228results about How to "Precision marketing" patented technology

The invention includes a method and system to provide a competitive pricing tool so that automobile dealers can more efficiently and effectively price their used vehicles. The system achieves the optimal sales price by obtaining the relevant pricing and mileage of vehicles for sale that are similarly situated to the focus vehicle. Once the information is obtained, the system creates a value ranking for each of the vehicles for sale and for the focus vehicle. The user is then able to revise the focus vehicle pricing to determine the optimal sales price. The invention also provides information to the potential customer about the vehicle for sale, including information relating to other similar vehicles for sale in a particular geographical area that can be accessed at the point of sale, or by the customer at a later time and place. The party offering the product for sale is informed each time the customer accesses the information, thereby indicating the level of interest by the customer. The invention further provides a stocking tool to determine when to purchase additional vehicles for inventory, a merchandising view to review and revise advertisements, and an automatic description generator for the particular vehicle being sold.

The invention provides information to the potential customer about the vehicle for sale, including information relating to other similar vehicles for sale in a particular geographical area that can be accessed at the point of sale, or by the customer at a later time and place. The party offering the product for sale is informed each time the customer accesses the information, thereby indicating the level of interest by the customer.

The present invention relates to an online advertisement classified pushing method and system based on a consumer behavior data analysis and classification technology. Compared with the prior art, the online advertisement classified pushing method and system overcome the defect that potential customers cannot be mined to carry out network online advertisement pushing. The online advertisement classified pushing method comprises the following steps of: carrying out data collection and preprocessing, i.e. collecting behavior data of consumers from online mobile terminals, establishing a data pool, carrying out preprocessing operation on the data in the data pool and providing data support for subsequent data analysis and modeling; aiming at the behavior data of the consumers, carrying out modeling, i.e. establishing a topic model facing the behavior data of the consumers so as to mine relations between the consumers and online advertisement categories as well as a purchase time period; and aiming at the consumers, carrying out effective classification and aiming at different consumer categories, pushing the corresponding types of advertisements online. According to the present invention, by collecting the behavior data of the consumers on various mobile terminals, carrying out analysis and modeling on behaviors of the consumers and mining consumption habits of different consumers, effective classification of the consumers is implemented.

The invention relates to an intelligent device and a goods association recommendation method thereof. The intelligent device comprises an attribute analysis unit used for analyzing goods attributes and population consumption attributes in cash data; a customer file establishing unit used for carrying out figure labeling according to the analyzed goods attributes and population consumption attributes, carrying out classification according to the figure labeling and establishing customer files; and an association recommendation unit used for carrying out goods and corresponding coupon association recommendation according to customer consumption hobbies and previous shopping detailed data in the customer files. The goods association recommendation method comprises the following steps of: collecting the cash data in a cloud server; obtaining the cash data in the cloud server and analyzing the goods attributes and the population consumption attributes; establishing the customer files according to the analyzed goods attributes and population consumption attributes; and carrying out goods and corresponding coupon association recommendation according to data in the customer files. Thus, the intelligent device and the goods association recommendation method thereof help merchants to realize precise marketing and customized service.

The invention discloses a mobile phone advertising method based on a user consumption feature vector, and belongs to the field of mobile phone data mining and analyzing. The method includes the steps of establishing a user keyword to represent a vector according to browsing contents of a user mobile internet; establishing a user consumption feature vector of a corresponding user according to the browsing contents of the mobile internet; extracting a keyword from an advertisement experience text database and setting a keyword weight, and constructing a characteristic matrix for each user feature vector; computing each component value of the user consumption feature vector of each user; setting the mapping relations between a user consumption tag and each component of the consumption feature vector of the user within different threshold ranges; labeling a corresponding consumption tag for each user and then conducting advertising according to each component of the current consumption feature vector of the user and the mapping relation. The mobile phone advertising method can improve precision of advertising, reduces manual interference, and effectively lowers platform running cost.

A method and system for purchased-based segmentation of potential customers employs the use of actual, observed purchases instead of presumptions and correlations to improve the accuracy of segmentation and involves collecting empirical data for a client on actual purchasing behavior of a group of customers and applying statistical modeling techniques to the empirical purchasing behavior data to identify segments or clusters of the customers that exhibit similar purchasing propensity characteristics. Thereafter, the segments or clusters are further differentiated from one another according to other factors having a tendency to directly affect actual purchasing behavior of the customers within the segments or clusters, and potential customers are then identified according to a correlation with the segments or clusters for customized marketing.

The invention discloses an O2O e-commerce system facing the industry of household building materials. The system includes a mobile terminal module, a foreground website module and a background management module. The mobile terminal module includes a homepage module, a type module, an order module, a user information module and other information module. The foreground website module includes a public function module, a user management module, a merchant management module, a careful choosing module, a best-seller module and a seckill module. The background management module includes a basic setting module, a member management module, a commodity management module, an order management module, an information management module and a configuration management module. The mobile terminal module and the foreground website module perform data transmission with the background management module. The O2O e-commerce system facing the industry of the household building materials integrates offline business opportunities with the mobile internet so as to facilitate use by merchants and users and also provides a marketing platform to the merchants.

The invention discloses a WeChat marketing service platform. A management module is used for businesses using WeChat marketing service platform accounts to add WeChat official accounts and modify password setting, view background operation settlement and platform announcement, and carry out renewal management and SMS top-up on WeChat marketing service platform accounts. A basic setting module is used for setting the basic content of WeChat official accounts. A WeChat mall module is used for providing a systematic mall system for online transaction of WeChat official accounts. A micro official website module is used for businesses to set a micro official website style according to a template provided by the WeChat marketing service platform or a custom template. A micro activity module is used for businesses to set marketing activities to attract more fans. The WeChat marketing service platform is a service platform which can be understood and used by users easily and allows users to carry out marketing easily. The platform can realize precision marketing, help enterprises to establish a brand quickly, enable enterprises to better face the consumers and market in tens of millions of marketing tides and reduce labor cost, and maximize the effectiveness of WeChat.

The invention provides a telecommunication service recommendation method and system, wherein the method comprises: acquiring telecommunication service information, identity information of users, order business information and net access journal information; acquiring subject indexing of webpage documents accessed by users according to the net access journal information; setting up a user interest model according to the subject indexing of webpage documents accessed by the users and the net access journal information; acquiring the incidence relation of the user interest and the telecommunication service according to the user interest model, the telecommunication service information and the order service information; and acquiring a recommendation service list and recommending the telecommunication service according to the incidence relation of the user interest and the telecommunication service and the user interest model. According to the invention, the precision marketing of the telecommunication service is realized, and simultaneously the user experience is improved.

The invention discloses a user portrait establishing method and system based on big data, which belongs to the technical field of big data application. The user portrait establishing method based on big data comprises the steps of S1 user portrait label system constructing, S2 data preprocessing; S3 automatic sample annotating, S4 user data sampling sample imbalance processing, S5 feature engineering, S6 model training through combination of a multi-classification model and a dichotomy model and S7 model optimization. The user portrait establishing method and system based on big data can improve the accuracy of a user portrait, can construct a personalized intelligent recommendation system to realize precise marketing and precise advertising, and has good promotion and application values.

The invention discloses a commodity selling system and method based on a storage cabinet, and the system comprises a server, the storage cabinet, and a client. The client communicates with the server through a network, and the storage cabinet communicates with the server through the network. The server comprises a stock-up module, a stock module, an information publishing module, a purchasing confirmation module, a goods fetching module, and a database. The method comprises the steps that a seller publishes the sale information of a commodity for sale; a user selects and purchases the commodity for sale; and a delivery worker delivers the commodity bought by the user. The system and method greatly shortens the delivery time, and a consumer can obtain the commodity in several hours after ordering the commodity. Moreover, the selling is very active and targeted, thereby improving the turnover.

The embodiment of the invention provides a user life cycle recognition method, device, electronic equipment and storage medium, and relates to the technical field of data processing. The user life cycle recognition method comprises the steps that historical behavior data of a user focusing on a target merchandise category is acquired; based on the historical behavior data, the stage of the user inthe user life cycle corresponding to the target merchandise category is determined. According to the technical scheme, the stages of the user in the user life cycle under various merchandise categories can be recognized, so that more precise and personalized marketing is conducted on the user under various merchandise categories.

The invention discloses a tourism big data co-constructing and sharing system based on a cloud platform, and relates to the application field of the tourism big data. The system comprises a cloud storage center, a scenic area comprehensive resource system, a mobile service terminal and an intermediate processing system; the cloud storage center is used for storing tourism resource information andestablishing a database according to the tourism resource information; the scenic area comprehensive resource system is used for colleting and storing the tourism scenic area data information to formthe tourism scenic area information database, and transmitting the stored data to the intermediate processing system; the mobile service terminal is used for collecting tourist information, displayingthe tourist information and the tourism scenic area information, and feeding back the tourism experience to the scenic area comprehensive resource system; and the intermediate processing system is used for establishing the contact among a cloud storage center, the mobile service terminal and the scenic area comprehensive resource system, collecting the tourism resource information of each tourismscenic area and transmitting to the cloud storage center to store; and the tourism resource information is displayed on the mobile service terminal according to the category division of the tourism scenic area.

The invention discloses a survey method for an audience rating of digital television users. The method is characterized in that the method comprises the following steps that: a data collection step in which a data collection module is internally arranged on a middleware of a digital set-top box and is responsible for collecting user viewing behavior data; a data transmission step in which the digital set-top box is connected with an Internet network by a built-in Bluetooth or an externally connected network card and transmits the data to a server having a public network IP; a data storage process in which the server receives the data and then the data are parsed and stored to a database; a data analysis process in which the server carries out automatic analysis and statistics on the data; and a data presentation process in which a client invokes a server to carry out calculation and analyses on all indexes of the audience rating and present data of data analysis results of the reviewing behaviors. According to the invention, a set-top box with two-way transmission is supported; and user viewing behavior data is transmitted from an Internet or a metropolitan area network to a server; therefore, compared with the traditional survey mode, the survey method provided in the invention has advantages of high real-time performance, high accuracy and low cost and the like; moreover, lots of manpowers, material resources and financial resources are saved.

The invention provides a core user mining method based on a deep neural network and a graph network. The core user mining method comprises the steps of constructing a user- game history information database; Performing data preprocessing; According to the game historical sequence observation data of the game user after data preprocessing, establishing a directed graph with a game name as a node and a time sequence as an edge, and inputting the directed graph into a graph network embedding method so as to predict a game which is interested in next time; And establishing the directed graph for each game user to obtain an expression of each game, carrying out feature splicing on the obtained expression of each game and the personal information of the corresponding user, and fusing and inputthe expression and the personal information into a deep neural network so as to predict whether the user is a core player of the game or not. According to the invention, the problem of sequence prediction is solved based on the fusion method of graph network embedding and the deep neural network, the time sequence information is fully learned in the form of the graph network, and higher-level interactive expression is learned by fusing the deep learning method, so that the model prediction accuracy is improved.

The invention discloses a recommending system and method for guiding a client to handle a banking business based on big data prediction. The system comprises clients, a positioning module, network sites, a data transmission module and a prediction module; the clients portray and classify the clients; the positioning module positions the current locations of the clients and synchronously displays specific distances and predicted arriving time of the network sites; the network sites divide time into different periods and respectively calculate the average handling time of a certain business in different periods, the demand density of handling the certain business in different periods or the demand density of reserving the certain business in different periods; the data transmission module obtains data through connecting with the client, the network sites and the positioning module in real time and transmits the data to the prediction module; and the prediction module customizes recommending information for the clients. According to the system and the method provided by the invention, the recommending degree of each network site can be accurately and intelligently given out; through portraying and classifying the clients, individual recommending and precise marketing can be carried out to different clients; the efficiency is relatively high; and the cost is relatively low.

The invention relates to a multi-enterprise and multi-user screen dividing, switching, emerging and interacting method facing to service information. The method comprises the following steps that a user registers within an application program client side on mobile equipment to issue a service information inquiry request; a data network arranged at an operator side detects an information transferring request issued by a mobile client and builds the data connection between the mobile client and a cloud service capability platform arranged at an enterprise side; an information management service module of the cloud service capability platform arranged at the enterprise side queries and returns an information content related to the current login user, wherein the information content is displayed by page, and each page of the information content corresponds to the information of one enterprise; and the client side carries out information exchange with the corresponding enterprises by page after receiving a service information list returned from the cloud service capability platform arranged at the enterprise side. According to the method, the service information of the plurality of related enterprises can be checked by the user by one requirement, so that the information can be conveniently and uniformly managed and queried, the user resource can be shared by the enterprises to some degree, and the breadth of the advertisement, the service and the precision marketing can be conveniently expanded.

The invention relates to a categorized electronic coupon use prediction method and device and electronic equipment. The method comprises the steps that a model training sample is determined according to historical information of getting categorized electronic coupons of a user; the features of the user and the features of the categorized electronic coupons in the model training sample are acquired to act as sample information of the model training sample; model training is performed on the model training sample based on the preset classification model according to the sample information; and the use probability of the given categorized electronic coupons of the given user is predicted based on the trained preset classification model. The use probability of the specific user for the specific categorized electronic coupons can be predicted and different categories of coupon issuing marketing can be performed for different users so that precision marketing can be performed, the repurchase effect can be enhanced and the repurchase marketing cost can be reduced.

The invention discloses a potential customer identification method, electronic equipment and a storage medium, and the method comprises the steps: obtaining product sales data, and obtaining the datainformation of a customer from a data information platform according to the personal information of the customer; establishing corresponding label data according to the data information of the customer; matching all the user personality labels of each customer with the information of the products purchased by the customer, and taking the matched user personality labels as training samples; establishing an artificial intelligence identification model by adopting a machine learning algorithm according to the user personality label; training the artificial intelligence identification model by using the training sample; and obtaining to-be-identified user label data and inputting the to-be-identified user label data into the artificial intelligence identification model to judge whether the user is a potential customer. The daily data information of the user can be analyzed and processed to obtain the matching relationship between the personalized label of the user and the information of the product purchased by the user, so that the intelligent identification of the potential customer is carried out through the artificial intelligence identification model, and the product dealer is helped to realize precision marketing.

The invention discloses an advertisement pushing method based on big data. The method comprises the steps of according to big data accumulation, determining the attention value of each to-be-generalized webpage commodity through the commodity visiting frequency, user residence time length and commodity exposure frequency of the to-be-generalized webpage commodity to a current user; determining scores of G commodity kinds with highest correlation in each to-be-generalized webpage commodity, scores of H webpage type kinds with highest correlation in a current visited webpage, and a correlation weight between each commodity kind and the webpage type kind; determining each commodity pushing total score according to the correlation weight between the commodity kind and the webpage type kind, the score of the corresponding commodity kind, the score of the webpage type kind and the attention value of the webpage commodity; performing sequencing from a highest commodity pushing total score to a lowest commodity pushing total score; and pushing the front N to-be-generalized webpage commodities in the sequencing result through preset N advertisement positions. The advertisement pushing method can realize pushing of the commodities with high interest probability of the user and realizes accurate marketing.

The invention relates to a multi-enterprise cloud folder deployment and information interaction method facing a common client. The method specifically comprises the following steps: a plurality of enterprises deploy client content of the enterprises in a cloud folder manner; when the content is approved by verification, a service operation module carries out billing operation on the enterprises; when the billing is successful, a result is expressed in an enterprise user client to carry out information interaction between the enterprise user client and the enterprises; the enterprises can publish information and services in the same sharing cloud folder or one enterprise can publish own information and services in the cloud folder of the other enterprise under the precondition that one enterprise can obtain the allowance of the other enterprise; and the enterprise user can obtain the information and services of a plurality of enterprises at the same time. According to the multi-enterprise cloud folder deployment and information interaction method facing the common client disclosed by the invention, the convenient publishing and management of a plurality of enterprises on the same enterprise user client can be realized, and the efficiency of carrying out the information interaction on the enterprise user and the enterprises is improved; and the multi-enterprise cloud folder deployment and information interaction method is mainly used for fields of propaganda of the enterprises, data collection, membership service, depth and precision marketing, and establishment, duplication and management of a client relation and the like.

The embodiment of the present application provides a method and device for recommending orders. According to the division information of the geographical area stored in advance, the historical order data is divided to obtain the historical order data set corresponding to the array and several sub-areas in the geographical area; according to the user information , to classify the users in the sub-area; by analyzing and processing the historical order data of similar users in the same sub-area, the hot sales data of the goods and the reference standard box information are obtained, and the reference standard box information is combined with the distributor’s inventory The standard box information to be recommended in the data is matched, and the recommended order is generated and pushed to the user. Using the order recommendation method provided in this application can help users quickly and accurately obtain goods based on standard boxes that meet their own needs, and improve user experience. At the same time, since the matching degree is limited when the recommended order is generated, logistics resources are saved to a certain extent, and it is conducive to the precise marketing of the brand owner or distributor of the product.

The invention relates to a method of cloud folder arrangement and information interaction for an enterprise client terminal. The method of the cloud folder arrangement and the information interaction for the enterprise client terminal comprises steps as below: a client terminal management service module arranges content of an enterprise client terminal in the mode of cloud folders, submits to a service operation service side so that the content of the cloud folders can be audited, after approval of the audition, the client terminal management service module releases the newest content of the cloud folders to the users of the enterprise client terminal, after the business operation service side judges that the account balance of the enterprise is sufficient, an information interaction service module pushes the newest content of the cloud folders to the enterprise client terminal, and the enterprise pays for thecharging type interaction. The method of the cloud folder arrangement and the information interaction for the enterprise client terminal builds management capabilities of organizing, visiting, interacting, and auditing of the content of the enterprise client terminal based on the mode of cloud folders, effectively reduces threshold for an enterprise to enter the field of cell phone client terminals, improves efficiency of information interaction, and is mainly used for the fields of publicity of enterprise, data collection, membership service, deep precision marketing, and building, copying and management of client relationship and the like.

The invention provides a massive search query log calculation and analysis system based on a cloud platform. The invention aims at characteristics and requirements of an internet e-commerce platform,designs a structured log of a search engine, and provides the structured log data for a log analysis system to be applied, so the space required by traditional log analysis and the workload of log cleaning work are greatly reduced; an efficient e-commerce platform search query log analysis system is realized in combination with a Hadoop distributed computing platform and a big data processing algorithm, thus mining data back value; key points and excavation potential are fully grasped by feature selection of the e-commerce platform, so massive log key extraction information currently needed bythe e-commerce platform can be clearly and visually displayed, enough expansion capacity can be provided for mining of various interested features of logs, website optimization and precision marketing are achieved by analyzing behavior logs of users, personalized services are provided, and the invention has huge utilization value.

The invention relates to a marketplace indoor positioning navigation method and system based on two-dimensional bar codes. The navigation method comprises the steps that (1), two-dimensional bar code labels are established in shops of a marketplace, thereby forming a two-dimensional bar code system, and marketplace shopping guide machines are established in the marketplace; (2), mobile terminals enter marketplace center shopping guide service platform by scanning the two-dimensional bar code labels or the two-dimensional bar code labels on the touch screens of the marketplace shopping guide machines through utilization of a wireless communication network and establish connection relationships with the marketplace center shopping guide service platform, and a marketplace internal wireless communication network is responsible for data interconnection between the mobile terminals and the marketplace center shopping guide service platform; and (3), the marketplace center shopping guide service platform collets information of the two-dimensional bar code labels sent by the mobile terminals, then compares the information with a marketplace two-dimensional bar code address library, judges positions of the mobile terminals, provides positioning service for the mobile terminals and displays a marketplace map. The navigation system comprises the marketplace shopping guide machines, the two-dimensional bar code system, the mobile terminal and the marketplace center shopping guide service platform.

The invention relates to an intelligent apparatus and a method for counting people. The intelligent apparatus comprises a wireless connecting unit for wirelessly connecting a user terminal to the intelligent apparatus, a commercial activity unit for pushing commercial webpages to the user terminal, allowing users to browse advertisement and participate on-line activity or on-line transaction, and a counting unit which is used to count the user participants for each activity, the people browsing the commercials and on-line transaction people and feeds the information back to merchants. The method includes establishing communication connection between the intelligent apparatus and an external network, adapting settings and parameters of a user terminal, connecting the user terminal to the intelligent apparatus through a wireless network, pushing commercial webpages to the user terminal to allow users to browse advertisements, participate on-line activity or on-line transaction, counting user participants for each activity, people browsing commercials and on-line transaction person and feeding the information back to the merchants. In this way, accurate marketing and customized service for merchants can be facilitated.

The invention provides a bank potential credit client mining method based on a knowledge graph and a machine learning algorithm. The method comprises the following steps: 1, a sample collection stage;2, a data preprocessing stage; 3, a model training stage. The method has the advantages that an efficient XGBoost integrated classifier is used for training a potential credit granting customer prediction model, potential credit granting customers with higher marketing success rate are mined, and accurate marketing of the customers is realized; the wide application and popularization of the method provide credit clients with higher marketing values for service personnel, the method improves the work efficiency of front-line service personnel, and has great significance and application valuesfor carrying out credit servicees in banks. A mode of extracting features based on the map is applied to potential credit granting customer mining for the first time, so that the application range ofthe knowledge map is expanded, and the development of the knowledge map is further promoted; and a good effect is achieved for solving the problem of nonuniform sample treatment.