Crede tailors a customer segmentation based on the client’s strategy. Typical segmentation scenarios optimize actions in order to prioritize results for different goals such as x-sell, customer value maximization, introduce new products based on life style or payment behavior, tailor solution to a risk profile. Read more…

Crede optimizes its client’s sales processes by translating every sales action into data and building a sales pipeline where all relevant KPIs are monitored. Read more…

Crede’s data mining algorithms learn from the past sales actions and predicts which propect customers are more likely to buy given products. Read more…

Having tens of metrics to monitor is an hassle for the management team. Crede identifies and implements KPIs that affect the bottom line and aligned with the corporate strategy.

Since every channel has its own strengths and weaknesses, Crede delivers the best channel mix for the client and prepares a action map for necessary channel migration.

Crede Analytics algorithms walk over process data (mostly IoT generated) and identifies points of improvement.

Crede generates analytical churn prediction models that rank customers by their likeliness to leave the company and defines statistically proven win back actions. Read more…

Customer value maximization is a combination of x-sell, up-sell, retention and win back efforts. It identifies the actions that has to be taken maximize the profitability of each customer. Read more…

Comprehensive assessment of receivables is a must for any monthly service contract. Crede, develops a risk score card of payment behavior and implements with the corporate data + Crede data. Read more…

Crede develops company specific algorithms (not generic) to detect likeliness of possible frauds. Our solutions range from financial fraud to insurance claims, even telco line setup.

Crede segments debtors and develops comprehensive collections actions relevant to their profiles in order to improve receivable collections efficiency. Read more…

Crede can forecast any future event of status that is foreseeable with the given data. World wide proven classification algorithms are widely used for forecasting analysis.