Customer value development or Customer Lifetime Value management is essential for every company. After all, acquiring new customers costs more than retaining existing customers. But how loyal are your customers? When and why do they regularly buy from your competitor? The most effective way to gain better insight into the Customer Lifetime Value is to monitor the customer journey. This allows you to predict which customers should be approached how and at what time and when they buy. But what if your customer data is locked up in all kinds of data silos? How do you get more sales from individual customers if you don't know them well enough?

To create a 360-degree customer view, it is necessary to accommodate all customer data in one system. This allows you to optimally analyze and segment the data. Once purchase and behavioral data has been collected over a longer period, it is possible to use smart AI and deep learningtechnology in a smart CDP system build a so-called RFM matrix (Recency, Frequency, Monetary). This matrix helps you identify your most valuable customers. This insight allows you to better focus on potential customers and save unnecessary costs.

Once the basic conditions for customer value optimization and customer lifecycle management have been completed, the next step is to predict the behavior of your customers. You can use Artificial Intelligence (AI) and Machine Learning solutions for this. With AI-driven Predictive Analytics -technology, you can predict what your customers will buy and even when and where they will buy. In this way you prevent 'no sales', increase the service level and improve the customer experience. In addition, you ensure a better stock position, which positively influences your cash flow. In summary: you create more customer value and lower operational costs.