Customer Analytics
Customer Analytics has been a central part of the analytics strategy of many companies for many years. Customer Analytics describes the evaluation and use of collected customer data and information in models from statistics and machine learning to optimize customer relationships, products and services.
In many projects in the customer analytics environment, historical customer data is used to make predictions about future customer behavior, e.g. about their emigration, buying habits or lifetime value. A wide range of mathematical and statistical methods are used to make precise statements.
Customer churn
Forecast of customer migration in the future based on historical data points.
Customer segmentation
Clustering of your customers based on purchases, transactions and other data for optimal customer contact.
Up- & cross-selling
Targeted forecasts of further product purchases by the customer of the same or a different genre.
Customer retention
Identify customers who are likely to return after the customer relationship ends.
Data Science in Customer Analysis.
Case studies in the field of customer analytics.
A+ EuroTEC offers you a wide range of services in the field of customer analytics.
Our data scientists support you competently in the development of use cases and projects in the customer analytics environment. We consolidate and aggregate internal and external customer data for you and develop models from statistics and machine learning for the optimization of your customer relationships, services and products.
With Customer Analytics you use existing customer data and make better, data-driven decisions to optimize products and services for your customers.
- Next-best product forecast
- Online upselling forecast
- Prediction of customer churn