing approach that personalizes messaging to generate the desired response for each customer.

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Predictive behavior modeling helps predict the future behavior of customers allowing customer marketers to maximize the effectiveness of their efforts.

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