99 results about "Marketing efficiency" patented technology

The invention relates to the technical field of artificial intelligence, in particular to an AI intelligent customer obtaining processing method and system, and the method comprises the following steps: collecting interaction data of a user and a platform, summarizing click, browsing duration and frequency information, extracting a user activity mode through an RNN and an LSTM network, analyzing the interest and behavior mode of the user, and generating a user behavior feature library. According to the method, the client acquisition process is optimized through data analysis and behavior prediction, the method does not depend on a traditional marketing means, user data are accurately analyzed through a sequence model, deep understanding of user behaviors is achieved, the accuracy of market segmentation is improved through refined analysis, it is ensured that marketing activities are matched with a target client group, and the marketing efficiency is improved. According to the method, the conversion rate is remarkably improved, the marketing means can be rapidly adjusted by means of intention recognition and real-time data analysis, synchronization with user requirements is ensured, the customer extension cost of the entity store is reduced by continuously integrating customer feedback and marketing data, and the problem that an entity store operator is difficult to obtain customers is solved.

The invention relates to a precision marketing method and system based on real-time data flow. The method comprises the following steps: collecting customer behavior data in real time; preprocessing and dynamically marking the customer behavior data to generate preprocessed customer behavior data; performing real-time analysis on the preprocessed customer behavior data by using a deep learning algorithm, and generating a customer portrait in combination with historical behaviors, preference changes and situational features of the customer; according to the customer portrait and the customer real-time behavior, a marketing strategy is generated in real time through an intelligent decision routing technology, and recommendation content in the marketing strategy is dynamically adjusted based on the customer interaction behavior in the customer real-time behavior; according to the marketing strategy, the service recommendation corresponding to the marketing strategy is sent to the customer contact point, and through a real-time feedback mechanism, the marketing strategy is dynamically optimized according to the real-time response of the customer. The method has the effect of improving the marketing efficiency.

The invention discloses an enterprise micro-marketing auxiliary method and system based on a large language model. The efficiency and effect of marketing are improved by using the large language model. According to the method, by integrating a vector database, an embedded model and a context learning technology, the capabilities of real-time understanding of user intentions, personalized reply and quick service change adaptation are realized. The method has the core advantages of accurate user demand analysis, personalized service provision and efficient knowledge retrieval system. By analyzing user behaviors and dialogue records, product recommendation and marketing strategies according with user preferences can be provided. In addition, the method also has a real-time verbal skill updating capability, so that the timeliness and accuracy of information are ensured; the automatic order information extraction technology improves the information processing efficiency, and reduces the time and cost of manual operation. According to the invention, the marketing efficiency is improved, the interactive experience between the user and the customer service is enhanced, and competitive advantages are provided for enterprises in the market with intense competition.

The invention relates to the technical field of digital marketing, and discloses an omni-channel marketing funnel intelligent attribution model and an automatic budget distribution system, and the model comprises a data collection module which is used for collecting data through a contact recording device and a user identification device which are disposed at a marketing terminal, and a behavior tracking device and a channel classification device which are disposed at a user side. Acquiring information such as multi-channel marketing contact interaction data, user behavior data and channel types; the path analysis module realizes data path analysis through time sequence synchronization of a time alignment unit, feature matching of a path association unit and dynamic adjustment of a computing power scheduling unit; the attribution calculation module generates the conversion attribution weight of each channel based on the matching data; and the budget mapping module establishes a dynamic mapping relationship between the weight and the budget and updates the dynamic mapping relationship. The system outputs the attribution result through the model application module, and the budget execution module distributes the budget according to the dynamic mapping, so that the channel contribution can be accurately evaluated, the scientific distribution of the marketing budget is realized, and the marketing efficiency and the rate of return on investment are improved.

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 an intelligent marketing system based on user portraits and behavior prediction, which belongs to the field of artificial intelligence, and comprises multi-source data acquisition and integration: a diversified data acquisition interface is configured, and user multi-type data can be acquired from multiple channels such as an e-commerce platform, social media, a search engine and an enterprise CRM system; comprising basic information, browsing and purchasing behavior records, social interaction information, search preferences and emotion-related text data. Data of different formats and sources are integrated into a unified data set by using preprocessing means such as data cleaning, duplicate removal and standardization; according to the invention, through accurate user portrait and behavior prediction, an enterprise can accurately grasp the demand preference of a target customer, accurate pushing of marketing information is realized, the hit rate and the conversion rate of marketing activities are greatly improved, and the marketing effect is effectively improved; according to user value and behavior prediction, marketing resources are reasonably allocated, resource waste is avoided, and enterprise marketing efficiency is improved.

The invention discloses a marketing strategy optimization management system based on six elements of order transaction, and belongs to the field of communication management systems, in terms of data acquisition, multi-source comprehensive information collection enables enterprises to perceive consumer demands in all directions and no longer blindly grope, a dynamic feature modeling unit fuses various kinds of data into six-dimensional feature vectors, and the six-dimensional feature vectors are integrated into a database; multiple factors of commodities, users and festivals are balanced and considered, a solid foundation is laid for a marketing strategy, a commodity-festival-user ternary association graph constructed by a festival graph generation engine enables commodities to be pushed in a targeted manner, a personalized strategy is generated by an intelligent decision module, the matching degree of the commodities and consumers is improved, and the marketing efficiency is improved. The overall continuous feedback optimization mechanism of the system enables the marketing strategy to be like a continuously evolved life entity, can better adapt to the market change, and improves the sales probability of commodities.

The invention discloses a smart marketing management method and system based on AI artificial intelligence. The smart marketing management system comprises a data collection and preprocessing module, a market dynamic prediction module, a competing product analysis module, an advertisement strategy generation module and a strategy execution and feedback module. The intelligent marketing management system collects related data of marketing advertisements on the market, collects market dynamic data, and monitors and updates advertisement strategies and market performance of competitive products in real time; and according to the competitive product analysis result and the real-time advertisement effect data, an advertisement putting strategy is automatically adjusted through an AI artificial intelligence technology. Through introduction of an AI technology, market and competitive product data are analyzed in real time, an advertisement strategy is automatically adjusted, advertisement content and putting channels are optimized, and advertisement budget and time frequency are dynamically adjusted, so that high intelligence and automation are achieved in advertisement decision making, reasonable configuration of marketing resources is achieved through a multi-dimensional optimization strategy, and the marketing efficiency is improved. And the overall effect and the return on investment of the advertisement are obviously improved.

The invention discloses an electronic commerce precision marketing intelligent system and method fusing AI personalized recommendation. The system comprises a multi-source data acquisition module, a data preprocessing module, a user portrait construction module, a real-time behavior monitoring module, a recommendation algorithm module, a marketing scheme generation module, a marketing effect evaluation module and a feedback optimization module. According to the method, the comprehensive user portrait is constructed by integrating the multi-dimensional user data, and the mixed recommendation algorithm is applied, so that the user requirements can be deeply mined, accurate personalized recommendation is realized, and the matching degree between the recommendation result and the actual requirements of the user is improved; by adopting the real-time behavior monitoring module and the recommendation algorithm module, the recommendation strategy can be updated in time according to the real-time behavior of the user, so that the recommendation better fits the current shopping intention of the user; by adopting the marketing scheme generation module, diversified marketing schemes can be generated, an effective marketing effect evaluation and feedback optimization mechanism is combined, marketing activities can be continuously optimized, and the marketing efficiency and income of merchants are improved.

The invention provides a marketing material generation method and system, electronic equipment and a storage medium. The method comprises the following steps: acquiring marketing materials and customer data; according to the marketing material and the customer data, determining an initial preference of the customer for the marketing material; performing emotion recognition on the customer data to obtain an emotion recognition result; determining marketing materials of the customer according to the emotion recognition result and the initial preference; different customers correspond to different marketing materials; namely, through a plurality of links of data collection, data analysis, emotion recognition, personalized marketing and the like, demands and preferences of customers can be better known, and more effective marketing strategies are formulated to attract and retain the customers, so that the efficiency of customizing marketing materials for the users is improved, all customers can be oriented, emotion connection with the customers is emphasized, and the marketing efficiency is improved. Marketing materials have infectivity and stimulate interests and resonance of customers.

The invention provides a marketing information identification method and device based on vehicle positioning, equipment and a medium, and relates to the technical field of financial science and technology. According to the method, the parking characteristics and the parking information of the vehicle can be accurately obtained by obtaining the vehicle positioning data. By analyzing the vehicle parking characteristics, the vehicle parking information is identified, so that high-frequency parking points in the use process of the vehicle can be identified, and potential collecting and distributing places can be identified. A clustering algorithm is used to analyze the vehicle parking information, and the target distribution place with concentrated vehicle rental demands can be effectively identified. By identifying the target marketing object in the preset radiation range of the target distribution place, the potential customer group can be more accurately positioned, so that the identification accuracy and the identification efficiency of the marketing information are improved, the customer obtaining cost is reduced, more accurate market positioning and customer service are provided, the pertinence and the effectiveness of the marketing activity are enhanced, and the marketing efficiency is improved. And the marketing efficiency and the conversion rate are improved.

The invention relates to the technical field of user behavior analysis marketing, in particular to an intelligent marketing system and method based on customer behavior real-time calculation, and the system comprises an edge behavior collection unit, a cleaning and desensitization unit, a spatial-temporal feature coding unit, a real-time prediction unit and a collaborative decision-making unit. According to the method, an edge behavior acquisition unit captures native data such as page staying duration and contact tracks, a cleaning and desensitization unit generates compliance time sequence fragments, and a spatial-temporal feature coding unit converts the data into spatial-temporal feature vectors containing time decay weights, topological graph nodes and behavior integrity indexes; the real-time prediction unit fuses multi-dimensional vectors through a graph neural network and outputs real-time preference probability distribution of commodity categories, and the collaborative decision-making unit dynamically allocates computing power and generates an optimal marketing action set, so that the problems of large user real-time intention capture deviation and lagging computing power allocation of traditional marketing are solved, the marketing accuracy and timeliness are improved, and the marketing efficiency is improved. And resource waste is reduced.

The invention provides a marketing strategy obtaining method and device, electronic equipment and a storage medium, and relates to the technical field of product marketing, and the method comprises the steps: comparing first prediction values of conversion indexes of different candidate marketing strategies under the condition of excluding the influence of a historical marketing strategy; the method comprises the following steps: obtaining a candidate marketing strategy, namely an optimal candidate marketing strategy, with the best individual effect, and then determining the degree of influence of a historical marketing strategy on the marketing effect of the optimal candidate marketing strategy by utilizing a conversion index predicted value under two conditions of considering the influence of the historical marketing strategy and excluding the influence of the historical marketing strategy. Therefore, the final possible marketing effect is attributed, namely the contribution degree of the historical marketing strategy and the optimal candidate influence strategy to the final marketing effect is determined. The final marketing strategy is formulated by referring to the attribution result, it is guaranteed that the to-be-executed marketing strategy has a good marketing effect, and the marketing efficiency is improved.

The invention relates to the technical field of big data and artificial intelligence, and discloses an artificial intelligence advertisement design and marketing recommendation platform based on big data, which comprises a multi-source data acquisition module, a dynamic portrait modeling module, an AI advertisement generation engine, a cross-platform recommendation decision module and an effect tracking and compliance auditing module. By integrating multi-source data and utilizing an artificial intelligence algorithm to construct a label system, interests and demands of users can be accurately grasped, precise advertisement putting is realized, and the advertisement putting effect is improved; a personalized recommendation system generated through an AI advertisement generation engine can significantly improve the user satisfaction and participation degree, and through a cross-platform recommendation decision module, the distribution of advertisement resources is further optimized, and the overall marketing efficiency is improved; and the effect tracking and compliance auditing module ensures the transparency and legality of the advertisement activity, so that the advertisement putting is more accurate and effective.

The invention belongs to the technical field of brand propagation and marketing management, and particularly relates to a one-stop self-service brand propagation and marketing management intelligent platform, which comprises a brand resource management module used for creating and publishing the propagation content of a brand; the multi-channel marketing management module is used for performing multi-channel marketing and management on the brand propagation content published by the brand resource management module; the user data management and analysis module is used for managing and analyzing the user data; the marketing activity planning and executing module is used for planning and executing marketing activities; and the intelligent marketing decision support module is used for recommending personalized marketing activities to the user according to the user data analyzed by the user data management and analysis module. Through one-stop management and an automatic process, the time and labor cost of marketing activity planning, execution and evaluation are reduced, and the marketing efficiency is improved.

The invention relates to the technical field of big data analysis, and particularly discloses a marketing management system based on big data analysis. The system comprises a data fusion center, a real-time portrait engine, a multi-contact attribution analysis module, a strategy optimizer and an execution gateway, and multi-source user data are integrated, a user interest model is dynamically updated, contact contribution weights are quantized, and marketing strategies are intelligently generated. Universe user view construction, real-time interest tracking, accurate attribution analysis and automatic marketing decision making are realized, and finally the marketing efficiency and the input-output ratio are improved.

The invention discloses a marketing management method and system based on big data analysis, and relates to the technical field of marketing management, and the method comprises the steps: analyzing the behavior data of a marketing target user, and constructing a marketing target user portrait; outputting a marketing strategy of the marketing target user and the associated user through the behavior record of the associated user in combination with the portrayal analysis of the marketing target user; adjusting marketing strategies of the marketing target user and the associated user based on the market data; the adjusted marketing strategy is applied to market activities, and the marketing process and the market risk condition are monitored in real time; marketing achievements of all stages are obtained based on real-time monitoring, the marketing achievements are analyzed, a marketing change trend is recognized, a marketing strategy optimization mechanism is triggered based on the marketing change trend, and a marketing strategy is adjusted and optimized. Accurate marketing, strategy dynamic adjustment and resource optimal configuration are realized, and the marketing efficiency and effect are remarkably improved.

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 the technical field of promotion, discloses a promotion management method and system based on big data, and particularly discloses a method for obtaining the order number and the number of browsers of a movie ticketing platform in a promotion period; dividing the promotion cycle into time periods, and marking the time periods of the promotion cycle according to the order demand coefficient to determine whether the time periods are marked as hot order placing time periods; establishing a dense classification model based on a convolutional neural network, and classifying each time period of the promotion cycle through the dense classification model to determine whether the time period belongs to a dense order placing time period; obtaining order prediction data of the dense order placing time period at a future target time point through the target prediction model; and selecting the dense order placing time period according to the promotion target time length to obtain a promotion plan time period, and determining the ticket putting amount corresponding to the promotion plan time period. According to the invention, the promotion and marketing efficiency can be effectively improved, and the promotion and marketing optimization method and system based on the data analysis and prediction model are realized, so that the sales conversion rate of promotion is improved.

The invention provides an information triggering channel optimization method and system, electronic equipment and a storage medium. The method comprises the following steps: determining first data of a user; extracting basic features related to a touch effect from the portrait data, and constructing a feature matrix in combination with a touch channel, historical marketing information and user response data; training the feature matrix by using a machine learning algorithm to obtain a response prediction model capable of predicting user response data; the response prediction model is used for predicting user response data of each arrival channel according to the portrait data of the user, the arrival channel data and the marketing information; predicting the user according to the trained response prediction model, and determining an optimal access channel of different marketing information of the user; namely, by collecting and analyzing the response data of the user on different channels, the model capable of predicting the response data of the customer is trained, then the bank is guided to select the optimal touch channel, the touch efficiency is high, and the marketing efficiency and the customer satisfaction degree are improved.

The invention relates to an enterprise customer relationship management system and a management method thereof, and the method comprises the following steps: a manager inputs user information in a user management module, sets the role and the corresponding authority of a user, collects new customer information, adds the new customer information into the system, classifies customers, and stores the classified customers into a database; customer data are analyzed to know customer demands and preferences, potential sales opportunities are tracked and managed in the sales management module, customer problems, complaints and demands are recorded in the customer service and support module, and the processing progress is tracked; client support and solutions are provided, marketing activities are designed and executed in the market management module, client reports and data analysis are generated in the statistics and analysis module, and client growth, sales trends and the like are provided; according to the invention, through a comprehensive customer management tool and a data analysis function, an enterprise is helped to improve customer satisfaction, enhance customer loyalty and improve sales and marketing efficiency.

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 provides a potential customer mining method and system based on data mining, and relates to the technical field of data mining, and the method comprises the steps: 1, collecting customer related data, including basic information, behavior data, transaction data and customer feedback data of customers; 2, cleaning, converting and integrating the collected data; according to the invention, through deep analysis of multi-dimensional customer data, customer groups with high potential purchase possibility can be accurately identified, blindness of a traditional marketing mode is avoided, an enterprise can intensively invest marketing resources to customers who are most likely to generate rewards, and through a prediction result based on a data mining model, the marketing efficiency of the enterprise is improved. According to the invention, enterprises can formulate personalized marketing strategies, accurately push product information and customize preferential activities according to potential customers, and the response rate of the customers to the marketing activities is improved, so that the sales cycle is shortened, and the marketing efficiency is improved.

The invention discloses a discount coupon issuing and verification method based on an offline store SaaS system, and the method comprises the following steps: A, a merchant creates a discount coupon activity in the SaaS system, sets the type, denomination, validity period and other information of discount coupons, and can select different types of discount coupons according to the demands and marketing strategies of the merchant, so that the discount coupons can be issued to the merchant; the coupons can be full-reduction coupons, discount coupons, gift coupons and the like, and meanwhile, merchants can set the denominations and the validity periods of the coupons so as to attract more customers. In the marketing aspect, coupon attributes are accurately set, target customers are accurately touched, the conversion rate is improved, abuse is avoided, operation, two-dimensional code receiving and cancel-after-verification are convenient and efficient, manpower and time cost is saved, data statistics is achieved, the system updates the coupon state in real time, cancel-after-verification information is fed back, reports are generated to assist merchants in analysis and decision making, and the marketing efficiency is improved. Consumer behaviors and preferences are deeply observed, powerful support is provided for optimizing marketing strategies, and the operation benefits and competitiveness of stores are effectively improved.

The invention discloses a private domain operation method based on enterprise WeChat. The private domain operation method comprises the following steps: constructing a customer portrait; personalized content is pushed; intelligent customer service and interaction; community operation and management; and data-driven decision making. Through the AI technology, accurate construction of customer portraits and intelligent pushing of personalized contents are realized, and the marketing efficiency and accuracy are improved.

The invention provides a customer classification management method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining customer contact data of target customers in different databases, and carrying out the data preprocessing of the customer contact data, and obtaining target customer contact data; performing data analysis on the target customer contact data, judging a target transaction stage of the target customer, and determining a customer classification corresponding to the target transaction stage; and based on the target customer contact data, generating display information of the target customer under the customer classification, and sending the display information to the target terminal for display. Compared with the prior art, the embodiment of the invention has the advantages that the customer contact data of the target customer is acquired from the plurality of databases, and data analysis is performed on the target customer contact data, so that the transaction stage of the target customer can be accurately judged; according to the analysis result of the target customer contact data, the customers can be automatically classified and managed, so that an enterprise can formulate personalized marketing strategies for different types of customers, and the marketing efficiency and the conversion rate are improved.

The invention relates to the technical field of labels, in particular to a label management system for private domain drainage, firstly, the system generates a unique two-dimensional code for each commodity, the unique two-dimensional code comprises commodity identification information and private domain drainage information, the two-dimensional code can be used for warehouse-in and warehouse-out management of a warehouse and can also provide skipping of a private domain platform for consumers to scan the code, and when the commodities are put in and out of the warehouse, the commodity identification information is stored in the private domain drainage information; a worker updates an inventory state in real time by scanning a code, when a consumer scans the code, the system guides to a private domain platform according to a preset path to promote interaction between a merchant and the consumer, and the system also provides real-time acquisition and analysis of code scanning data, helps the merchant to understand a drainage effect, optimizes a marketing strategy, and improves the marketing efficiency through data-driven precise marketing. The system can push personalized contents to different consumers, and the drainage effect and the re-purchase rate are improved. According to the invention, through the design of one-code multi-purpose and one-object one-code, the functions of commodity warehousing and ex-warehouse management and private domain drainage are integrated, and the warehousing and marketing processes of the clothing industry are optimized.

The invention discloses an association rule mining and traceability analysis-based appeal attribution optimization method, and relates to the technical field of power marketing, and the method comprises the following steps: inputting the inconvenience of bill query and the unsmooth payment channel into an optimization module, outputting a comprehensive association degree and a comprehensive influence degree, and carrying out the analysis of the comprehensive association degree and the comprehensive influence degree; and an optimization measure is formulated based on the comprehensive correlation degree and the comprehensive influence degree, the measure is optimized in real time in an electric power marketing system, and then an optimization effect index is output. The method has the advantages that relevance among different appeals can be identified, follow-up analysis results are convenient to be comprehensive and accurate, a complete appeal chain can be formed to connect multiple appeal times in series, potential problem traceability analysis on power marketing is facilitated, artificial experience and judgment are reduced on the basis of a data driving mode, and power marketing efficiency is improved. Therefore, the accuracy is improved, the root cause of the customer appeal can be accurately identified, the corresponding optimization strategy can be formulated, the customer problem can be more effectively solved, and the customer satisfaction and loyalty are further improved.

The application discloses a data processing method, device and equipment and a computer readable storage medium. The method comprises the following steps: querying a triple corresponding to entity information of current communication content; performing time segmentation on the current communication content based on the triple, and obtaining each conversation window; determining a basic emotion value corresponding to each conversation window based on user image data corresponding to each conversation window, and determining a first image emotion value corresponding to each conversation window based on the basic emotion value; determining a first voice emotion value based on user voice data corresponding to each conversation window and the basic emotion value; and determining a customer preference degree corresponding to each conversation window based on the first image emotion value and the first voice emotion value. The application enriches the data dimension by collecting more sufficient data in a specific scene, improves the success rate of online marketing activities, and improves the timeliness of data application and marketing efficiency in online business marketing.

The invention relates to the field of marketing information management, and particularly discloses a marketing information management platform and method based on big data, and the method comprises the steps: firstly obtaining the basic information of stationery product market clients, the purchase information of the stationery product market clients and the research data of the stationery product sales market, and then carrying out the deep learning technology, according to the method and the system, feature extraction and correlation analysis are carried out on the three, and finally, a stationery product personalized marketing strategy is generated through a generator, so that a more accurate marketing plan is made according to the characteristics and demands of different customer groups, the marketing activity is closer to the actual demands of users, the marketing efficiency is improved, and the conversion rate is increased.