35results about How to "Improve marketing effectiveness" patented technology

The invention belongs to the field of artificial intelligence and finance, and relates to a personalized copywriting generation method, which comprises the following steps: classifying all customers according to historical customer feature data to obtain different customer groups, obtaining copywriting keyword combinations of the customer groups according to historical copywriting of each customer group, and generating personalized copywriting keywords of the customer groups according to the copywriting keyword combinations; and constructing a customer group portrait according to the customer group characteristics and the customer group document keyword combination, matching a target customer group portrait according to the customer characteristics of the target customer, and generating a product recommendation scheme according to the customer characteristics and the target customer group portrait through a product recommendation model. And generating a personalized copywriting according to the customer features, the customer group portrait features and the product recommendation scheme through the copywriting generation large model. The invention further provides a personalized copywriting generation device, computer equipment and a storage medium. In addition, the invention also relates to a block chain technology, and historical customer feature data can be stored in a block chain. According to the invention, the client can be accurately positioned, and the generated copywriting can be accurately put.

The invention discloses a digital marketing system based on big data. The digital marketing system comprises a data acquisition module, a data analysis module, a data planning module, a customer relationship management module and an effect evaluation module. The data acquisition uses advanced technology to collect multi-source data, the analysis module deeply mines values, the planning module customizes personalized strategies, the customer relationship management operates efficiently, and the effect evaluation module monitors in real time and adjusts the strategies according to results. All the modules work cooperatively, precision and intelligence of digital marketing are achieved, the marketing effect and efficiency are improved, and a corresponding innovative marketing method and related technologies are applied to all the steps to ensure efficient operation of the system; according to the digital marketing system, comprehensive and accurate data collection and integration, deep intelligent analysis and mining of data values, personalized marketing planning execution, efficient customer relationship management and real-time dynamic effect evaluation and optimization are realized, the marketing effect and efficiency are improved, resource waste is reduced, customer loyalty is enhanced, and innovative development of enterprise marketing is promoted.

The invention discloses an industrial marketing management method, system and equipment based on digital twinning and a medium, belongs to the technical field of big data processing and analysis, and aims to solve the technical problem of how to collect and process various data in a cigarette marketing management process in real time, find market changes in time, improve marketing efficiency and flexibility and improve marketing efficiency and flexibility. According to the technical scheme, the method comprises the following steps: data acquisition and data cleaning: collecting full-life-cycle data of an industrial product; wherein the full life cycle data of the industrial product comprises information of each stage of design, production, test and sales; performing data modeling: performing accurate three-dimensional modeling on the industrial product by utilizing three-dimensional modeling software, constructing a virtual model of the product based on a physical law and engineering knowledge, and simulating the running state and performance of the product under various working conditions through a simulation technology; virtualizing a production scene; building a virtual product model; and simulating a virtual marketing scene.

The invention discloses a method, a system and equipment for simulating a customer approval result based on historical data learning. The method comprises the steps of user data collection and data preprocessing; constructing and training a model; model evaluation: performing prediction accuracy evaluation on the trained model by using an independent test data set, and if an evaluation result is not good, adjusting and optimizing model parameters until the evaluation result meets requirements; adjusting a marketing strategy according to a simulation result; applying the strategy to a marketing operation scene, and applying the adjusted marketing strategy to actual marketing operation; effect monitoring and iterative optimization are carried out, feedback and iterative optimization are carried out on the model, the marketing strategy or the whole process according to the monitoring result, and the prediction accuracy and the marketing effect are continuously improved. According to the method, intelligent simulation and prediction of a complex approval process are realized, the accuracy and reliability of an approval result are greatly improved, a more personalized marketing strategy and service scheme are formulated, and the marketing effect and customer satisfaction are remarkably improved.

The invention relates to the technical field of advertisement data processing, and discloses a method and device for achieving creativity generation by means of AI, and the method comprises the steps: obtaining user generation content from each social media platform in real time, and collecting hot topics of a current market; performing semantic analysis and sentiment analysis based on the hot topics to generate hot portraits; performing matching degree calculation on the hot portraits and target audience portraits of the product, and screening the hot portraits with the highest matching degree as the hot portraits of the target audience portraits; according to the hotspot portraits of the target audience portraits, performing two-dimensional screening in combination with the popularity of the hotspots to obtain target hotspot portraits; and inputting the target hotspot portrait and the associated product information into a preset deep learning model based on semantic matching, and outputting originality. The method has the advantages that the timeliness of the creativity is guaranteed, and the click rate and the conversion rate of the creativity are improved.

The invention discloses a marketing strategy execution method and related equipment. The method comprises the following steps: acquiring a historical consumption record of a user and basic information of the user; the historical consumption records of the user and the basic information of the user are input into a pre-trained consumption willingness analysis model, a user consumption willingness portrait is generated, and the consumption willingness analysis model is obtained based on training of a large number of sample historical consumption records, sample basic information and correspondingly matched sample consumption willingness portraits; calculating a strategy matching degree between each preset marketing strategy and the user consumption willingness portrait; and determining a target marketing strategy according to the preset marketing strategy with the highest strategy matching degree, and executing the target marketing strategy. According to the method and the device, the selected marketing strategy is ensured to be highly matched with the user demand, so that the pertinence and the effectiveness of the marketing activity are improved, and the marketing effect is improved.

The invention relates to the technical field of cross-border e-commerce commodity operation, and provides a commodity operation management method and system applied to cross-border e-commerce, and the method comprises the steps: carrying out the data division of commodity operation data, obtaining a divided data set, carrying out the data set optimization of the divided data set, and obtaining an optimized data set; performing multi-source analysis on the commodity operation data, and constructing an operation network of the operation commodity; querying potential users operating commodities, extracting target potential users from the potential users, constructing a screening matrix of the target potential users, and performing user screening on the target potential users to obtain screened users; and carrying out user updating on the screened users to obtain updated users, constructing an initial operation strategy of the operation commodity, carrying out supply risk assessment on a target operation user to obtain an assessment result, and constructing a commodity operation management strategy of cross-border e-commerce. According to the invention, high efficiency of commodity operation management can be improved.

The invention relates to the technical field of data processing, in particular to an intelligent recommendation system fusing big data and AI, and the system comprises a scheme obtaining module which obtains a plurality of target marketing schemes; the scheme analysis module analyzes a plurality of target marketing schemes to determine a plurality of marketing features; the data acquisition module collects a plurality of historical behavior data of a user; the data analysis module analyzes a plurality of historical behavior data to determine user characteristics; the association determination module analyzes association between the user features and the plurality of marketing features based on the initial association AI model, and determines prediction priorities of the plurality of target marketing schemes based on an association analysis result; a recommendation module constructs a user recommendation page based on the predicted priority, and determines target priorities of a plurality of target marketing schemes based on the real-time behavior data of the user; and the feedback module compares a comparison result of the prediction priority and the target priority to adjust the initial association AI model to obtain a target association AI model. According to the invention, the accuracy of personalized marketing scheme recommendation of the user is improved.

The invention discloses a short message copywriting generation method and device, equipment, a medium and a computer program product, and relates to the technical field of data processing, the method comprises the following steps: obtaining externally input generation demand information for generating a short message copywriting, the generation demand information comprising at least one of an activity theme, a target customer group and an activity keyword; the generation demand information is input into a preset large language model for prediction, multiple short message copywriting is obtained, the large language model comprises text preference strategies of different customer groups, multiple first activity texts generated according to the activity theme and the activity keyword are adjusted according to the text preference strategy corresponding to the target customer group, and multiple short message copywriting information is obtained. Obtaining a short message copywriting corresponding to each first activity text; and selecting a target short message copywriting from the plurality of short message copywriting and sending the target short message copywriting to target equipment, wherein the target equipment is equipment used by customers in the target customer group. According to the method, the short message copywriting meeting the personalized requirements of clients can be quickly generated, and the marketing effect is improved.

The invention discloses a resource allocation method and device, relates to the technical field of big data, can be used in the financial field, and comprises the following steps: in response to a received resource allocation request of a current user, obtaining first historical behavior data of the current user, and determining a target service corresponding to the resource allocation request; based on the preset configuration information of the target service, determining whether the target service needs refined resource allocation; determining a first resource library corresponding to the target service based on the first historical behavior data and historical resource allocation information of the target service in response to determining that refined resource allocation is needed; determining a first target resource to be allocated to the current user from a first resource library; and in response to determining that fine resource allocation is not needed, determining a second target resource to be allocated to the current user from a pre-configured second resource library. According to the invention, based on the user portrait and the business demand, more appropriate resources are allocated to the user, so that the accuracy of resource allocation and the marketing effect of the activity are improved.

The invention relates to the technical field of intelligent voice interaction, in particular to an AI mobile phone voice interaction method oriented to automatic marketing, which comprises the following steps of: providing a comprehensive basis for personalized marketing and improving the marketing pertinence by recognizing a user emotional state and a real-time user intention in parallel and mastering the user state; an emotion state transition network is dynamically constructed and updated, key indexes are extracted, and a user emotion change rule is analyzed, so that an interaction strategy is accurately adjusted; semantic fragments are recombined by combining emotional stability and emotional infection degree indexes, adaptive dynamic marketing verbal skill is generated, the attraction and persuasion of the verbal skill are enhanced, and the marketing effect is improved; the local NPU is utilized to synthesize emotional voices and superpose features, so that natural and vivid interaction experience is provided, and recognition of a user on marketing content is enhanced; through dynamic decision-making verbal skill strategy cross-scene switching, timely adjustment is carried out according to user changes, marketing strategy stiffness is avoided, and the marketing success rate is guaranteed.

The invention discloses a model training method, a product recommendation method, equipment, a medium and a program product, and relates to the technical field of big data, and the model training method comprises the steps: obtaining initial feature information of a training user group; performing feature extraction on the initial feature information according to the correlation between each feature information in the initial feature information and the target product acceptance degree to obtain training feature information of the training user group; and training the to-be-trained model according to the training feature information and the target hyper-parameter group to obtain a recommendation group determination model. Therefore, on one hand, the correlation between the feature information and the target product acceptance degree is fully considered, and the group determination accuracy of the recommendation group determination model is improved. And on the other hand, only the target product is recommended to the user group, so that the user with relatively low acceptance on the target product is prevented from receiving the recommendation of the target product, and the marketing effect is improved. And on the other hand, the time cost in the marketing process is reduced.

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 marketing platform management system for Internet promotion, and relates to the technical field of marketing platform management.The marketing platform management system comprises a commodity information analysis module, a customer information analysis module, a promotion information analysis module and a sales information analysis module, environment protection information of all commodities is obtained by collecting commodity information of a target enterprise, and the environment protection information is analyzed by a client; obtaining each threat commodity of each commodity of the target enterprise through the environmental protection information of each commodity of other enterprises, obtaining a green platform according to the environmental protection browsing information of each promotion platform, and obtaining each preset promotion platform according to the promotion advertisement quantity, the effective customer quantity and the potential customer quantity of each threat commodity of the green platform; the promotion platform is selected for promotion according to the provided budget, then the promotion scheme is changed according to the sales volume of the promoted commodities, the promotion platform is selected according to the environmental protection feature information of the commodities, and the pertinence of promotion is enhanced.

The embodiment of the invention discloses a business marketing method and system, computer equipment and a storage medium. The method is applied to a business marketing system, the business marketing system comprises a business platform and at least one cooperation platform, and the method comprises the steps that the cooperation platform obtains a putting link and target user data; performing encryption processing on the target user data to obtain a user data ciphertext; generating a target link according to the putting link and the user data ciphertext, and putting the target link to a corresponding target user terminal; when the user clicks the target link, the service platform issues a service page to the target user terminal and obtains a user data ciphertext; and decrypting the user data ciphertext according to a corresponding target decryption rule to obtain target user data, and generating and issuing a corresponding user data mask to the target user terminal, so that the user data mask is filled into a corresponding position in the service page. By implementing the method provided by the invention, the security of the user data in the marketing process can be improved.

The invention discloses an intelligent cloud customer acquisition system based on big data, which relates to the technical field of intelligent cloud customer acquisition and comprises a data acquisition module, a processing module, a calculation module and an analysis module. According to the method, various behavior characteristics of the user in the financial field are combined, so that the accurate customer portrait is constructed, the current state of the customer is reflected, the potential demand and the future trend of the customer are reflected, powerful support is provided for subsequent accurate recommendation, and the customer portrait and the financial product or service characteristics are combined, so that the user experience is improved. According to the method, accurate prediction of potential demands of customers is realized, powerful decision support is provided for financial institutions, and finally, a plurality of factors such as potential demand prediction values, market feedback data and user credit scores are comprehensively considered, so that personalized recommendation priority ranking is obtained; the sorting result not only improves the recommendation accuracy and the conversion rate, but also optimizes the resource configuration and improves the operation efficiency of the financial institution.

This application relates to heterogeneous graph analysis and corporate marketing, providing a method for recommending potential corporate clients of banks based on heterogeneous graphs. The method includes: constructing a corporate client relationship network based on corporate client data, wherein the corporate client relationship network is a heterogeneous graph containing multiple types of corporate client relationships; dividing these multiple corporate client relationships according to application scenarios to obtain multiple corporate client relationship subgraphs, and calculating similarity matrices for these subgraphs; fusing these similarity matrices to obtain a quantitative graph of corporate client relationships; and recommending potential corporate clients of the input bank user based on the quantitative graph of corporate client relationships and the input bank user data. The heterogeneous graph-based method for recommending potential corporate clients of banks provided in this application accurately recommends potential corporate clients, improving marketing effectiveness.

The invention relates to the field of data pushing, in particular to a marketing system based on a social platform. The system comprises a sharing permission endowing module, a platform product sharing module, an invitee association module, a registration judgment module, a purchase judgment module, a purchase amount statistics module and a reward distribution module. The sharing permission endowing module is used for endowing the user meeting the condition as an inviter, and the inviter has the permission of sharing the platform product link; the platform product sharing module is used for generating a platform product link according to a sharing operation request sent by an inviter and sharing the link to a target invitee; the invitee association module is used for detecting whether the invitee has a social relationship with the inviter; the registration judgment module is used for judging whether an invitee registers a platform account or not; the purchase judgment module is used for judging whether the invitee purchases the product within a set time range or not. According to the method, the user interaction and participation degree can be improved, the user sharing behavior is motivated, and strategy optimization is carried out through deep data analysis.

The invention discloses a marketing data distribution method based on a network flow algorithm, and the method comprises the steps: ingeniously converting a marketing data distribution problem into a network flow model with capacity constraint, carrying out the solving through employing a network maximum flow algorithm, taking marketing data as a source point, taking a marketing strategy as a sink point, and converting a limiting condition into flow limitation. Through the application of the network maximum flow algorithm, an optimized data distribution scheme can be efficiently calculated, and the requirement of an enterprise for data fine management is met. The efficiency of data distribution and the fine management level are remarkably improved, and the adaptability and flexibility of the system to marketing data and strategy dynamic changes are greatly enhanced. According to the scheme, the subjective influence caused by manual distribution is effectively avoided, the objectivity and fairness of the distribution result are ensured, the formulation of a marketing strategy is optimized, the marketing effect and the resource utilization rate are improved, and greater value is created for enterprises.

The invention relates to a method for dynamically generating a mobile banking activity set page, which comprises the following steps of: constructing a tree structure in which a root node represents an activity set page and a first-level node represents a service category, and dynamically generating child nodes according to marketing activity data, a DIEN model comprising an embedded layer, an interest extraction layer, an interest evolution layer and a prediction layer is used to predict the interestingness of the user to different marketing activities, and user interest prediction is realized; according to the method, the user geographic position, preference setting and interest prediction value are integrated, child node weights are calculated, a descending sorting algorithm is used for sorting the child node weights, activity set pages are dynamically arranged according to the sorting result, and personalized recommendation and efficient marketing are achieved. Through modular design and real-time dynamic updating, the system efficiency and the user experience are improved.

The invention discloses a white list processing method and device, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: receiving an activity access request, and obtaining an activity name, information of an activity party and a user identifier from the activity access request; determining an activity table of an activity party, querying an activity serial number corresponding to the activity name from the first-level partition, determining a serial number of a second-level partition corresponding to the activity serial number, and obtaining a white list from the second-level partition; the user identifier exists in the white list, forwarding the activity access request to the activity party, allowing the user to access the activity, obtaining an access result and returning the access result; otherwise, triggering alarm reminding; and acquiring access behavior information of the user to the activity, acquiring a risk scene configured for the activity in advance, acquiring corresponding data information from the risk scene, and deleting the user identifier from the white list when abnormal information exists in the data information. According to the embodiment, multi-level verification and management are performed on the activity access request, so that accurate control and risk prevention of activity access are realized.

The invention discloses a training method of a sorting model, a sorting method of contact channels and a related device. Firstly, training data is obtained, the data comprises multiple pieces of sample data with recommendation sequence labels, each piece of sample data comprises a sample user, N contact channels of the user and corresponding trimming information sets, and the recommendation sequence labels are used for indicating recommendation sequences of the contact channels. The trimming information set is extracted from a historical full-amount information set including a basic information set of the customer, a historical insurance policy information set, a historical marketing contact time sequence information set, a historical active interaction time sequence information set and a historical customer contact opportunity time sequence information set. And then inputting the training data into a neural network for training, and finally obtaining a sorting model. By using various data in a historical full-amount information set, the model can determine an optimal contact channel recommendation sequence based on the learned mutual dependency relationship between different channels, so that the marketing effect and the customer satisfaction are improved.

The invention provides a marketing strategy processing method and device based on customer data, and the method comprises the steps: building a corresponding multimedia content generation model based on a preset deep learning model, obtaining batch customer data and an image material library, and carrying out the processing of a marketing strategy based on the multimedia content generation model, the customer data and the image material library, generating a corresponding multimedia marketing material, obtaining a marketing strategy for the multimedia marketing material, pushing the multimedia marketing material to a target customer group based on the marketing strategy, constructing a corresponding target customer tendency model based on a preset machine learning algorithm and the customer data, and obtaining a purchase willingness of the target customer group based on the target customer tendency model, and adjusting a marketing strategy of the multimedia marketing material based on the purchase willingness of the target customer group.

The present disclosure relates to a method, device and system for controlling an outbound marketing process, the method comprising: predicting a designated customer data set through a target model to obtain a prediction result, wherein the target model is a model obtained by training a model based on the outbound marketing data of existing outbound customers; obtaining a list of target customers to be marketed and corresponding customer types based on the prediction result; for each target customer in the target customer list, when the customer type of the target customer is a first type, triggering an automatic outbound calling terminal to perform outbound marketing processing on the target customer; and when the customer type of the target customer is a second type, triggering a manual outbound calling terminal to perform outbound marketing processing on the target customer.

The invention discloses an e-commerce platform flow pushing method and system for shopping cart commodity directional display, and the system comprises a basic information acquisition unit, a data analysis unit and a flow pushing information output unit, and relates to the technical field of e-commerce platform flow pushing, and solves the problem that incomplete data analysis cannot fit the actual condition of a user, and the user experience is improved. In order to solve the technical problems of poor user experience due to the fact that a user purchases commodities according to the purchase record of the user, the method performs classification processing on the purchased commodities according to the purchase record of the user, analyzes whether the user purchases the commodities by active search or flow pushing in the classification processing process, and performs different analyses according to different conditions, so that the user experience is improved. According to the method, the corresponding stream pushing information is generated, meanwhile, the commodities collected by the user are analyzed in the analysis process, whether collection records exist or not is judged, and reasonable stream pushing is carried out in combination with the real-time information of similar products, so that the actual situation of the user can be fit, and the experience feeling of the user is improved; and meanwhile, the commodity marketing effect brought by the plug flow can also be improved.

This application relates to a method, apparatus, device, and medium for managing integrated online and offline marketing channels. The method includes: grouping and processing data based on original channel attribute data to generate a channel priority model; cleaning customer interaction path records in interaction logs to generate a cleaned path record set; identifying bottlenecks based on the cleaned path record set to generate a bottleneck set; integrating the bottleneck set with historical promotion effect records to generate an optimized interaction path; evaluating available indicators in the resource pool to generate an adjustment plan; if the adjustment plan's coverage is insufficient, optimizing node weights to generate an enhanced flow mechanism; and verifying customer satisfaction data based on the enhanced flow mechanism to generate an optimized configuration. This method enables efficient collaboration between online and offline marketing channels, optimizes resource allocation, and improves customer experience and marketing effectiveness.

The invention discloses a sub-account-based commodity publishing method and system, and the method comprises the steps: creating a main account, and enabling the main account to be associated with a plurality of authorized stores of an e-commerce platform; setting at least one sub-account based on the main account, and allocating an authorized shop for the sub-account; creating a first public rule based on the main account, wherein the first public rule is synchronized to each sub-account when being applied to the authorized store; a target sub-account is determined in the sub-accounts, a second public rule and a personal rule are created based on the target sub-account, the second public rule can be viewed or applied by the main account and any sub-account, and the personal rule can only be viewed or applied by the target sub-account; and obtaining commodity release data, processing the commodity release data based on any one of the first public rule, the second public rule or the personal rule to obtain target commodity data, and executing a commodity release operation. The claim rule can be flexibly adjusted or applied for the shop, so that the commodity release efficiency is improved.

The invention provides a marketing method based on cross-platform design synchronization, and relates to the technical field of marketing methods, and the method comprises the steps: obtaining the login data, interaction data, total customer interaction number and purchase data of a customer on a platform in the recent week, and calculating the liveness of the customer; obtaining the number of customers on each platform and the number of platform users of each platform, calculating the customer activity coefficient of each platform according to the number of newly added users in one week, the number of active users in one week and the number of platforms, predicting the customer activity trend of each platform, and calculating the resource allocation ratio with the number of potential customers of each platform; according to the method, marketing resources are distributed, theme features, product style features and platform style features of products for marketing each time are obtained, a feature coincidence rate is calculated, product style feature types are selected, a comprehensive profit space and a popularity value of each type of platform are calculated, product popularity indexes are obtained, and hot product names are screened out to serve as main marketing products.

The present invention relates to the field of e-commerce technology, and discloses a text message marketing method and system, the method comprising: obtaining text message marketing area information, and obtaining a target phone number based on the text message marketing area information; obtaining marketing text message information, analyzing the marketing text message information, and determining the marketing type; and matching the anti-shielding words corresponding to the marketing type in a pre-configured word library based on the marketing type; based on the anti-shielding words, regenerating the marketing text message information through a pre-trained natural language processing model to obtain an anti-shielding marketing text message; and sending the anti-shielding marketing short message to the target phone number. The present invention can effectively prevent text messages from being intercepted by mobile phone operators or mobile phone systems, and the anti-shielding rate of text messages is greatly improved, ensuring that marketing information can be successfully delivered to the target audience, increasing the exposure and conversion rate of marketing activities, and improving marketing effects.

The invention discloses a member point management system based on an SaaS mode, and belongs to the technical field of Internet of Things. Comprising a plurality of mutually independent member platforms, and each platform comprises a user management module, a point management module, a coupon management module, a right management module and a task management module. The user management module is used for management configuration of user basic information of members in the member platform; the point management module is used for management configuration of member behavior points and member basic point scenes in the member platform; the card and coupon management module is used for management configuration of card and coupon issuing and cancel-after-verification scenes during member marketing in the member platform; the right management module is used for management configuration of member rights in the member platform; the task management module is used for specifying a business strategy of a special marketing scene; through modular design and multi-member platform support, the system can efficiently manage a large amount of member information, and the member management efficiency is improved.