147 results about "Digital marketing" patented technology

The invention relates to the technical field of digital marketing, in particular to an intelligent marketing data analysis system and method. According to the invention, through deep analysis of the user interaction data, the user behavior offset is accurately identified, so that the marketing strategy can be dynamically adjusted, and the putting accuracy is improved. By means of the change trend of the residence time sequence, the relative change rate is calculated in combination with the access preference, user interest hotspot distribution information is effectively extracted, and the pertinence of content recommendation is improved. Based on access path stability analysis of interest hotspots, a stable mode of user behaviors is extracted, and an advertisement putting interval is optimized, so that user loss caused by frequent putting is reduced. And user groups with fluency decline or obvious jumping behaviors are screened by utilizing change calculation of interaction fluency, so that the advertisement pushing rhythm is reasonably adjusted, and the advertisement experience is improved. The user access data is synthesized to analyze the conversion change of the user behavior after the advertisement is displayed, and the influence of different advertisement intervals on the user behavior is accurately evaluated.

The invention relates to an intelligent marketing content generation and optimization system, and belongs to the technical field of artificial intelligence and digital marketing. According to the system, through cooperative operation of the data acquisition module, the intelligent text generation module, the multi-modal synthesis module, the risk management and control module and the dynamic optimization module, whole-process closed-loop management of marketing content is realized. The data acquisition module captures unstructured data from a multi-source platform based on a user authorization protocol, semantic cleaning and structured processing are performed through a large model interface, and the problems of data dispersion and fragmentation are solved. The intelligent text generation module receives user parameters through an interactive interface, matches a preset prompt word bank, calls a large model interface to generate multi-version copywriting in batches, and supports concurrent processing of single-choice or multi-choice product lists. The multi-modal synthesis module extracts keywords according to copywriting semantics, matches pre-annotated visual materials and generates multilingual speech paraphrases, so as to ensure the consistency of graphic and text information. The risk management and control module intercepts sensitive content in real time based on an industry rule base, and guarantees output compliance. And the dynamic optimization module integrates the user behavior data to generate a delivery strategy, updates a prompt word bank and a generation model through a closed-loop feedback mechanism, and realizes dynamic adaptation of contents and market demands. Compared with a traditional method, the system has the advantages that the content generation efficiency, the cross-modal matching precision and the compliance control level are remarkably improved, and the system is suitable for the global digital marketing requirements of multiple industry scenes such as e-commerce, industrial equipment and cross-border trade.

The invention discloses a multi-agent cooperative driven AI marketing content generation method, and belongs to the technical field of artificial intelligence and digital marketing, the whole process of marketing content from planning to generation and auditing is completed through cooperative work of a plurality of AI agents with different functions, and the method comprises the steps that S1, a strategy planning agent plans the marketing content direction and key points, generating a content creative outline or scheme; s2, creating a specific content material by the creative generation agent according to the content creative outline or scheme; s3, the content auditing agent continuously monitors the generated content and audits the content; s4, the creative generation agent reads the modification suggestions and modifies the modification suggestions; s5, after the content auditing agent passes auditing, final marketing content is output; according to the multi-agent collaborative driven AI marketing content generation method provided by the invention, the AI agents with different functions cooperate with each other to jointly complete the whole process from content planning to generation and auditing, so that the generation quality and efficiency of the marketing content are remarkably improved.

The invention discloses a cross-border advertisement accurate delivery method, system and device based on a user portrait, relates to the technical field of cross-border digital marketing, and discloses the cross-border advertisement accurate delivery method, system and device based on the user portrait, which generates an accurate user portrait by integrating cross-regional behavior data. An advertisement putting strategy is dynamically calculated in combination with exchange rate, tax and logistics economic parameters, and compliance adaptation is performed based on legal and cultural rules, so that the problems of single data dimension, inaccurate user portraits and lack of economic variables in the prior art are solved; the method has the advantages that the cross-border advertisement putting accuracy and conversion effect are improved, and the compliance risk is reduced.

The invention discloses a multi-modal generation-based agricultural product brand digital marketing method and system, and the method and system collect multi-source data related to a target agricultural product, carry out the preprocessing, and construct an agricultural product culture knowledge graph; based on a graph convolutional network, a potential diffusion model and a multi-modal fusion Transform prediction network, constructing a visual generation model, receiving an agricultural product culture knowledge graph and a specific demand description statement input by a user by the visual generation model, and outputting a prediction value of a key marketing index; and performing parameter updating and iterative optimization on the visual generation model to form a closed loop, and applying the optimized visual generation model to complete the generation and effect prediction of the agricultural product marketing image-text. According to the method, a complete process from cultural element mining, visual content automatic generation, market effect prediction to strategy closed-loop optimization is constructed, and the problems of visual generation blindness and effect evaluation hysteresis in agricultural product brand digital marketing are solved.

The invention provides an electric power marketing digitalization method based on a business platform, and the method comprises the steps: recognizing an electric power marketing business scene, and generating a scene feature identifier; calling a capability matching engine of a service platform according to the scene feature identifier; matching a target atomic power set in an atomic power library of a business platform through the capability matching engine; dynamically arranging and generating a digital marketing process instance based on the target atomic power set; executing the digital marketing process instance, and collecting process operation data in real time; inputting the process operation data into a quality monitoring module of a service platform for anomaly detection; according to the anomaly detection result, triggering a process optimization instruction to a capability matching engine; and updating the atomic power matching strategy based on the process optimization instruction and re-executing the matching operation. The risk management and control capability and the operation efficiency of power marketing can be improved, and the economic benefits and the service stability of power enterprises are guaranteed.

The invention relates to the technical field of artificial intelligence-driven digital marketing, in particular to an AI-based new media intelligent marketing method, which comprises the following steps of: 1, carrying out cross-platform user behavior fusion modeling; 2, constructing a multi-modal content gene pool: analyzing a visual focus area and a text emotional tendency of historical content, and generating a content gene vector; 3, dynamic content generation and real-time optimization, wherein initial marketing content is generated according to the space-time behavior matrix retrieval gene bank; user interaction behaviors are monitored in real time, elements in a visual focus area are dynamically replaced, and the emotion intensity of the copywriting is adjusted; and step 4, closed-loop strategy optimization: a dynamic effect index is calculated by fusing multi-platform indexes, a gene variation mechanism is triggered when the index continuously decreases, and cross-platform compensation content is generated based on failed user behaviors. By analyzing the cross-platform behavior and the content preference of the user, the user demand can be accurately predicted, and the content more conforming to the personalized preference of the user is provided.

The invention discloses an enterprise overseas marketing automation service method based on multi-mode AI cooperation, and relates to the technical field of artificial intelligence and digital marketing. According to the method, enterprise multi-modal data is aggregated through an intelligent data center, an AI model is driven to automatically generate an independent station page and a marketing video adaptive to a target market, and the independent station page and the marketing video are synchronously published to a social media platform. A cross-platform intelligent customer service module is deployed in the system, user consultation is analyzed in real time, a preset notification rule is triggered, and response efficiency and compliance are guaranteed. And dynamically optimizing the display content of the master station based on a multi-modal AI scoring mechanism, and realizing accurate recommendation in combination with user behavior analysis. Compared with a traditional method, the system solves the problems of multi-platform operation splitting, manual response delay, poor content adaptability and the like through multi-AI model collaboration and automatic process integration, and remarkably improves the overseas marketing efficiency and precision.

The invention relates to a construction scheme of a consumer financial marketing system. The construction scheme comprises the following steps: constructing a user full-life-cycle digital marketing system; constructing a customer data platform to integrate customer data; a data-driven closed-loop marketing whole process is realized; a marketing automation technology is applied; and an end-to-end marketing integration capability is constructed. According to the method, the reach rate is improved, and by constructing a user full-life-cycle digital marketing system, precise marketing and personalized services can be realized, so that the reach rate of marketing activities is remarkably improved.

The invention relates to the technical field of digital people, and provides a method and equipment for generating a digital people video, which can be applied to a digital marketing scene. According to the method, the generation of the digital human video is divided into an audio generation process and a video generation process, when the audio is generated, a target text, an emotion parameter and a reference audio are taken as input, and the target audio of the target text is broadcasted by the sound of a reference person in the reference video and a set emotion, so that sound cloning is realized, the degree of violation of the generated digital human video is reduced, and the user experience is improved. And the text features are extracted from two dimensions of characters and pronunciation, so that the pronunciation accuracy during sound cloning is ensured. When the video is generated, the cloned target audio and the cloned reference video are used as input, and the fidelity of the digital human video is improved through expression and mouth shape matching, so that a reference person can quickly and efficiently generate vivid digital human videos with different broadcast contents only by shooting one reference video without shooting one by one, thereby reducing the manufacturing cost of the digital human video, and improving the user experience. And the video production efficiency is improved.

The invention relates to the field of digital marketing, and discloses a video understanding-oriented hierarchical spatio-temporal semantic extraction method, which analyzes video content through a three-stage progressive analysis framework: firstly, detecting an object instance in a key frame sequence and constructing a spatio-temporal trajectory to ensure object identity continuity; modeling an object state evolution law by using a recurrent neural network, and quantifying an interaction relationship between objects; and finally, constructing an event causal graph based on the state mutation points, and generating a directed causal chain through a statistical causal test algorithm. Video content is abstracted into event causal logic from pixel features, a semantic path of'track-state-causal 'is formed, structured semantic description of decisions can be directly driven, video semantics and user behavior data are coupled, user preference portraits are dynamically constructed, and personalized material generation is guided.

The invention provides a digital marketing method and system, a storage medium and a computer, and the method comprises the steps: obtaining multi-dimensional data of a customer group, encrypting the data, and integrating the encrypted data; carrying out feature extraction on the integrated data based on a distributed big data calculation framework; performing label setting on customers in the customer group based on the extracted features to form a to-be-screened customer group, and performing intelligent product matching according to the customers in the to-be-screened customer group to form a matching white list of the products and the customers; and a marketing model is constructed, the matched white list is evaluated and analyzed according to the marketing model, so that the purchase intention of the customer is quantified, and the intention customer is screened out for product marketing recommendation. According to the digital marketing method provided by the invention, the target intention customer can be accurately obtained, and the marketing conversion rate is improved.

The invention discloses a marketing management method and system based on machine learning, and relates to the field of digital marketing, and the method comprises the steps: collecting consumer transaction records and user interaction data, constructing a data transmission channel through a distributed message module, and carrying out the abnormal value detection and field standardization processing, and obtaining structured data; inputting the structured data into a feature calculation engine to obtain basic purchase behavior features and geographic spatial-temporal features, and generating a multi-dimensional behavior feature matrix through sliding window statistics and a time sequence decomposition algorithm; and inputting the multi-dimensional behavior feature matrix into a graph neural network for behavior pattern mining, and generating a user embedding vector. According to the method, the anti-fact data set is constructed through tendency score matching, the causal forest is utilized to quantify the grouping heterogeneous processing effect, the real increment income and the RO I of the strategy are accurately calculated, the deviation problem of traditional mean value evaluation is solved, and dynamic optimization of budget is realized.

The invention relates to the technical field of digital marketing, and discloses a digital marketing system based on big data, which comprises a multi-modal data acquisition module used for collecting original behavior data of a user on an e-commerce platform, a social media platform and a search platform; the cross-modal feature alignment module is used for performing space-time alignment and feature mapping on texts, images and behavior sequences in the original behavior data to generate cross-platform alignment features; and the dual-channel generation type interest modeling module is used for extracting a time sequence mode through a dominant behavior channel based on cross-platform alignment features, generating hidden interest representation in combination with a potential vector channel, and separating long-term interest from short-term dynamic interest by utilizing orthogonal constraints. According to the method, a double-channel generation type interest modeling module is adopted, the hidden interest detection rate is increased, and compared with a static label matching method based on collaborative filtering in the prior art, the technical bottleneck that potential demands of users are not completely captured, and recommendation deviation is caused by long-term and short-term interest coupling is solved.

The invention discloses an intelligent video editing optimization system and method based on target audience prediction, and belongs to the technical field of artificial intelligence and digital marketing. According to the method, dynamic analysis of target audience features and real-time adaptation of a video editing strategy are realized through a programmed automatic process, and the problems of high manual dependency, poor cross-culture adaptability, strategy updating lagging and the like in the traditional technology are solved. The method specifically comprises the following steps: calling a third-party platform application program interface to obtain user behavior data, and generating a dynamic audience portrait by using an artificial intelligence large model; shot selection, duration distribution and culture adaptation of video content are optimized through a reinforcement learning algorithm on the basis of portraits, a shot selection module dynamically distributes technical parameter close-up and cost comparison content according to user role types, and a culture adaptation module calls a taboo library to automatically replace sensitive elements; a synchronous test is carried out by generating multiple versions of videos, closed-loop feedback iteration is realized based on a user click rate and a conversion rate index, and an editing strategy is continuously optimized. Compared with a traditional method, the system has the advantages that the cross-culture adaptation precision, the strategy response speed and the user conversion effect of the video content are remarkably improved through cooperation of the artificial intelligence model and the programmed decision engine, and the system is suitable for precision marketing requirements of multiple scenes such as cross-border e-commerce and industrial equipment.

The invention discloses a novel digital marketing collaboration method and system suitable for small and medium-sized banks, and relates to the field of marketing collaboration, and the method comprises the steps: obtaining the user attribute of a target user; constructing a user portrait of the target user according to the user attribute; analyzing the demand information through a preset CNN-BiLSTM model to determine a demand intention of the target user; performing matching degree verification on the demand intention according to the user portrait; converting the demand intention into a marketing task index; obtaining resource information of all departments; determining evaluation indexes of all departments according to department resource information and marketing task indexes in combination with game theory empowerment and multi-criterion compromise solution sorting; comparing the evaluation index with a preset evaluation threshold value; and if the evaluation index is smaller than a preset evaluation threshold value, determining a marketing task allocation department by using a preset screening model. The marketing efficiency of small and medium-sized banks can be effectively improved.

The invention belongs to the technical field of advertisement putting, and discloses an accurate customer obtaining and advertisement putting system and method based on big data. The method comprises the following steps: S1, multi-source data acquisition: acquiring Internet public data, enterprise private domain data and third-party compliance data to form a comprehensive data pool; s2, data structured storage: the collected data are classified and stored, and an index is established. According to the method, through the collaborative application of multiple technologies such as integrated distributed crawlers, generative adversarial networks, Kalman filtering, edge calculation, multiple linear regression and Lasso regularization, full-link optimization from data acquisition to effect landing is realized, the core problems of inaccurate customer acquisition and poor advertisement effect in the prior art are solved, and the service life of the advertisement is prolonged. Manual intervention cost is reduced through an automatic mechanism, the comprehensive goals of improving customer obtaining precision, optimizing advertisement effect, reducing marketing cost and guaranteeing long-term effectiveness are finally achieved, and a more systematic and more efficient technical support is provided for enterprise digital marketing.

The invention relates to the technical field of digital marketing management, and discloses a Malus hupehensis cloud digital marketing service management platform. The system comprises a marketing service management module, a marketing data stability analysis module, a marketing strategy configuration module and a marketing execution optimization module. Wherein the marketing service management module collects global marketing data and constructs a multi-dimensional historical marketing data set; a marketing data stability analysis module traverses the data set for stability analysis, and outputs product, channel and user behavior stability factors; the marketing strategy configuration module takes the stability factors as indexes, and searches and determines a target marketing strategy decision value in a marketing strategy configuration space in a centralized manner; the marketing execution optimization module generates an execution scheme based on the decision value and optimizes execution process data in real time through a marketing strategy analyzer. According to the platform, the whole-process systematic management of marketing data is realized, the marketing management efficiency and strategy accuracy are improved, and enterprises are assisted to adapt to the change of a digital marketing environment.

The invention provides a digital marketing effect analysis method and system based on big data, and the method comprises the steps: obtaining browsing behavior data of a user for different marketing contents under different marketing channels, and integrating and storing the browsing behavior data; analyzing the browsing behavior data on the basis of the integration and storage results, determining progressive conversion rates of different marketing contents in each marketing stage under different marketing channels, performing correlation analysis on the progressive conversion rates of each marketing content in each marketing stage, and determining user conversion contributions under different marketing channels; and determining the return on investment of different marketing channels based on the user conversion contribution, and performing tabulation visualization display on the return on investment of different marketing channels. According to the method, the user can intuitively and effectively understand the marketing effects of different marketing channels, and meanwhile, the reliability and the accuracy of digital marketing effect analysis are improved.

The invention discloses a digital marketing content interaction generation method adaptive to multi-scene delivery of a large model, and relates to the technical field of interaction generation. According to the method, by setting an envelope boundary set modeling mechanism, behavior transition characteristics of a user in different content paths can be accurately described, high-value interaction nodes are effectively identified, and blindness and redundancy of content display are avoided; meanwhile, a double-channel feedback mechanism divides real-time behaviors of the user into high-speed feedback and verification feedback, collaborative linkage of high-frequency response and long-term optimization is achieved, and instantaneity of content scheduling and stability of a strategy are both considered. And in combination with a dynamic exposure frequency matrix and an ordering and rearranging strategy, content delivery has structural self-adaption and multi-scene generalization capabilities, and personalized accuracy and user response efficiency of digital marketing driven by a large model are remarkably improved.

Embodiments of the present disclosure disclose a service request processing method and device, electronic equipment and a computer readable medium. A specific embodiment of the method comprises: in response to receiving a service participation request, querying object participation flow information corresponding to the service participation request; determining the number of historical participations of the object according to the object participation flow information; constructing an object participation flow identifier according to the number of historical participations of the object and service object information; and storing the object participation flow identifier in a database corresponding to the object participation flow information. The embodiment is related to digital marketing, realizes user concurrency inventory restriction in a lock-free manner, and meets the user dimension inventory restriction of a business scenario.

The application discloses a route data processing method and device, and relates to the technical field of digital marketing. The specific implementation of the method comprises the following steps: acquiring historical query data corresponding to a plurality of routes; performing continuous processing on the historical query data corresponding to the plurality of routes respectively, and determining continuous processing results; determining one or more target routes and a target coverage time period corresponding to each target route according to a preset coverage time period and the continuous processing results; and acquiring route data corresponding to each target route according to the target coverage time period corresponding to each target route, and storing the route data in a cache. According to the actual route resource use scene, the implementation can maximize the use of the cost of consideration, determine an accurate and continuous route resource coverage range, process special time periods, respond to users in time to improve user experience, prevent interference of abnormal data, and improve operation and management efficiency.

This invention relates to the field of commission settlement technology and discloses a real-time settlement system for digital marketing commissions based on a group-buying platform. The system includes a payment traceability unit, a commission analysis unit, a payment verification unit, and a real-time settlement unit. Through the collaboration of multiple units, it overcomes the shortcomings of traditional solutions where payment success and commission settlement status are inconsistent due to network fluctuations or lost callbacks. Specifically, the payment traceability unit generates an unforgeable settlement traceability identifier; the commission analysis unit generates a commission settlement benchmark form containing the total commission amount and the amounts for each promoter without relying on real-time callbacks; the payment verification unit performs anti-interference comparison using dynamic time-window verification factors and amount deviations, and automatically triggers a secondary push in case of anomalies; and finally, the real-time settlement unit generates a unique transfer authorization code to complete fund transfer and comparison storage. This solution ensures the real-time nature, consistency, and tamper-proof nature of marketing commission settlement.

The application is suitable for the technical field of data processing, and provides a visitor information processing method and device, a terminal and a storage medium, wherein the method comprises the following steps: obtaining visitor data based on a preset digital marketing material; a data collection item is set in the digital marketing material; a set number of target data are selected from the visitor data as information factors based on a target data collection item; the information factors are encoded based on data encoding parameters corresponding to the target data collection item, so as to obtain visitor identification information; and the visitor identification information and other data in the visitor data are stored in a visitor database in association, wherein the other data are data in the visitor data except the target data. The scheme can ensure that the generated visitor identification information can meet the information uniqueness requirement of digital marketing, and ensure the effective implementation of subsequent data analysis.

The application relates to the technical field of digital marketing data processing, and in particular to a marketing data synthesis and enhancement method and system based on a generative adversarial network. The method comprises the following steps: acquiring original marketing data, extracting multi-modal features, and inputting the multi-modal features into a generative adversarial network comprising a generator, a reality discriminator and an effect discriminator; using the effect discriminator to evaluate the probability of the synthesized data producing a positive marketing effect and generating a signal; calculating a joint loss function of the generator and dynamically adjusting a weight coefficient, and updating the generator parameters according to the joint loss function and the weight coefficient to optimize the quality of the synthesized data; and finally mixing the optimized synthesized data and the original data to form an enhanced data set. The application realizes the automation and intelligentization of marketing data synthesis, significantly improves the marketing effect while guaranteeing the data authenticity, and effectively protects the data privacy and security.

The present application relates to the technical field of digital marketing and search marketing, and particularly relates to a large model global search marketing layered delivery attribution joint optimization method and system, the method and system acquire global marketing data and generate query semantic representation and intent recognition, construct layered delivery units and randomly shunt four groups; in the trigger time window, the trigger value is obtained by correcting the search volume based on the benchmark prediction, and the inter-layer migration strength is counted; in the capture time window, the capture value is obtained by predicting and correcting the conversion; the layered delivery strategy is output under the joint optimization of the total budget constraint, the migration strength and the cost combined with the double reward signals, the unified trigger and capture incremental criteria are reduced, the individual tendency and fluctuation are reduced; the layered fine regulation is realized by the semantic intent and the inter-layer migration strength; the two types of costs and the double rewards are jointly optimized under the total budget constraint, the collaborative delivery strategy is output, and the overall income is improved.

This invention belongs to the field of digital marketing technology. It discloses an intelligent analysis and optimization system based on short video platform traffic data, comprising: acquiring short video platform traffic trajectory data and interaction fingerprint features to construct a content performance profile library; classifying traffic flows and drawing a domain popularity star map; detecting algorithm pulses and user preference migration traces to form a fluctuation feature spectrum; interpreting historical traffic data, mapping seasonal traffic rhythm rules, and constructing a trend prediction model; applying it to target content to generate performance prediction results and transforming them into content frequency adjustment schemes; implementing real-time effect monitoring and establishing a feedback loop. This invention achieves intelligent analysis and automatic optimization of short video content delivery, accurately predicting content performance trends and dynamically adjusting delivery strategies, effectively improving platform traffic conversion efficiency.

The utility model relates to a workbench convenient for digital marketing, which comprises an advertising machine body, the front side of the advertising machine body is provided with a supporting mechanism, and the bottom of the advertising machine body is provided with a moving mechanism; the supporting mechanism comprises a box body, the box body is fixedly installed on the front side of the advertising machine body, a rotating rod is rotatably installed in the box body, two connecting rods are fixedly installed on the outer surface of the rotating rod, a supporting frame is fixedly installed between the bottoms of the two connecting rods, and an auxiliary part is arranged at the top of the box body. And a locking piece is arranged on the left side of the box body. According to the workbench convenient for digital marketing, the advertising machine body can be supported through the supporting frame, compared with a traditional advertising machine supported only through a base, the design has higher stability, and the angle of the supporting frame can be adjusted according to actual needs; and the advertising machine body can be kept in a stable state in different use scenes.

An information processing device stores medical content information viewable or browsable on a Web site and tag information classifying the medical content information to be associated with each other; stores user behavior information that associates user identification information, the tag information corresponding to the medical content information viewed or browsed by a user, and a number of times of viewing or browsing per the tag information with one another; stores user attribute information that associates the user identification information and attribute information including viewing / browsing situation information of the medical content information viewed or browsed by the user with each other; normalizes the number of times of viewing or browsing per the tag information to represent a frequency of viewing or browsing by the user; and applies factor analysis processing to the user behavior information after the normalizing to calculate a predetermined number of common factors.

The invention provides a data processing method and device, a rule configuration method and device, equipment, a medium and a product, and relates to the field of user interface design, the technical field of streaming data processing and the technical field of digital marketing. The data processing method comprises the following steps: calling a real-time stream calculation engine to calculate a plurality of order transaction data based on a pre-configured conversion rule in response to receiving a plurality of order transaction data for a plurality of to-be-processed orders issued by an order system, and generating conversion data, the conversion data represents a conversion value for converting the transaction resources of the plurality of orders to be processed into special resource consumption, and the conversion rule represents a conversion mode for converting the transaction resources of the orders into special resource consumption.