Dynamic Rating
PROBLEM
To compute the potential value of a customer by overcoming the existing prospect screening framework, and to perform a forecast per customer that changes as all potential characteristics change.
SOLUTIONÂ
Moxoff has developed customised machine learning models and tools to dynamically estimate all aspects of prospects that impact the prospect’s expected value.
+ Â New customers
+ Greater accuracy
Forecasting in natural gas logistics
PROBLEM
As a result of new regulatory scenarios, gas providers and distributors are required to forecast, on a daily basis, the next day’s consumption in order to enable optimal balancing of the network.
SOLUTIONÂ
Moxoff has developed a gas demand forecasting model, based on machine learning, capable of predicting gas consumption of customers, enabling better portfolio management.
+ More reliable decisions
+ Savings on imbalance charges
Optimising electricity supply management
PROBLEM
Accurate forecasting that supports operators in making timely and effective decisions for electricity grid management.
SOLUTIONÂ
Moxoff has analysed the available data, developed mathematical models able to identify significant occurrences, and implemented a forecasting system to support operators in making the best decisions.
+ Timely interventions
+ Reliable decision-making
Customer churn rate
PROBLEM
Understanding the causes of churn, i.e. the rate of customer drop-out, and enabling the customer service department to implement targeted actions to prevent and adjust the offer.
SOLUTIONÂ
Moxoff has carried out a customers behaviour analysis that lays the base data for predicting future patterns and changes in customers, in order to be able to plan in time data-driven actions.
+ More effective retention actions
+ Higher quality of service provided
