108 results about "Customer attrition" patented technology

A churn analysis system helps a business analyze, predict, and reduce customer churn. The system analyzes customer experiences by using an insightful block level approach to correlate customer experience with customer churn. Through the block level approach, the system is able to more accurately predict and effectively reduce future customer churn. As a result, businesses are able to reduce customer acquisition costs and improve customer retention rates.

The present invention relates to a system and method for customer retention. Historical transaction and customer data may be received from stores. Likewise, recent customer transaction data may be received from the stores. The transactions are linked to each customer. Attriters, historical customers who discontinued shopping, are identified. Next, risk factors for attrition may be identified by examining the attriters' transaction history for commonalities. From the risk factors a loss model may be generated. The loss model may be used, in conjunction with current transaction data, to generate the likelihood of loss for each of the current customers, which may then be reported. Retention measures may be generated for each customer by comparing the customer's transactions to the loss model and the risk factors. The retention measures may be outputted to the stores, and a price optimization system. Likewise, the retention measures may be validated by comparing actual customer loss to the loss model.

A method and apparatus for training a neural network to compute hazard functions for customers and analyzing hazard functions, both for an individual customer, and for set of customers to focus marketing techniques. The hazard function represents the likelihood of churn for a particular customer. The gain in lifetime value is also calculated for each customer which incorporates the present value of the customer with the future value of the customer if a new contract is entered. The overall shape of the hazard function, combined with the gain in lifetime value, specifies what marketing techniques are to be applied together with what additional incentives are to be offered to the customer in order prevent churn.

A computerized method of predicting customer churn from an organization, including: receiving at a computer server a recorded customer interaction with an agent of the organization; analyzing the received customer interaction to extract basic features that provide an indication regarding the churn probability of the customer; extracting the entity information of the customer from the recorded interaction; retrieving from a database accessible by the server previous interactions for the same entity and extracting advanced features that provide an indication regarding the churn probability of the customer by comparing multiple interactions of the same entity; predicting a churn probability for the received interaction by applying a statistical customer churn model to the extracted basic features and extracted advanced features; and wherein the interaction and the previous interactions are recordable from more than one type of communication channel by which the customer can communicate with the organization.

The invention relates to a method for analyzing customer churn of a mobile communication service. The method comprises the following steps of: connecting a data warehouse; scheduling a data mining tool to analyze information such as calling in the past period of time, customer service complaints or payment and the like of a churned customer; extracting behavior characteristics of the churned customer or a customer with the churning tendency; building a customer churn prediction model; applying the model to an actual customer service; acquiring customer churn prediction information; and providing support for the management decisions of enterprises. Compared with the prior art, the method can well analyze the customer churn for the mobile communication industry.

The present invention generally relates to estimating a customer's lifetime value to a company. The customer's lifetime value to the company can be based on remaining value of existing products and one or both of new purchase value and historic profitability. The remaining value and new purchase value for the customer may be estimated based on the customer's current customer segment and the customer's predicted future migration to a different customer segment. In addition, the remaining value may be estimated based on expected customer attrition, and the new purchase value may be estimated based on expected individual customer purchases.

Customers buy a variety of equipments and gadgets from multiple vendors and interact with manufacturers through contact centers to get their questions on the bought products answered. The market opportunities and competitiveness are forcing manufacturers to be accommodative and innovative in providing post-sale support. An essential aspect of this market dynamics is customer churn and the manufactures are required to ensure that product loyalty and brand loyalty of the customers are high. While Customer Relationship Management (CRM) has been playing an all important role of monitoring and managing customer relationships, it is necessary to augment CRM with more specific enhancements. The need is to have an integrated, practical, and realizable approach that focuses on measuring customer satisfaction index based on multiple interactions of customers with manufacturers. A system and method for tracking customer satisfaction index involves tracking of the intentional states of customers and assessing them just in time to help improve the satisfaction index.

The invention discloses an automatic excavation system for analogous customer groups, which comprises a data preprocessing and cleaning device, an unstructured information extractor, a fusion search engine, an excavation target generator, a data warehouse, a relevance analyzer, a tendency analyzer, a customer lose analyzer, a classification analyzer, a cluster analyzer, an isolated point analyzer, customer enterprise characteristic analyzer, a commercial activity analyzer, a customer enterprise credit analyzer, a customer enterprise loyalty index analyzer, a customer enterprise attention analyzer, a customer enterprise marketing analyzer and a result summarization and visualization module. With the system, the contracted customer enterprises are taken as cases, and the analogous customer groups are deeply and accurately excavated in real time, so that value-added services of analogous customer enterprise groups can be immediately provided for users according to rules of a case expansion method.

Method and apparatus that facilitates customer retention, churn reduction, and customer satisfaction by predicting customer churn and taking an appropriate action to retain a customer is described. In an example, a customer retention method acquires information indicative of customer service usage by customers. The customer retention method then provides an analysis of the acquired information. The analysis predicts the likelihood of churn for each customer. The customer retention method then identifies affected customers based on the analysis. The customer retention method then automatically selects customer support executives to initiate an action for each of the affected customers. The customer retention method selects the customer support executives based on skill in handling the affected customers, among other factors.

A method and system of reducing churn of customers for a communications service provider may include storing account information of a customer of the communications service provider. The customer account information may include customer service plan data and customer history data. The customer account information may be accessed by a computing unit. A total number of points collected by the customer during a time period based on the customer account information may be determined. The calculation may include totaling points associated with the customer service plan data and customer history data. A number of sweepstakes entries the customer achieved based on the calculated total number of points may be determined. The customer may be entered into the sweepstakes with one or more achieved sweepstakes entries for the time period. A sweepstakes drawing for the sweepstakes may be conducted, and a prize may be awarded to a winner of the sweepstakes.

The invention discloses a lending method, device and computer-readable storage medium for joint lending by banks. The method includes: when a loan application is received, judging whether the loan application meets the lending requirements for joint lending; When the loan requirements for joint lending are met, the joint bank for joint lending is determined; when the joint bank and the loan application are matched, the matching joint bank is used as the target joint bank for joint lending. In this scheme, when the loan application meets the lending requirements for joint lending, it matches the joint bank determined to be eligible for joint lending with the loan application. When the joint bank and the loan application are successfully matched, the matching joint bank is used as the target joint bank for multi-bank processing. joint lending. Through this bank joint lending method, the borrower can borrow money while reducing the risk of bank lending, realizing risk sharing, preventing customer loss and improving customer experience.

The invention provides construction of a loss prediction model combining an echo state network and a support vector machine. Aiming at a non-ideal single model prediction effect, a classifier construction method is explored and improved, and the construction of the classifier can be divided into three aspects of a training set construction strategy, a classifier selection strategy and a predictionvalue determination strategy, comprehensively evaluating features and categories by fusing the Mahalanobis distance and the maximum information coefficient, and jointly measuring the redundancy between the features and the correlation degree between the features and the categories. The advantages of an echo state network and a support vector machine are integrated, and the problem of secondary optimization is solved through linear constraint, so that the performance of a telecom customer loss system is improved, and the prediction effect of a customer loss prediction model is improved.

The invention discloses an enterprise information loss prediction method of a double-layer structure. The method comprises the steps: enabling a system to obtain a data set, and dividing the data setinto a training set and a test set; performing double-layer training on the training set by utilizing XGBoost, LightGBM, AdaBoost and a weighted voting algorithm, outputting evaluation indexes of a classification prediction model, and finally performing result analysis and comparison on the evaluation indexes of the classification prediction model and a comparison object. By using a double-layer fusion method and an adaptive algorithm, the accuracy and precision of the customer loss prediction model are improved, and the customer loss prediction model is further perfected.

The invention provides a business hall service specification quality inspection method based on video monitoring. The business hall service specification quality inspection method comprises the following steps: A, establishing a standard image model; B, acquiring real-time video monitoring, and confirming a monitoring target in the video monitoring; C, extracting features of the monitoring target,comparing the features with the standard image model, and performing service specification quality inspection according to a comparison result; and D, processing based on the result of the service specification quality inspection, and generating a service quality inspection report. Based on video monitoring and video analysis technologies, the business hall environment and worker behaviors are monitored, so that the service quality of workers is improved, the customer complaint rate is reduced, the insufficient service quality is found by analyzing the service quality data of the workers, thedeficiencies of the workers are summarized, sorted and supervised, the service quality of the workers is effectively improved, and customer loss is avoided.

Potential customer loss is identified under circumstances where structured data may be ineffective. Game theory analytics of customer loss enable the construction of a parameter list to be screened. Concepts are associated with the parameters and their ranges. Keywords associated with the concepts are mined by an extraction engine to identify contact records of customers at risk of loss. Appropriate customized loss mitigation and customer retention strategies can be implemented.

The invention discloses an intelligent return visit method based on reinforcement learning, and the method comprises the steps: obtaining a customer portrait which comprises a plurality of feature tags for identifying customers; determining a target customer to be visited back according to the feature tag of the selected customer portrait; reading related information of the target client and establishing a call connection with the target client; inputting the related information of the target customer into a preset return visit model; and through the return visit model, generating a text dialogue content which performs dialogue with the target client, performing voice synthesis on the text dialogue content, and outputting the text dialogue content. The invention further discloses an intelligent return visit device and equipment based on reinforcement learning and a computer readable storage medium. According to the method, dialogue communication with the callback client is realized, answers are accurate and timely, the callback effect is effectively improved, and meanwhile, the client loss rate is also reduced.

The invention relates to a method and system for achieving the availability of an RMB cashier counter on a foreign trade e-commerce platform. The method is characterized in that through a process in which the RMB cashier counter monitors JOB (scripts), the availability of payment modes, including UnionPay payment, quick payment, third-party payment and platform account payment, can be automatically detected, and different processing procedures can be carried out according to different situations; if a bank payment mode is unavailable, whether a backup channel exists or not is detected; if the backup channel exists, automatic routing to a new bank of the backup channel is carried out for payment; and if the new bank payment mode is still unavailable, a bank payment icon is hidden. The method has the advantages that a client can freely choose an available payment mode during payment, and can give priority to the payment mode with the lowest cost, so that the user experience for foreign trade e-commerce platform payment is improved, client loss caused by slow payment and unsatisfactory experience on the platform is prevented, the availability of the RMB cashier counter on the foreign trade e-commerce platform is achieved, and operation risks of the platform are reduced.