140 results about "Sales promotion" patented technology

The invention relates to the technical field of e-commerce marketing, in particular to a product marketing service platform system and method, and the system comprises a user behavior tracking module, a consumption intention analysis module, a promotion time optimization module, an inventory monitoring and discount adjustment module, and a precision marketing push module. According to the method, the commodity access frequency and cross browsing data are extracted and analyzed in real time, the consumption trend of the user in a short period is rapidly identified, consumption tendency parameters are generated, potential purchase behaviors are accurately predicted by using browsing behaviors and an interaction mode, the recommendation accuracy is improved, the real-time inventory data are combined, a discount strategy and inventory management are dynamically adjusted, and the recommendation efficiency is improved. According to the method, the promotion activity is ensured to be closely matched with the inventory state, the resource utilization efficiency is improved, precise marketing pushing is performed according to the user equipment preference, the user interaction experience is enhanced, the sales growth is promoted, and the market response speed and the marketing effect are remarkably improved.

The invention belongs to the intelligent information technology, and discloses an e-commerce platform operation system and method based on intelligent decision and dynamic optimization. The system comprises a plurality of modules of multi-source data acquisition and preprocessing, user portrait and demand prediction, intelligent commodity recommendation and the like. A recommendation algorithm fusing a knowledge graph and reinforcement learning and an inventory prediction and optimization algorithm based on dynamic time sequence analysis are innovatively adopted, and a reward function formula and an inventory cost function formula are arranged respectively. According to the method, data acquisition, user portrait construction, business operation and system optimization are realized according to collaborative operation of the system and the modules. The system can accurately recommend commodities, intelligently manage inventory, efficiently plan promotion activities, collaboratively optimize a supply chain, and improve the operation efficiency and commercial competitiveness of an e-commerce platform.

An AI-powered augmented reality (AR) system for optimizing product placement and customer loyalty. The system includes: • a user interaction data collection unit configured to monitor consumer behavior in real time in any retail scenario (point-of-sale POS, online e-commerce and shopping areas within a public virtual technology space), with the unit analyzing consumer movement patterns, engagement metrics, eye-tracking and purchase intent; • an intelligent spatial mapping module to build a contextual understanding of high-traffic zones, underutilized areas and high-quality product placements using heatmap analysis, other spatial computer algorithms and the live movement of consumers; • A model-based product placement recommender based on machine learning, which uses one or more DL-based predictive models trained by importing current sales data, historical text interaction data, and consumer preference data to suggest optimal product placement so that customers see the advertisement and are likely to click through it to ensure a conversion. • a customer-centric, real-time AR visualization interface configured to allow customers to experience digitally enhanced product presentations directly via mobile AR applications, smart glasses, or in-store digital kiosks, enabling customers to preview product placements, rotate and resize objects, and visualize interactive advertising content before purchasing; • a customized advertising and sales promotion engine configured to generate augmented reality-based marketing content and provide users with tailored promotions and interactive ads based at least in part on an analysis of consumer sentiment by the system, as well as information on location data or consumer interaction history, wherein the customized advertising and sales promotion engine personalizes the configuration instructions for advertising and sales promotion to encourage consumer interaction and achieve higher sales revenues; • A secure, cloud-based data processing and analytics unit that uses an automated engagement model to link online and in-store sales information with established activity models for product placement decisions. The unit leverages AI-powered consumer insights to continuously recommend product placement changes based on a variety of programmatic retail trends; • a privacy-friendly AI module based on federated learning and on-device AI processing, providing consumer behavior analytics while complying with global data protection regulations and preventing the use of open data; • a processing framework characterized by a low-power mode suitable for AR rendering and AI calculations, and implemented via dynamic voltage scaling and energy management techniques for seamless and sustainable operation; The system according to claim 1, wherein the user interaction data capture unit further comprises an eye-tracking and sentiment analysis sub-module, wherein the sub-module detects facial expressions, emotional reactions, and attention levels of consumers in real time to determine the effectiveness of product placements and advertising strategies.

The invention discloses an intelligent logistics supply chain management system, and the system comprises a block chain information sharing platform which is responsible for building an information sharing platform based on a block chain, inviting all participants on the supply chain to join, and storing and transmitting the data of each link of the supply chain through the distributed account book technology of the block chain; the product information tracing system is responsible for distributing a unique block chain ID for each fresh food and recording the circulation process of the fresh food in a supply chain; and the collaborative management platform is responsible for integrating and uniformly managing data of purchasing, warehousing, transportation and sales, predicting future sales trend and inventory demand change by using a random forest according to historical sales data and market trend information, and optimizing an inventory level, a reorder strategy, a sales strategy and a promotion activity plan in combination with a genetic algorithm, so as to achieve the purpose of sales promotion. The inventory cost is minimized, the sales demand is met, and the block chain information sharing platform and the collaborative management platform carry out data synchronization.

A digital promotion processing system may include a shopper device associated with a given shopper, and a promotion processing server. The promotion processing server may be configured to determine available digital promotions for a given product for purchase, each available digital promotion having different redemption terms. The promotion processing server may also be configured to cooperate with the shopper device to prompt the shopper to select one of the available digital promotions to apply toward purchase of the given product, store shopper promotion terms preference data based upon the selected digital promotion, and update the shopper promotion terms preference data based upon a plurality of new selections of available digital promotions. The promotion processing server may further be configured to generate and communicate a personalized digital promotion to the shopper device. The personalized digital promotion may have redemption terms based upon the updated shopper promotion terms preference data.

Methods and apparatus are disclosed regarding an e-commerce system that promotes sales of products based on product comparisons. Some embodiments may present a marketing message that justifies a price difference between presented products based on attribute differences between the presented products.

The invention relates to a data processing method for intelligent marketing products, and the method comprises the steps: obtaining the financial behavior data of a target user, carrying out the clustering through a machine learning algorithm, and selecting a target cluster through a preset threshold value; and defining a matching degree model to evaluate the comprehensive matching degree between the user and different loan products, and predicting the preference value of the target cluster. Then, sales promotion information is customized according to the sales target, and marketing influence factors of the sales promotion information are calculated; and calculating a recommendation score of each user for each loan product according to the matching degree and the marketing influence factor, calculating a comprehensive score according to the recommendation scores, dividing the loan products into priorities, and selecting a corresponding marketing strategy. And finally, collecting KPIs (Key Performance Indicators) related to marketing strategies, evaluating effects and adjusting strategy parameters. According to the invention, through accurate user data analysis and a personalized marketing strategy, the recommendation accuracy and marketing effect of loan products are improved, and the satisfaction and loyalty of users are enhanced.

The invention relates to a supermarket fresh commodity sales volume prediction method based on big data analysis, and belongs to the technical field of commodity sales volume prediction, and the method comprises the following operation steps: 1, carrying out the data collection and preprocessing through sensor data, historical sales data and consumer behavior analysis; 2, summarizing the data of the three angles of the person and goods yard and processing the data; missing values and abnormal values are processed, and the abnormal values and features are selected. 3, establishing a data model; feature engineering is established, data segmentation is carried out, a prediction model is selected, and then prediction and evaluation are carried out. And 4, dynamically adjusting a pricing strategy based on the predicted demand quantity and supply condition. And 5, according to the predicted sales volume data, planning sales promotion activities, order quantities and distribution arrangements in advance. And the accuracy and the real-time performance of sales volume prediction are improved. The inventory loss is effectively reduced, and the sales management efficiency of fresh commodities is improved.

The invention relates to the technical field of market analysis, in particular to a footwear market trend prediction system and method, and the system comprises a sales volume change analysis module, a time period influence analysis module, a promotion influence analysis module and a sales volume prediction evaluation module. According to the method, the change rate of the sales volume of the shoes can be effectively evaluated by analyzing the association between the sales volume data and the economic indexes, the specific influence of seasons and festivals on the sales volume is considered, the sales volume prediction is more suitable for the actual market condition by calculating the time period influence factors, and the sales promotion activity effect is analyzed. According to the method, the influence of the sales promotion activity on the sales volume can be evaluated, data support is provided for making an effective sales promotion strategy, the sales volume change trend is predicted through multi-dimensional analysis, the accuracy of market trend prediction is improved, resource allocation is optimized, an enterprise can more flexibly cope with market changes, and thus the market competitiveness and profitability are improved.

The invention relates to the technical field of rural e-commerce marketing, and discloses a rural e-commerce precision marketing method based on big data, and the method comprises the steps: dividing user data sets of all regions based on the geographic positions and consumption records of users, including purchase and browsing behavior data; determining a user type according to the purchase frequency and the commodity preference; generating a marketing strategy set and determining an execution sequence; generating recommended commodities and a promotion activity list in combination with user types, stock and the like; and associating the data to generate a precision marketing scheme. The method further relates to user data boundary determination, user type subdivision, marketing strategy dynamic adjustment, consumption potential grade division, personalized recommendation strategy generation, marketing scheme verification and correction and the like. According to the method, accurate classification and regional differentiation marketing of users are realized through big data mining, the strategy is dynamically optimized, the marketing effect and the resource utilization rate are improved, and the method is suitable for accurate operation of a rural e-commerce platform.

The invention discloses a cloud service system and method applied to logistics docking, and relates to the technical field of cloud services, and the method comprises the steps: receiving order data sent by an e-commerce platform and a dealer in real time, and obtaining the inventory data of each warehouse; analyzing order data, extracting communication features, analyzing association between order placing time and sales promotion activities, and obtaining an emergency order proportion in a specific time period of the target region; associating the order communication characteristics with the warehouse inventory data of the corresponding region, and generating an inventory allocation trigger signal when the order quantity exceeds an order quantity surge threshold value and the emergency order proportion exceeds a threshold value and is lower than an inventory safety threshold value within a preset duration after the promotion activity of the target region starts; based on the inventory allocation trigger signal, screening out surrounding warehouses, and sending a scheduling instruction to start emergency replenishment; and calling historical same-period promotion order data, analyzing an order growth trend and a replenishment amount, predicting a subsequent replenishment amount, and notifying related warehouses to prepare in advance.

The invention relates to the technical field of artificial intelligence and machine learning, in particular to an intelligent retail shelf monitoring system based on artificial intelligence image recognition. Comprising a data acquisition unit, an image recognition unit, a data processing and analysis unit, a feedback and decision support unit and a communication unit, wherein the data acquisition unit is used for acquiring state information of commodities on a shelf through a camera and a sensor which are mounted on the shelf. Multi-modal information is fused through the image recognition unit, a lightweight model is developed, a meta-learning mechanism is introduced, the recognition efficiency and precision are improved, the computing resource requirement is reduced, the model adaptability is enhanced, prediction, self-adaptive adjustment and customer subdivision of the future sales trend are generated by using a time sequence analysis model and other external factors, and the market competitiveness is improved. The sales data value is mined, the trend is accurately predicted, the inventory is dynamically optimized, retailers are helped to better plan purchasing plans and sales promotion activities, and the market competitiveness is improved.

The invention provides an e-commerce integrated order management system, and relates to the technical field of e-commerce, and the system comprises an order processing module which is used for receiving, splitting, merging and updating order states, automatically optimizing order circulation, improving the order processing efficiency, guaranteeing the real-time synchronization of the order states, and reducing the processing delay. In the invention, the data analysis module analyzes user behavior data (such as browsing, purchasing and returning) and market sales data in real time and predicts future commodity demands and sales trends by using the prediction model, and the system can automatically provide a real-time report for an operation team based on the data, so that the user experience is improved. The module helps to adjust the inventory replenishment cycle, sales promotion activities and commodity shelving plans, and has the core advantages that market changes are identified through big data analysis, response measures are automatically generated, the inventory management precision is improved, and the inventory overstock and stockout conditions are reduced.

To enhance convenience of promotions utilizing generative AI for customers using mobile terminals.SOLUTION: An information processing apparatus according to an embodiment comprises a first acquisition unit, a second acquisition unit, a first generation unit, a second generation unit, and an output control unit. The first acquisition unit acquires customer information related to a customer who enters a facility. The second acquisition unit acquires position information representing a position of the customer in the facility. The first generation unit generates first text information including the customer information and the position information. The second generation unit, by inputting the first text information into generative AI which generates a text related to a product handled in the facility in response to the input of the first text information, generates, based on a generative text generated by the generative AI, second text information for a promotion of the product described in the generative text. The output control unit outputs the second text information to a terminal device used by the customer.SELECTED DRAWING: Figure 3

According to one embodiment, an information processing device includes a control unit and a communication unit to communicate with an edge device. The control unit is configured to acquire an attribute of a customer visiting a store and generate an inquiry prompt for providing a promotional recommendation of merchandise items for sale at the store to the customer. The inquiry prompt is generated based on condition information including at least the attribute of the customer. The control unit inputs the inquiry prompt to a functionalized generative AI to generate a response, then extracts a merchandise item corresponding to description information in the generated response from among the various merchandise items available for sale at the store, and generates sales promotion information for the extracted merchandise item based on merchandise information of the extracted merchandise item and the description information in the generated response.

The present invention relates to the field of retail data analysis technology, and specifically to a sales performance attribution analysis system and method based on store retail terminals. The data acquisition module provided by the present invention collects comprehensive data from multiple key data sources to ensure that no important information is missed, and provides a comprehensive and in-depth sales performance attribution analysis for store retail terminals. By accurately quantifying the contribution of customer factors, product factors and store operation factors to sales performance, store managers can more effectively allocate market promotion resources and design personalized marketing strategies based on accurate data, optimize product combinations, adjust pricing strategies and improve display methods to improve product sales efficiency and gross profit contribution. In addition, in terms of store operations, evaluating factors such as promotional activities and employee performance is helpful to reasonably arrange promotion plans and motivate employees, thereby improving the overall operation efficiency of stores.

By implementing product sales measures in advance in a virtual store that mimics a real store, we can predict sales in the real store and aim to expand product sales in the real store. [Solution] The system includes a means for implementing a first sales measure in a virtual store, a means for calculating virtual store sales after the implementation of the first sales measure in the virtual store, a means for determining whether the virtual store sales after the implementation of the first sales measure are greater than a virtual store target value, and if it is determined that they are greater, a means for implementing the first sales measure in a physical store, a means for calculating physical store sales after the implementation of the first sales measure, a means for determining whether the physical store sales after the implementation of the first sales measure are greater than a physical store target value, and if it is determined that they are smaller, a means for implementing a second sales measure in the virtual store.

An object of a system according to an embodiment is to generate an attractive promotion of a restaurant and improve a user's meal experience.SOLUTION: A system according to an embodiment includes a promotion generation unit, a description providing unit, and an experience improvement unit. The promotion generation unit generates an attractive promotion of the restaurant by using the generated AI. The explanation providing unit provides the promotion generated by the promotion generating unit with a rich explanation and beautiful images. The experience enhancer enhances the user's dining experience based on the information provided by the explanation provider.SELECTED DRAWING: Figure 1

The present invention discloses an online marketing coupon and promotion activity data tracking and optimization system, belonging to the technical field of marketing data processing. It includes a data storage module for storing data related to promotion activities; a data collection module for collecting consumption record information of the system; a range setting module for analyzing the data related to promotion activities to obtain a time interval and an activity effect threshold; a promotion analysis module for analyzing newly generated coupon consumption records according to the time interval and the activity effect threshold to obtain an evaluation result of the promotion activity effect; and an optimization warning module for warning users according to the evaluation result to adjust the promotion strategy. By adopting advanced data processing algorithms, the present invention tracks key indicators such as the participation situation and conversion effect of coupons and promotion activities, can accurately evaluate the effects of different promotion strategies, and realizes the real-time collection, efficient storage, intelligent analysis and dynamic optimization of online marketing data.

The invention discloses a store digital display sales interaction method and system of an AI agent. The method comprises the steps of generating drainage characters, drainage pictures and drainage videos of a target product and initial display parameters of the target product according to preset promotion and drainage requirements; displaying drainage characters, drainage pictures and drainage videos of the target product through a holographic display device, and collecting user behavior data, environment data and product interaction data in real time; generating a digital display dynamic adjustment scheme according to the user behavior data, the environment data and the product interaction data, and adjusting the initial display parameters of the target product through the digital display dynamic adjustment scheme to obtain final display parameters; and monitoring interaction feedback data of the user for the target product in real time and carrying out intelligent guide sales promotion. The intelligent and variable display parameters can be generated based on the product characteristics and the product selling point of the target product and the drainage principle, and the display efficiency and the product exposure rate are improved.

The invention discloses a train carriage vending robot intelligent prediction and dynamic verbal skill adjustment system based on multi-dimensional data, and relates to the technical field of intelligent retail and data analysis. The system comprises a user attention recognition module (for recognizing expressions and body movements of passengers), an intelligent prediction and conversion analysis module (for generating a product conversion rate and a preference analysis report in combination with information such as interactive data, purchase behaviors, train numbers, stations, time periods and regional air temperatures), and a dynamic verbal skill adjustment module (for optimizing selling verbal skill based on an analysis result, and adjusting the verbal skill. According to the method, through multi-dimensional data fusion analysis, accurate prediction of product conversion and intelligent optimization of verbal skills are achieved, the selling conversion rate is effectively improved, meanwhile, the comfort degree of user interaction is enhanced, and the method is suitable for automatic selling requirements of specific scenes such as train carriages.

To efficiently acquire the situation of use of a promotion activity using the fragrance of a commodity.SOLUTION: An information processing system has: injection means that injects fragrance corresponding to a predetermined commodity according to a customer's operation; first acquisition means that acquires first data obtained by recording the injection date on which the injection means injects the fragrance and identification information for identifying the commodity corresponding to the injected fragrance; detection means that detects the movement of a customer reaching for the commodity from a picked-up image of a display shelf on which the commodity is displayed; second acquisition means that acquires second data obtained by recording the detection date on which the detection means detects the movement of the customer, and identification information on the commodity reached for by the customer in the movement or position information for specifying the display position of the commodity; and data management means that stores the first data and the second data in a storage and stores pieces of data having a time-series relationship in association with each other.SELECTED DRAWING: Figure 1

The invention belongs to the technical field of power marketing, and particularly discloses an information processing method and system for a power marketing management system. The method comprises the following steps: S1, data acquisition: acquiring electric power data through a sensor; s2, preprocessing data, calculating an average value and a standard deviation, removing abnormal values and filling missing values; s3, feature extraction: calculating a power consumption feature value and a load fluctuation feature value, and dynamically adjusting the acquisition frequency; s4, load prediction: predicting a power load value by using a neural network model; and S5, marketing decision making: making an electricity price, resource allocation and promotion activity strategy according to the predicted value. The system comprises a data acquisition module, a preprocessing module, a feature extraction module, a load prediction module, a marketing decision module, a data storage module and a communication module. The problems that a traditional power load prediction method is low in precision and an existing marketing decision lags behind and is difficult to meet individual requirements are solved. Experiments prove that the method has a good application effect in different scenes, and the efficiency and accuracy of power marketing management are improved.

To save time and effort in creating sales promotion tools and in doing creative check and achieve increased efficiency and automatization.SOLUTION: Provided is a system for creating sales promotion tools, said system including: means for a user to select the type of sales promotion tool and designate a place where a text or an image is located; means for automatically generating the design of the sales promotion tool on the basis of inputted information; means provided with a function to check the generated design for creativity; and means for outputting the generated design.SELECTED DRAWING: Figure 1

The utility model relates to the technical field of sales promotion devices, and discloses a sales promotion device for sales planning, which comprises a mounting frame, a connecting column is fixedly connected to the middle of the upper surface of the mounting frame, a storage cavity is formed in the connecting column, and a first servo motor is fixedly connected to the middle of the bottom surface of the storage cavity. The output end of the first servo motor is fixedly connected with a threaded rod, and a rod body of the threaded rod is sleeved with a threaded sleeve block. When the sales promotion device for sales planning is used, a first servo motor is started to drive a threaded rod to rotate and drive a threaded sleeve block and a limiting rod to adjust the height at the same time, then the overall height can be adjusted, a second servo motor is started to drive a rotating rod to rotate and drive a rotating table to rotate at the same time, and the height of the whole sales promotion device can be adjusted. The displayed articles can be subjected to high-degree circulating reciprocating and angle continuous rotation, so that the products are presented in front of customers in an omnibearing and multi-angle manner, and the probability that the products are concerned is improved.

Self-adhesive scratch-off labels / stickers for primarily mechanical application using a fully automatic labeling module on commercial goods and packaging of all kinds, for advertising and sales promotion purposes. Characterized in that the prefabricated scratch-off labels according to the invention, coming from a rotating carrier roll, can be applied fully automatically to and at various locations on commercial goods and packaging of all kinds using a corresponding electronically controlled and appropriately positioned labeling module. The application can take place both during the completion phase of a product on the line and afterwards.

A system and method for obtaining sales promotions via a text-messaging based interaction. The system comprises a call-to-action link that reduces the number of steps needed to obtain a sales promotion via a website. The call-to-action link triggers a prepopulated text message on a user's mobile device, whereby the user needs to only press send, and receive the sales promotion text message in return. The returned text message may provide the sales promotion in a variety of ways, such as a scannable bar code or QR code, a hypertext or URL link, an alphanumeric text, or other medium send-able via messaging services and usable by business establishments.

The invention discloses a store fresh food commodity ordering algorithm, and belongs to the field of ordering algorithms, and the algorithm comprises the following steps: S1, obtaining historical sales data, raw material sales data, commodity information data and inventory data including in-transit inventory of fresh food commodities sold in each store; s2, generating an intermediate result table required by the algorithm; s3, date information, holiday and festival arrangement and promotion activity information related to sales are acquired; s4, integrating the obtained data; s5, generating a classification sales volume intermediate result table taking the store ID + the classification ID + the date as a unit; s6, if the store commodity participates in the sales promotion activity, adjusting the sales quantity according to the discount to offset the interference of the sales promotion on the sales volume so as to restore the real demand level; and S7, extracting a daily classification sales volume sequence in a past period of time. The beneficial effects are that accurate prediction and optimization of the store fresh food commodity ordering quantity are realized, stockout and unsalable risks are significantly reduced, and the inventory turnover rate and the store operation efficiency are improved.

The system according to this embodiment aims to analyze customers' communication usage data and behavioral patterns to provide optimal pricing plans and promotions. [Solution] The system according to the embodiment comprises a collection unit, an analysis unit, a proposal unit, a provision unit, and an update unit. The collection unit collects customer communication usage data and behavioral patterns. The analysis unit analyzes the data collected by the collection unit. The proposal unit proposes optimal pricing plans and promotions based on the analysis results obtained by the analysis unit. The provision unit provides the content proposed by the proposal unit to the user. The update unit periodically re-analyzes the data based on the content provided by the provision unit and updates the proposals.