Customer Analytics

• Customer Segmentation: Identify customer groups with common characteristics by delving into your customer base with comprehensive data analysis and clustering methods. By understanding these groups, create specific campaigns for each customer segment.

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• Behavior Analysis: Analyze customer interaction data in detail, predict future behavior, and optimize your marketing strategies with data analytics to make informed decisions that drive success..

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• Lifetime Value Analysis: Determine the life-time value (LTV) of customers and support your marketing activities and customer loyalty.

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• Personalized Marketing Strategies: Create targeted campaigns focused on individual customer needs using customer data obtained through data analytics.

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• Customer Churn and Retention : Develop effective retention strategies with this information by predicting customer churn with data analytics, i.e. predicting the tendency of customers to abandon the service.

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• Customer Experience Analysis: Identify areas that need improvement and maximize customer experience by analyzing customer complaints and sentiment analysis.

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• Association Rules Analysis: By analyzing the frequency of purchasing products and services together, identify products that can be sold more together and evaluate cross-selling potential.