26results about How to "Precision marketing" patented technology

The invention discloses a real-time cultural tourism path optimization and adjustment system based on big data analysis, and relates to the technical field of cultural tourism path optimizing.The system comprises an acquisition and analysis module, the acquisition and analysis module is connected with a combination and matching module, the combination and matching module is connected with a path optimization module, and the path optimization module is connected with a data processing module. The path optimization module is connected with an interaction feedback module, and the collection and analysis module is used for collecting tourism behavior characteristic information of tourists in real time by using a big data analysis technology. According to the real-time cultural tourism path optimization and adjustment system based on big data analysis, a personalized model is established, tourism paths can be customized for tourists, unique tourism requirements and preferences of the tourists are met, the satisfaction degree and participation degree of the tourists in the tourism process are improved, the tourism paths can be adjusted in time according to real-time external data, and the tourism efficiency is improved. The tourists are prevented from being caught in unfavorable conditions such as congestion and severe weather, and smooth and efficient travel itinerary is ensured.

The invention discloses an intelligent commodity management method, and relates to the technical field of commodity management. Through the design of the whole method, the efficiency can be improved, the intelligent system can automatically manage a plurality of goods management tasks such as inventory management, purchase decision making and demand prediction, manual intervention is reduced, the management efficiency is improved, inventory optimization is facilitated, the intelligent system can accurately predict demands through data analysis and prediction algorithms, and the management efficiency is improved. The inventory level is optimized according to the prediction result, the inventory overstock or stockout phenomenon is avoided, the inventory turnover rate is improved, the cost is reduced conveniently, the intelligent system can help enterprises to optimize purchasing strategies and reduce the inventory cost, the purchasing cost is reduced through price optimization and other modes, and therefore the overall cost of the enterprises is reduced, and the enterprise experience is improved. The customer satisfaction can be improved conveniently under the overall application, and the customer satisfaction can be improved and the customer loyalty can be enhanced by meeting customer requirements in time, accurately predicting the market trend and providing personalized services and intelligent commodity management.

The invention relates to the field of artificial intelligence shopping, in particular to a shopping mall system of an intelligent search interest recommendation algorithm, which comprises a registration and login module used for selecting a login identity and a login mode and inputting login information; the factory cloud supply module is used for updating and deploying the commodity supply information in real time; the merchant service module is used for managing commodity orders, counting service of buyers and analyzing sold commodities; the promotion and distribution module is used for carrying out advertisement putting and promotion activity promotion based on a digital transmission channel, and is also used for helping merchants to carry out management setting on distributors and formulate distribution levels, regional distribution and shareholder bonuses; the financial module is used for providing balance and points of shop members for merchant users and providing commission calculation and commission withdrawal; according to the invention, the enterprise operation efficiency is improved, the cost is reduced, the brand influence and market competitiveness are improved, and an efficient, intelligent and integrated business management system is realized.

The invention discloses an intelligent marketing analysis and decision-making method based on customer full life cycle data, and the method comprises the steps: S1, collecting a plurality of types of heterogeneous data source information of a customer, and cleaning the plurality of types of heterogeneous data source information; s2, establishing a data lake warehouse, and storing the cleaned heterogeneous data source information into the data lake warehouse; and S3, loading and analyzing the data in the customer data lake warehouse according to different business requirements to obtain a corresponding data analysis result. According to the method, the consistency and integrity of data are ensured through data cleaning; real-time processing and analysis of large-scale data are realized, the requirements of enterprises on real-time data processing are met, and the data processing efficiency is improved; various multi-dimensional analysis tools and personalized marketing support are provided, enterprises are helped to deeply understand customer demands and behaviors, precise marketing is achieved, and the marketing effect is improved.

The invention discloses a user portrait generation method and device based on big data and electronic equipment, and relates to the field of data analysis, and the method comprises the following steps: 1, defining a plurality of project attributes based on a user personal data information base; step 2, after user authorization, acquiring a data acquisition authority under a specified item in a user personal data information base, performing data acquisition, and cleaning the acquired data; step 3, selecting a demand attribute of a certain application target; step 4, determining as selection, defining a keyword capturing template by taking a preset application target demand attribute as a reference, performing keyword capturing on the cleaned data by using the capturing template, and performing tagged classification; according to the method, data cleaning, keyword capturing and label mining are utilized to ensure that the used data are highly related to target requirements, an accurate user portrait is generated, and a keyword capturing template and label classification can be adjusted according to different application targets.

The present invention discloses a data value visualization analysis system, which relates to the field of data analysis technology, including: establishing an operation database of a target supermarket; analyzing the sales data change trend in the operation database, and evaluating the commodity sales status of the target supermarket; performing correlation analysis based on the commodity sales status of the target supermarket and the customer data in the operation database, and building a customer behavior portrait database; dynamically allocating commodity thermal values ​​for inventory data in historical operation data based on the customer behavior portrait database and the commodity sales status of the target supermarket, and obtaining the dynamic thermal vector index of the inventory commodities of the target supermarket; adjusting the operation strategy plan of the target supermarket based on the dynamic thermal vector index of the inventory commodities of the target supermarket. The advantages of the present invention are: improving the operation efficiency of supermarkets and realizing precision marketing.

The invention relates to an ETC (Electronic Toll Collection) system based on an Internet of Things mode, which comprises a distributed database, a processing center, a service registration center, a service governance center, a monitoring platform and an application center, the AI middle station comprises a data access unit, a data processing unit, a data storage unit, a label extraction unit, a model training unit and a model application unit. According to the system, multi-scene and full-process application of ETC data is realized, the ETC value can be deeply mined, the data utilization rate is high, the data analysis effect is ideal, the usability of ETC is improved, and the value increment of the ETC data is promoted.

The invention discloses a recommendation method and device, equipment, a storage medium and a product, and relates to the technical field of artificial intelligence. According to the method, the target graph data is constructed by acquiring the information of the multiple user groups, so that the relation among the user groups, the services subscribed by the users and the devices used by the users is clearly and structurally expressed, and the accuracy of subsequent spectral clustering is ensured; according to the method, spectral clustering is carried out on the target map data, and unsubscribed services and unused equipment in the same cluster are recommended to the user group based on the cluster of the clustering result, so that more accurate marketing is realized, and contents which better meet the requirements of the user are recommended to the user.

The invention discloses a financial scene marketing generation system and method, and the system serves as a key turn for integrating multi-head data, deepening the understanding of a user, and optimizing the operation of a product. Access safety control, multi-terminal connection management, target data extraction, data privacy desensitization and integration of multi-terminal data into a bank mobile application platform (such as a mobile bank APP) are performed on core bank systems such as an account management system and a risk management system in a bank, and user behavior tracking is performed on external clients of the bank application in the using process. Interest preference inference is carried out based on interaction intention understanding and multi-head data analysis, and real-time recommendation pushing, pushing content skipping and interaction evaluation feedback are carried out in combination with recommendation content management, so that precise marketing meeting personalized requirements of users is realized.

The invention relates to the technical field of page development, and discloses a dynamic page layout and content distribution method, system and device, and the key point of the technical scheme is that the method comprises the following steps: S1, creating a page layout template in a content distribution system, configuring layout information for the page layout template, creating a scene code for a scene, establishing association with the page layout template; creating a content distribution strategy according to the scene, associating different unit contents in the content distribution strategy, and associating a corresponding customer group for each unit content; s2, in response to the page demand request, creating a new page, and integrating an SDK (Software Development Kit) provided for the new page and a content distribution system; a scene code is configured for the new page, and the new page obtains a corresponding page layout template and layout information according to the scene code; and S3, performing page drawing on the new page through the SDK according to the returned page layout template and layout information.

The application discloses a multimedia publicity page promotion method and system, and technical scheme points are as follows: a multimedia publicity page promotion method comprises the following steps: S1, performing promotion analysis: including analyzing publicity purposes and audience groups, determining a network public activity theme, and selecting a network promotion tool; S2, generating and manufacturing publicity pages: according to a result of the promotion analysis, drawing an electronic file and a text page of the publicity pages; S3, publishing the publicity on the network; S4, integrating information after acquisition; S5, feeding back the publicity pages; S6, opening a video conference: uploading an opinion book to the video conference to discuss and acquire a publicity scheme; and S7, secondary publicity. The multimedia publicity page promotion method and system have good publicity page promotion capability, can realize accurate marketing, have the capability of integrating promotion feedback, and the method steps are simple and easy to implement.

The invention provides a new retail system with bidirectional connection between the Internet and a physical store and an operation method thereof, and relates to the field of retail, and the method comprises the following steps: S1, after a consumer purchases a commodity offline, scanning a QR code of the commodity by using a mobile terminal; entering a corresponding applet shopping mall in the mobile terminal system; s2, the consumer activates a member and obtains a corresponding point; S3, the consumer enters a corresponding application program in the applet shopping mall through a preset entry module; s4, after the consumer shares the application program shopping mall commodity page, a preset point is obtained; s5, the consumer can obtain rebate through system sharing purchase or recommended purchase of a predetermined number of commodities at a specified agent; through a novel retail offline and online 020 interactive business mode, the sales space is expanded by relying on offline resource advantages, consumption users are quickly accumulated through offline code scanning points, bidirectional communication between traditional consumption and the Internet is realized, and a continuous and stable consumption ecological closed loop for high-viscosity users is constructed.

The invention relates to the technical field of shopping mall marketing, and particularly discloses a personalized content recommendation method and system based on collaborative filtering. Drainage configuration information is obtained, a drainage link is obtained according to the drainage configuration information, and the drainage configuration information comprises basic information, distribution rule information, welcome information and landing page template information; link type information of a drainage link is obtained according to the basic information, application mode information is obtained according to the link type information, and the link type information comprises special link information and universal link information; according to the method, a plurality of multi-user live codes and drainage links are created through the drainage configuration information, and corresponding scene labels and welcome words are configured, so that after a merchant places the live codes in different drainage scenes, the drainage effect of each channel can be effectively evaluated, and the drainage efficiency is improved. Therefore, a basis can be provided for determining resource allocation and marketing key points.

The present invention discloses a real-time optimization and adjustment system for cultural tourism paths based on big data analysis, which relates to the field of cultural tourism path optimization technology, including a collection and analysis module, the collection and analysis module is connected to a combination and matching module, the combination and matching module is connected to a path optimization module, and the path optimization module is connected to an interactive feedback module, the collection and analysis module is used to collect tourist behavior feature information in real time, using big data analysis technology. The real-time optimization and adjustment system for cultural tourism paths based on big data analysis establishes a personalized model, can tailor tourist paths for tourists, meet their unique travel needs and preferences, improve tourists' satisfaction and participation in the travel process, can timely adjust the travel path according to real-time external data, avoid tourists from falling into unfavorable situations such as congestion and bad weather, and ensure smooth and efficient travel itineraries.

The application relates to the technical field of Internet, and provides a precise marketing method, device and equipment based on user consumption data, which comprises the following steps: dividing a data set into a majority class data set and a minority class data set after normalizing the consumption data; sorting the Mahalanobis distance of each sample in the minority class data set and then dividing the sorted samples into several subsets to calculate the minimum Mahalanobis distance; taking the samples in different subsets as parent samples by using the MAHAKIL algorithm with a random parameter, iteratively generating offspring samples, and training a user group classifier by taking the offspring samples with a Mahalanobis distance greater than or equal to the minimum Mahalanobis distance from the parent samples as a new minority class data set to perform precise marketing on different user groups; and balancing the sample quantity relationship between the minority class data set and the majority class data set can make the classifier accurately identify the minority class users, avoid the bias towards a certain class of users caused by the quantity difference of the training data set, and improve the precision of marketing.

The embodiment of the invention discloses a small and micro financial marketing data analysis and effect statistics method and device and computer equipment. The method comprises the following steps: in an activity planning stage, positioning a target customer group; setting a message transmission mechanism; capturing an interaction behavior of the target customer group according to the message passing mechanism to obtain initial data; performing effect statistics and deep analysis on the initial data to obtain an analysis result; and continuously optimizing resource allocation according to the analysis result. By implementing the method provided by the embodiment of the invention, the problem of effect statistics caused by customer group diversity due to business diversity in marketing activities of the small and micro financial industry and association relationship complexity can be effectively solved.

The present invention discloses a tobacco-based big data management method, which relates to the technical field of intelligent management, including matching seller information according to the seller name, establishing a consumer database according to customer tags, calculating the seller's confidence, building a monitoring model, and testing the monitoring model, calculating the distribution ratio of the producer's information, generating a planting distribution strategy, matching the optimal transportation scheduling route and the number of transport vehicles, tracking the path of the transport vehicle, and issuing a transportation warning signal. The beneficial effects of the present invention are: by dividing the management area and the numbered sub-area, the overall efficiency and productivity are improved, a consumer database is established, and customer satisfaction and loyalty are improved. Through the monitoring model, it is beneficial to the security and stability of transactions, the planting distribution strategy is formulated, the waste of resources is reduced, the path of the transport vehicle is tracked in real time, the distribution efficiency is improved, and the safety and timeliness of the goods are guaranteed.

The invention relates to the technical field of data processing and electronic commerce, in particular to a multi-terminal transaction platform based on data mining, which comprises a data acquisition and preprocessing module used for acquiring, integrating, cleaning and storing user data and commodity data; the security and privacy protection module is used for encrypting storage and setting an access control strategy and an authentication mechanism; the personalized recommendation and prediction module is used for carrying out personalized recommendation on commodities and predicting future demands of users; the supply chain management module is used for predicting a sales result and optimizing inventory management; the commodity bidding module is used for auction bidding; the risk early warning module is used for monitoring abnormal behaviors in real time and dividing early warning signals into different grades; the optimization and improvement module is used for carrying out regular evaluation and summarization and is also used for improving and optimizing a model and an algorithm; through data mining and analysis, personalized transaction experience is provided for different terminal users, and the platform operation efficiency and the user experience are improved.

The present invention is applicable to the field of data processing technology, and in particular to a thematic data processing method and system, the method comprising: S100: establishing a word set of thematic keywords, classifying the word set into a preset data platform for matching, defining the matching result as an initial event, extracting the initial viewpoint, creating a monitoring tree, and embedding the hierarchical architecture. By constructing a monitoring tree, the present invention can monitor the spread of the initial event in real time, help users to grasp the public opinion dynamics related to themselves in a timely manner, identify potential crisis signals, and quickly make public relations responses to avoid the spread and fermentation of negative information. It can also understand the current public concerns and emotional tendencies, adjust marketing strategies, and through a linked list, can help users fully understand the complete path from the emergence to the spread of a topic, formulate more accurate marketing and public relations strategies, and provide decision support for users.

The invention relates to the technical field of computers, and provides a vehicle recommendation method and an intelligent exhibition hall digital vehicle distribution interaction system, and the method comprises the steps: obtaining the initial vehicle purchase behavior information of a customer; generating car purchase demand information of the customer based on the initial car purchase behavior information; recommending a pre-selected vehicle model and a pre-selected accessory to the customer based on the vehicle purchase demand information; wherein the pre-selected vehicle types comprise a plurality of vehicle types, the pre-selected accessories comprise a plurality of types of accessories, and each type of accessories comprises a plurality of accessories; responding to a target vehicle model selected by the customer from the preselected vehicle models and a target accessory selected by the customer from the preselected accessories, and combining the target vehicle model and the target accessory to obtain a target vehicle; and displaying the target vehicle to the customer. According to the method, vehicle types and accessories can be selected according to preferences and requirements of customers, and personalized vehicle purchase experience is achieved.

The invention relates to the field of commodity demand prediction, in particular to a commodity demand prediction method and system for a live broadcast platform, and the method comprises the steps: recognizing the video content which is being played in a live broadcast room according to the moment when a user enters the live broadcast room; analyzing the video content, and extracting keywords of the video content according to an analysis result; obtaining the popularity degree of the commodities in the live broadcast room by counting the frequency of searching the commodities by the users in the live broadcast room; on the basis of the keywords of the extracted video content and the popularity degree of the commodities, analyzing the completed transactions in the live broadcast room to determine a purchase reason proportion, and on the basis of the purchase reason proportion and the number of the commodities in the live broadcast room, predicting the future transaction volume of the live broadcast commodities; and recording the purchase reason of the user completing the transaction so as to determine the pushing mode of the future live broadcast. And the shopping experience and the purchasing efficiency of the user in the live broadcasting room are improved.

The invention relates to the technical field of financial science and technology, in particular to a product pushing method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring key feature data of a target user, wherein the key feature data comprises multi-dimensional key identity feature data and multi-dimensional key behavior feature data; inputting the key feature data of the target user into a target super network model to obtain a target product output by the target super network model; generating a target push path according to the target product and the target browsing habit data of the target user; and pushing the target product to the target user according to the target pushing path.

The invention discloses a user network behavior analysis and prediction method. The method comprises the following steps: obtaining a user network behavior information set; extracting a consumption behavior set and a consumption preorder behavior set from the user network behavior information set; performing correlation analysis on the consumption behavior set and the consumption preorder behavior set to obtain a user payment prediction model; and processing the acquired user network behavior information by using the user payment prediction model to obtain network content prediction information and a prediction value of the user payment possibility. According to the method, the user network behavior data is deeply extracted and mined, and the quantitative relationship between the user behavior and the payment intention is accurately established, so that network contents such as a video matrix are optimized, and the network traffic conversion rate is improved.

The embodiment of the invention provides a method and device for obtaining and processing social media messages and electronic equipment, and belongs to the technical field of data processing.The method comprises the steps that an HTML file containing an element structure set H is created, and a social media platform JavaScriptSDK is loaded and initialized to form an instance; a login button is arranged on a user interface, the attribute set of the login button is B, and the SDK instance is loaded to request an access right to the platform during clicking; the processing platform returns a response, and if effective authorization information is contained, the SDK instance is used for obtaining user information and extracting key data; initiating a call request containing a parameter set P to a predefined API endpoint, analyzing a response to obtain an access token and a page ID, and calling an API to obtain a session list; and for each session, calling an API (Application Program Interface) by using specific parameters to obtain a message list, and carrying out automatic reply, classified storage or statistical analysis on the messages according to requirements. According to the invention, the accuracy and safety of message processing are improved.

The invention provides a group delivery method and computing equipment, and the method comprises the steps: constructing a label vector knowledge base which is used for carrying out the vectorization storage of the labels of commodity groups; obtaining a natural language question which is input by a user and is used for article selection; processing the natural language question to obtain a question vector; according to the problem vector, performing preliminary screening matching in the label vector knowledge base to obtain a preliminarily screened label list; generating a tag combination result from the natural language question and the tag list through a large language model; and putting the pallets according to the label combination result. According to the technical scheme of the invention, the work difficulty related to commodity labels can be reduced, the efficiency of a commodity selection process is improved, the complexity of commodity distribution is reduced, and commodity assembly and delivery can be better carried out.