Nice Systems Ltd.

Hila Lam

Moshe Wasserblat

Yuval Lubowich

Barak Eilam

Gil Dobry

A method and apparatus for predicting customer churn from an organization. The method and apparatus determine an interaction churn score based on analyzing an interaction between the customer and the organization and related data. Optionally, the method and apparatus determine also a transactional churn score based on additional data related to the customer or the organization, and a combined churn score based on the interaction churn score and the transactional churn score. The interaction churn score is determined by assessing a categorization score for the interaction in association with one or more categories, and combining the categorization scores. Of further use is a retention offer mechanism for making a retention offer to the customer.

Method and apparatus for predicting customer churn

A method for classifying a pair of audio signals into an agent audio signal and a customer audio signal. One embodiment relates to unsupervised training, in which the training corpus comprises a multiplicity of audio signal pairs, wherein each pair comprises an agent signal and a customer signal, and wherein it is unknown for each signal if it is by the agent or by the customer. Training is based on the agent signals being more similar to one another than the customer signals. An agent cluster and a customer cluster are determined. The input signals are associated with the agent or the customer according to the higher score combination of the input signals and the clusters. Another embodiment relates to supervised training, wherein an agent model is generated, and the input signal that yields higher score against the model is the agent signal, while the other is the customer signal.

Growing community of inventors

Ramat Gan, Israel

Hila Lam