Apara solution dVelox Customer Intelligence provides a complete customer management. Learning automatic detection of similar churn patterns, customer loyalty and attracting new customers in short, medium and long term.
Visión general

Its powerful engine creates predictive probabilistic models to extract variables knowledge which directly affect the probability of client abandonment and helps to establish appropriate communication strategies and customized across the most appropriate channel to optimize customer interaction.
Apara has fully developed this customer management solution for the business environment to pinpoint exactly which customers are more likely to buy products, how to establish close and lasting relationships to anticipate their needs and prevent customer migration to the competition .
Capacities
- Easy to separate micro segments in your audince target.
- Precision to predict which target segment is more likely to contract your services.
- Complete cycle Automation on decision making and identify segment and the three main reasons why they would acquire your products.
- 40% increase speed detecting new patterns behaviors and preventing customer churn.
- Adaptation to new scenarios experienced by the market.
- Explain which variables influence the purchase of your products and can simulate actions to understand the impact on your target audience.
- Provides reports on customer behavior and needs.
- Performance in real-time the changes in your target audience.
- Easy to use interface, does not need experts to handle this mathematical tool.
Value added
- Higher level fragmentation on your target segments.
- Detailed and accurate knowledge of the target segment.
- Detects changes inmediately in your target public.
- Allows to predicts the capacity of influence in a target that has been micro-segment .
- Pinpoint the purchasing propensity in your target audience .
- Independence of personnel specialized to operate the tool.
- Provides valuable statistics that indicate the customer´s comsumption patterns data on sales volumes, avarage consumption per month, what kind of products consumed, which is their behavior, and so on.
- Detects new scenarios without extensive historical activity.

