36results about How to "Improve marketing success" patented technology

The invention relates to the technical field of data processing, and discloses a prediction method and device for the secondary purchase intention of customers, used for improving the accuracy of a predicted result of the secondary purchase intention of the customers. The method comprises the following steps of: reading a target customer list from a specified storage position, acquiring historical benefits of respective customers according to customer identifiers stored in the obtained target customer list, determining the variation tendency of the historical benefits as well as the purchasing power parameters and customer maturity of the respective customers according to the historical benefits; calculating the user psychological comfort levels of the respective customers according to the acquired parameters; and generating a final marketing customer list according to customer identifiers of the customers whose user psychological comfort levels reach set conditions. Thus, the calculation workload can be reduced, the calculation speed can be improved, and therefore the operation pressure of a server can be effectively reduced. The invention also discloses an evaluation device.

The invention discloses a user communication circle relation identification method based on a communication frequency and a communication index, belonging to the technical field of operator communication circle reputation and home package recommendation marketing. The method comprises a step of calculating a communication frequency and a communication index between every two users, a step of establishing a communication circle model corresponding to the users according to the communication frequency, the communication index and a contact time period, wherein the communication circle model comprises a work circle model, a life cycle model and a comprehensive circle model, a step of establishing a user social network model based on communication circle information corresponding to the users, and a step of constructing a home relation model based on the user life circle model. According to the method, problems of poor marketing pertinence, a low cost-benefit ratio and easily caused user complaints of an existing single-client group sending mode are effectively solved, according to the method, and the rate of marketing success is significantly improved through the identification and classification of user social network relations and home relations.

The invention discloses a method for establishing and analyzing electric power user portraits based on big data technology, which can obtain historical electricity consumption information, basic attributes, payment information and appeal information of electric power users; determine the collection of classification categories of user portraits, and the influence of classification results The factor set determines the mapping relationship between the influencing factor set and the classification set; the obtained data is randomly selected, and part of it is used as a training sample, and the data is used as a prediction sample; the training sample and the prediction sample are normalized, discretized, and Attribute reduction, determine the set of influencing factors after correction; train the training samples, and use ten-fold cross-validation as the test mode, establish a power user portrait prediction model based on the naive Bayesian classifier, use the prediction model to predict the samples Data classification, mining and analysis to obtain power user portraits. The invention facilitates the forecasting and management of electric power flows.

Embodiments of the present invention provide a method and device for information push. The method obtains at least two mobile phone numbers corresponding to the user according to the user's identification, and determines at least one target mobile phone number according to the consumption records and communication records of each mobile phone number. , the at least one target mobile phone number is a subset of the at least two mobile phone numbers, and information is pushed to the at least one target mobile phone number; this method does not directly push information to all mobile phone numbers of the user, but according to each According to the consumption records and communication records of the mobile phone numbers, one or more target mobile phone numbers are selected, and information is pushed to the target mobile phone numbers of the user. Compared with the prior art, the marketing cost can be reduced, and the marketing success can also be improved. Rate.

The invention discloses a user identification method and device, and relates to the technical field of big data. A specific implementation of the method includes obtaining user data from the data warehouse by calling a preset data interface; based on the user data, determining the customer group according to the preset customer group classification component to match the corresponding customer group Recognition model; call the recognition model engine, select the data collection time point to obtain the historical data of the user, and then calculate the scoring result of the user according to the historical data, and push the user data whose scoring result meets the preset matching conditions To third-party marketing platforms. Therefore, the embodiments of the present invention can solve the problems of low accuracy in recommendation of existing housing loan products, poor user experience, and costing manpower and material resources.

The embodiment of the invention provides self-help bank information pushing method and device. The method comprises the following steps: counting up behavior information for taking actions on marketing content seen by a plurality of sample users so as to judge first attraction degrees of the marketing content to the sample users; taking sample concerning points and sample position movement paths corresponding to the plurality of sample users as samples to be input, and classifying the plurality of sample users by a first self-organized neural network to obtain a plurality of sample user sets; obtaining a target concerning point and a target position movement path of a target user according to an image recognition algorithm; and taking the target concerning point and the target position movement path as samples to be input, and obtaining a target marketing content set corresponding to the maximum value of a second attraction degree and selecting any one target marketing content from the target marketing content set to be pushed to the target user. The embodiment of the invention provides a method for accurately calculating the attraction degrees of the marketing content to customers, and the marketing success rate of the marketing content is improved.