A store digital display sales interaction method and system of an AI intelligent agent

Abstract

The application discloses a store digital display sales interaction method and system of an AI intelligent agent, and the method comprises the following steps: generating a target product's flow text, flow pictures and flow videos and the initial display parameters of the target product according to preset sales flow requirements; displaying the target product's flow text, flow pictures and flow videos through a holographic display device and collecting user behavior data, environmental data and product interaction data in real time; generating a digital display dynamic adjustment scheme according to the user behavior data, the environmental data and the product interaction data, adjusting the initial display parameters of the target product through the digital display dynamic adjustment scheme, and obtaining final display parameters; and monitoring the user's interaction feedback data for the target product in real time and intelligently guiding sales. The intelligent variable display parameters can be generated based on the product characteristics and product selling points of the target product and the flow principle, so that the display efficiency and product exposure rate are improved.

Description

Technical Field

[0001] This invention relates to the field of AI technology, and in particular to a digital display and sales interaction method and system for stores using AI intelligent agents. Background Technology

[0002] Currently, with the rapid development of new retail and smart commerce, the scale of the retail industry continues to expand, and competition is becoming increasingly fierce, especially for offline retail. On the one hand, compared with online retail, offline retail is inherently characterized by high costs due to factors such as shop rent. On the other hand, with numerous shops in cities, the services offered by these shops are highly homogenized, making it difficult to stand out. To survive and thrive in this competitive environment, establishing a positive store and brand image for consumers is essential. In this context, the display of goods in shelves not only affects the effective utilization of the shelves but is also a key means of showcasing the store and product image to consumers. Therefore, traditional store display and sales models face multiple technological bottlenecks. Traditional displays rely on fixed shelf layouts and paper signs, which cannot be dynamically adjusted based on real-time customer flow, inventory changes, or user preferences. For example, clothing stores cannot automatically highlight waterproof jackets on rainy days, resulting in low display efficiency. Furthermore, existing digital signage (such as electronic price tags and LCD screens) only supports one-way information display and lacks personalized interactive capabilities. Customers are unable to deeply interact with products through gestures, voice, or AR / VR, resulting in a fragmented experience and reducing the enjoyment and practicality. Summary of the Invention

[0003] To address the aforementioned problems, this invention provides an AI-powered digital store display and sales interaction method and system. This solves the problems mentioned in the background section, where traditional displays rely on fixed shelf layouts and paper signs, failing to dynamically adjust based on real-time customer flow, inventory changes, or user preferences, resulting in low display efficiency. Furthermore, existing digital signs only support one-way information display and lack personalized interactive capabilities. Customers cannot deeply interact with products through gestures, voice, or AR / VR, leading to a fragmented experience and reduced user experience and usability.

[0004] A method for digital store display and sales interaction using an AI-powered agent includes the following steps:

[0005] Generate lead generation text, images, and videos for the target product, as well as initial display parameters for the target product, based on preset sales and lead generation requirements;

[0006] The holographic display device displays promotional text, images, and videos of the target product and collects user behavior data, environmental data, and product interaction data in real time.

[0007] A digital display dynamic adjustment plan is generated based on user behavior data, environmental data, and product interaction data. The initial display parameters of the target product are adjusted using the digital display dynamic adjustment plan to obtain the final display parameters.

[0008] Real-time monitoring of user interaction feedback data for target products and intelligent guidance and promotion.

[0009] Preferably, the step of generating the target product's promotional text, promotional images, promotional videos, and initial display parameters based on preset promotional and lead generation requirements includes:

[0010] Collect product image information, video explanation information, and voice description information of the target product; perform image enhancement preprocessing on the product images; perform noise reduction preprocessing on the product videos; and perform voice enhancement preprocessing on the product description voice.

[0011] The AI ​​model in the background determines the target sales audience, core selling points, promotional strategies, and brand tone of the target product based on the preset sales and lead generation requirements.

[0012] Based on the target audience, core selling points, promotional strategies, and brand tone of the target product, determine the title formula and body structure of the lead-in text and the embedded keywords, the visual formula and design rules of the lead-in images, and the script structure and content design of the lead-in videos.

[0013] Generate lead-generating text based on title formulas, body structure, and embedded keywords; generate lead-generating images based on visual formulas and design rules; and generate lead-generating videos based on script structure and content design.

[0014] Based on the promotional text, images, and videos, determine the display combination and space requirements for the target products, and then determine the initial display parameters for the target products based on the display combination and space requirements.

[0015] Preferably, the step of displaying promotional text, images, and videos of the target product through a holographic display device and collecting user behavior data, environmental data, and product interaction data in real time includes:

[0016] Determine the field of view data of the holographic display device, and adjust the display parameters of the holographic display device according to the field of view data to achieve content rendering and adaptation for the promotional text, promotional images and promotional videos;

[0017] Configure the user's interaction trigger mechanism for the holographic display device, and determine the timing of the user's interaction with the target product through the interaction trigger mechanism;

[0018] Determine multiple interaction metrics and the data collection method for each metric. Based on the interaction timing, collect user operation parameters for each interaction metric and generate product interaction data.

[0019] Data on user behavior and the store environment is collected through a pre-set sensor array and cameras.

[0020] Preferably, the step of generating a dynamic digital display adjustment plan based on user behavior data, environmental data, and product interaction data, and adjusting the initial display parameters of the target product using the dynamic digital display adjustment plan to obtain the final display parameters, includes:

[0021] Determine the personnel flow efficiency of the target product under the initial display parameters based on environmental data, and determine the display conversion rate of the target product under the initial display parameters based on personnel flow efficiency;

[0022] Based on the display conversion rate, determine whether the initial display parameters of the target product meet the traffic requirements. If yes, it is confirmed that no adjustment to the initial display parameters is needed; otherwise, it is confirmed that the initial display parameters need to be adjusted.

[0023] A user profile is generated for each user based on user behavior data and product interaction data. Product preference tags and emotional state tags for each user are obtained based on the user profile.

[0024] The product display strategy priority weight is determined based on each user's product preference tags and emotional state tags, as well as the inventory and sales information of each product.

[0025] The focus of the display adjustment strategy is determined based on the priority weight of the product display strategy, and a digital display dynamic adjustment plan is generated based on the focus of the display adjustment strategy.

[0026] Determine the array adjustment position parameters and array adjustment distance parameters for the target products based on the digital display dynamic adjustment plan;

[0027] The final display parameters for the target product are generated based on the array adjustment position parameters and array adjustment distance parameters.

[0028] Preferably, the real-time monitoring of user interaction feedback data regarding the target product and the intelligent guidance and promotion includes:

[0029] Collect user operation sequence data for the target product and the distribution of click hotspots on the product details page of the target product in the holographic display device;

[0030] The click hotspot distribution and operation sequence data are integrated to generate user interaction feedback data for the target product;

[0031] Based on the interactive feedback data, determine the correlation index of users' purchase decisions for the target product, and based on the correlation index of purchase decisions, determine the intensity index of users' purchase intention for the target product.

[0032] Based on the strong purchase intention index, intelligent and proactive intervention is used to guide sales through human or intelligent robots.

[0033] A digital display and sales interaction system for stores using AI-powered intelligent agents, the system comprising:

[0034] The generation module is used to generate the target product's promotional text, promotional images, promotional videos, and initial display parameters based on preset promotional and lead generation requirements.

[0035] The data acquisition module is used to display the promotional text, images, and videos of the target product through a holographic display device, and to collect user behavior data, environmental data, and product interaction data in real time.

[0036] The adjustment module is used to generate a dynamic digital display adjustment plan based on user behavior data, environmental data, and product interaction data. The initial display parameters of the target product are adjusted through the dynamic digital display adjustment plan to obtain the final display parameters.

[0037] The sales module is used to monitor user interaction feedback data for target products in real time and provide intelligent guidance for sales.

[0038] Preferably, the generation module includes:

[0039] The data acquisition and preprocessing submodule is used to acquire product image information, video explanation information and voice description information of the target product, perform image enhancement preprocessing on the product images, noise reduction preprocessing on the product videos, and voice enhancement preprocessing on the product description voice.

[0040] The first determination submodule is used to determine the target sales audience, core selling points, promotional strategies, and brand tone of the target product based on the preset sales and lead generation requirements through the background AI model;

[0041] The second sub-module is used to determine the title formula and body structure of the lead-in text and the embedded keywords, the visual formula and design rules of the lead-in images, and the script structure and content design of the lead-in videos based on the target sales audience, core selling points, promotional strategies and brand tone of the target product.

[0042] The first generation submodule is used to generate traffic-generating text based on the title formula and body structure of the traffic-generating text and embedded keywords, generate traffic-generating images based on the visual formula and design rules of the traffic-generating images, and generate traffic-generating videos based on the script structure and content design of the traffic-generating videos.

[0043] The third determination submodule is used to determine the display combination and display space requirements of the target products based on the promotional text, promotional images and promotional videos, and to determine the initial display parameters of the target products based on the display combination and display space requirements.

[0044] Preferably, the acquisition module includes:

[0045] The adjustment submodule is used to determine the field of view data of the holographic display device, and adjust the display parameters of the holographic display device according to the field of view data to achieve content rendering and adaptation for the promotional text, promotional images and promotional videos.

[0046] The fourth submodule is used to configure the user's interaction trigger mechanism for the holographic display device, and to determine the timing of the user's interaction with the target product through the interaction trigger mechanism;

[0047] The first data collection submodule is used to determine multiple interaction metrics and the data collection method for each interaction metric. Based on the interaction timing, the module collects the user's operation parameters for each interaction metric and generates product interaction data.

[0048] The second data acquisition submodule is used to collect user behavior data and store environment data through a preset sensor array and camera.

[0049] Preferably, the adjustment module includes:

[0050] The fifth submodule is used to determine the personnel flow efficiency of the target product under the initial display parameters based on environmental data, and to determine the display conversion rate of the target product under the initial display parameters based on the personnel flow efficiency.

[0051] The confirmation submodule is used to determine whether the initial display parameters of the target product meet the traffic requirements based on the display conversion rate. If yes, it confirms that no adjustment is needed to the initial display parameters; otherwise, it confirms that the initial display parameters need to be adjusted.

[0052] The acquisition submodule is used to generate a user profile for each user based on user behavior data and product interaction data, and to obtain product preference tags and emotional state tags for each user based on the user profile.

[0053] The sixth submodule is used to determine the priority weight of product display strategies based on each user's product preference tags and emotional state tags, as well as the inventory and sales information of each product.

[0054] The second generation submodule is used to determine the focus of the display adjustment strategy based on the priority weight of the product display strategy, and generate a digital display dynamic adjustment plan based on the focus of the display adjustment strategy.

[0055] The seventh submodule is used to determine the array adjustment position parameters and array adjustment distance parameters of the target products based on the digital display dynamic adjustment plan;

[0056] The third generation submodule is used to generate the final display parameters of the target product based on the array adjustment position parameters and array adjustment distance parameters.

[0057] Preferably, the sales module includes:

[0058] The third acquisition submodule is used to collect user operation sequence data for the target product and the distribution of click hotspots on the product details page of the target product in the holographic display device.

[0059] The fourth generation submodule is used to integrate the click hotspot distribution and operation sequence data to generate user interaction feedback data for the target product;

[0060] The eighth submodule is used to determine the correlation index of users' purchase decisions for the target product based on interactive feedback data, and to determine the intensity index of users' purchase intention for the target product based on the correlation index of purchase decisions.

[0061] The sales submodule is used to proactively guide sales through human or intelligent robots based on a strong purchase intention index.

[0062] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0063] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0064] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0065] Figure 1 A flowchart illustrating the workflow of a digital store display and sales interaction method for an AI-powered intelligent agent provided by this invention.

[0066] Figure 2 Another flowchart of a store digital display and sales interaction method for an AI intelligent agent provided by the present invention;

[0067] Figure 3 A schematic diagram of the structure of an AI-powered digital display and sales interaction system for stores provided by the present invention;

[0068] Figure 4 This is a schematic diagram of the data acquisition module in a digital store display and sales interaction system for an AI-powered intelligent agent provided by the present invention. Detailed Implementation

[0069] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0070] Currently, with the rapid development of new retail and smart commerce, the scale of the retail industry continues to expand, and competition is becoming increasingly fierce, especially for offline retail. On the one hand, compared with online retail, offline retail is inherently characterized by high costs due to factors such as shop rent. On the other hand, with numerous shops in cities, the services offered by these shops are highly homogenized, making it difficult to stand out. To survive and thrive in this competitive environment, establishing a positive store and brand image for consumers is essential. In this context, the display of goods in shelves not only affects the effective utilization of the shelves but is also a key means of showcasing the store and product image to consumers. Therefore, traditional store display and sales models face multiple technological bottlenecks. Traditional displays rely on fixed shelf layouts and paper signs, which cannot be dynamically adjusted based on real-time customer flow, inventory changes, or user preferences. For example, clothing stores cannot automatically highlight waterproof jackets on rainy days, resulting in low display efficiency. Furthermore, existing digital signage (such as electronic price tags and LCD screens) only supports one-way information display and lacks personalized interactive capabilities. Customers cannot deeply interact with products through gestures, voice, or AR / VR, resulting in a fragmented experience and reduced user enjoyment and usability. To address these issues, this embodiment discloses a digital display and sales interaction method for stores using an AI-powered intelligent agent.

[0071] A method for digital store display and sales interaction using AI-powered agents, such as... Figure 1 As shown, it includes the following steps:

[0072] Step S101: Generate the target product's promotional text, promotional images, promotional videos, and initial display parameters based on the preset promotional and lead generation requirements;

[0073] Step S102: Display the promotional text, promotional images, and promotional videos of the target product through a holographic display device, and collect user behavior data, environmental data, and product interaction data in real time;

[0074] Step S103: Generate a digital display dynamic adjustment plan based on user behavior data, environmental data, and product interaction data. Adjust the initial display parameters of the target product using the digital display dynamic adjustment plan to obtain the final display parameters.

[0075] Step S104: Monitor user interaction feedback data for the target product in real time and provide intelligent guidance and sales promotion.

[0076] In this embodiment, the preset sales and customer acquisition requirements refer to the requirements for product selling points, promotional strategies, and brand tone needed to increase sales volume and attract customer traffic.

[0077] In this embodiment, user behavior data includes, but is not limited to: user dwell time, gaze focus trajectory, body movements, and emotional feedback, etc.

[0078] In this embodiment, environmental data is represented as foot traffic data within the store.

[0079] The working principle of the above technical solution is as follows: Based on preset promotional and lead generation requirements, generate lead generation text, images, and videos for the target product, as well as the initial display parameters of the target product; display the lead generation text, images, and videos of the target product through a holographic display device and collect user behavior data, environmental data, and product interaction data in real time; generate a digital display dynamic adjustment plan based on the user behavior data, environmental data, and product interaction data; adjust the initial display parameters of the target product through the digital display dynamic adjustment plan to obtain the final display parameters; monitor user interaction feedback data on the target product in real time and provide intelligent guidance for promotion.

[0080] The beneficial effects of the above technical solution are as follows: By generating initial display parameters for the target product, intelligent and variable display parameters can be generated based on the product characteristics, selling points, and traffic-driving principles, improving display efficiency and product exposure. Furthermore, by intelligently adjusting display parameters based on user behavior data, pedestrian flow data, and product interaction data, the exposure of the target product can be further improved according to pedestrian flow distribution, enhancing stability. Moreover, by generating traffic-driving images, videos, and other promotional materials for holographic display and user interaction, multi-dimensional deep interaction between users and products can be achieved, improving user experience and usability. This solves the problems mentioned in existing technologies, such as traditional displays relying on fixed shelf layouts and paper signs, which cannot be dynamically adjusted according to real-time customer flow, inventory changes, or user preferences, resulting in low display efficiency. Additionally, existing digital signage only supports one-way information display and lacks personalized interactive capabilities. Customers cannot deeply interact with products through gestures, voice, or AR / VR, leading to a fragmented experience and reduced user experience and usability.

[0081] In this embodiment, after generating the target product's promotional text, promotional image, and promotional video, the method further includes:

[0082] Obtain the content attribute tags of the promotional text, the image factor attribute tags of the promotional image, and the video stream attribute tags of the promotional video;

[0083] Determine the timeliness popularity value of each content attribute tag, image factor attribute tag, and video stream attribute tag, and determine the marketing exposure traffic feedback of each lead generation text, lead generation image, and lead generation video based on the timeliness popularity value;

[0084] Determine the respective traffic generation metrics sequence for traffic-driving text, images, and videos based on marketing exposure and traffic feedback;

[0085] Based on marketing exposure traffic feedback, determine the traffic fluctuation parameters of the traffic acquisition indicator sequence, and select high traffic sequence factors based on the traffic fluctuation parameters;

[0086] Obtain the identification elements corresponding to high-traffic sequence factors, determine the user preference parameters of the identification elements, and determine the user preference attention weights of the traffic-driving text, traffic-driving images, and traffic-driving videos based on the user preference parameters;

[0087] Based on the user preference attention weight, the product's in-depth feature description is determined, and based on the product's in-depth feature description, the modification vectors for the traffic-driving text, traffic-driving images, and traffic-driving videos, as well as marketing environment factors, are determined.

[0088] Based on the modification vector, a modification scheme is generated. The promotional text, promotional image, and promotional video are then adaptively modified according to the modification scheme to obtain the final promotional text, final promotional image, and final promotional video.

[0089] Based on marketing environment factors, determine the planning and placement information for the final lead generation text, the final lead generation image, and the timing and visual angle of the final lead generation video.

[0090] The beneficial effects of the above technical solution are as follows: by estimating traffic feedback for lead generation text, images, and videos, and then adjusting the content of text, images, and videos according to user preference weights, high-quality normal exposure traffic feedback can be guaranteed, thereby achieving the best lead generation effect and improving practicality and stability. Furthermore, by planning the angles of lead generation text, images, and videos based on marketing environment factors, the best exposure and visual effects can be guaranteed, thereby improving the lead generation effect on the target product.

[0091] In one embodiment, generating the target product's lead generation text, images, and videos, as well as the target product's initial display parameters, according to preset sales and lead generation requirements, includes:

[0092] Collect product image information, video explanation information, and voice description information of the target product; perform image enhancement preprocessing on the product images; perform noise reduction preprocessing on the product videos; and perform voice enhancement preprocessing on the product description voice.

[0093] The AI ​​model in the background determines the target sales audience, core selling points, promotional strategies, and brand tone of the target product based on the preset sales and lead generation requirements.

[0094] Based on the target audience, core selling points, promotional strategies, and brand tone of the target product, determine the title formula and body structure of the lead-in text and the embedded keywords, the visual formula and design rules of the lead-in images, and the script structure and content design of the lead-in videos.

[0095] Generate lead-generating text based on title formulas, body structure, and embedded keywords; generate lead-generating images based on visual formulas and design rules; and generate lead-generating videos based on script structure and content design.

[0096] Based on the promotional text, images, and videos, determine the display combination and space requirements for the target products, and then determine the initial display parameters for the target products based on the display combination and space requirements.

[0097] In this embodiment, a title formula is generated based on the product's functions, the problems it solves, and the corresponding actions: Taking an eye-protecting desk lamp as an example, the title formula could be: "Must-see for night owls! XX eye-protecting desk lamp | Reduces blue light + intelligent dimming | Order today and get 200 yuan off instantly";

[0098] In this embodiment, the referral image includes a product title, product image, price tag, and feature description tag, etc.

[0099] The beneficial effects of the above technical solution are as follows: by determining the target audience, core selling points, promotional strategies, and brand tone of the target product, a reference condition can be laid for the generation of subsequent lead generation text, images, and videos, thereby ensuring the richness of the content and its attractiveness to consumers, and improving practicality. Furthermore, by determining the display space requirements and display combinations, the target product can be highlighted more intuitively through product comparison or product auxiliary mapping, thereby making consumers invest more interest and energy in the target product, further improving practicality.

[0100] In one embodiment, such as Figure 2 As shown, the step of displaying promotional text, images, and videos of the target product through a holographic display device and collecting user behavior data, environmental data, and product interaction data in real time includes:

[0101] Step S201: Determine the field of view data of the holographic display device, and adjust the display parameters of the holographic display device according to the field of view data to achieve content rendering and adaptation for the promotional text, promotional images and promotional videos;

[0102] Step S202: Configure the user's interaction triggering mechanism for the holographic display device, and determine the timing of the user's interaction with the target product through the interaction triggering mechanism;

[0103] Step S203: Determine multiple interaction metrics and the collection method for each interaction metric. Based on the interaction timing, collect the user's operation parameters for each interaction metric and generate product interaction data.

[0104] Step S204: Collect user behavior data and store environment data in the store through a preset sensor array and camera.

[0105] The beneficial effects of the above technical solution are: by determining the timing of interaction, user interaction data on the product can be collected in the first instance, ensuring the comprehensiveness and integrity of the data.

[0106] In one embodiment, the step of generating a dynamic digital display adjustment plan based on user behavior data, environmental data, and product interaction data, and adjusting the initial display parameters of the target product using the dynamic digital display adjustment plan to obtain the final display parameters includes:

[0107] Determine the personnel flow efficiency of the target product under the initial display parameters based on environmental data, and determine the display conversion rate of the target product under the initial display parameters based on personnel flow efficiency;

[0108] Based on the display conversion rate, determine whether the initial display parameters of the target product meet the traffic requirements. If yes, it is confirmed that no adjustment to the initial display parameters is needed; otherwise, it is confirmed that the initial display parameters need to be adjusted.

[0109] A user profile is generated for each user based on user behavior data and product interaction data. Product preference tags and emotional state tags for each user are obtained based on the user profile.

[0110] The product display strategy priority weight is determined based on each user's product preference tags and emotional state tags, as well as the inventory and sales information of each product.

[0111] The focus of the display adjustment strategy is determined based on the priority weight of the product display strategy, and a digital display dynamic adjustment plan is generated based on the focus of the display adjustment strategy.

[0112] Determine the array adjustment position parameters and array adjustment distance parameters for the target products based on the digital display dynamic adjustment plan;

[0113] The final display parameters for the target product are generated based on the array adjustment position parameters and array adjustment distance parameters.

[0114] The beneficial effects of the above technical solution are as follows: by determining the user profile, the distribution of the people who like each product can be evaluated, and then the array adjustment parameters for each product can be determined based on the products that users are interested in, so as to determine the products to be emphasized and then adjust them to be placed in a display array with a large field of view and obvious visibility, thereby further improving the exposure of the products.

[0115] In one embodiment, the real-time monitoring of user interaction feedback data regarding the target product and the intelligent guidance and promotion include:

[0116] Collect user operation sequence data for the target product and the distribution of click hotspots on the product details page of the target product in the holographic display device;

[0117] The click hotspot distribution and operation sequence data are integrated to generate user interaction feedback data for the target product;

[0118] Based on the interactive feedback data, determine the correlation index of users' purchase decisions for the target product, and based on the correlation index of purchase decisions, determine the intensity index of users' purchase intention for the target product.

[0119] Based on the strong purchase intention index, intelligent and proactive intervention is used to guide sales through human or intelligent robots.

[0120] The beneficial effects of the above technical solution are as follows: by determining the user's purchase intention index for the target product, the user's liking for the target product can be accurately assessed based on the user's interaction behavior, and then intelligent guidance and promotion can be carried out. This not only improves the user's pre-purchase experience, but also enriches the user's product usage experience, further improving practicality.

[0121] In one embodiment, this embodiment also discloses an AI-powered digital display and sales interaction system for stores, such as... Figure 3 As shown, the system includes:

[0122] The generation module 301 is used to generate the target product's promotional text, promotional images, promotional videos, and initial display parameters of the target product according to the preset promotional and traffic-driving requirements.

[0123] The data acquisition module 302 is used to display the promotional text, promotional images and promotional videos of the target product through a holographic display device and to collect user behavior data, environmental data and product interaction data in real time.

[0124] The adjustment module 303 is used to generate a dynamic digital display adjustment plan based on user behavior data, environmental data, and product interaction data. The initial display parameters of the target product are adjusted through the dynamic digital display adjustment plan to obtain the final display parameters.

[0125] The sales module 304 is used to monitor user interaction feedback data on target products in real time and provide intelligent guidance for sales.

[0126] The working principle and beneficial effects of the above technical solution have been explained in the method embodiments, and will not be repeated here.

[0127] In one embodiment, the generation module includes:

[0128] The data acquisition and preprocessing submodule is used to acquire product image information, video explanation information and voice description information of the target product, perform image enhancement preprocessing on the product images, noise reduction preprocessing on the product videos, and voice enhancement preprocessing on the product description voice.

[0129] The first determination submodule is used to determine the target sales audience, core selling points, promotional strategies, and brand tone of the target product based on the preset sales and lead generation requirements through the background AI model;

[0130] The second sub-module is used to determine the title formula and body structure of the lead-in text and the embedded keywords, the visual formula and design rules of the lead-in images, and the script structure and content design of the lead-in videos based on the target sales audience, core selling points, promotional strategies and brand tone of the target product.

[0131] The first generation submodule is used to generate traffic-generating text based on the title formula and body structure of the traffic-generating text and embedded keywords, generate traffic-generating images based on the visual formula and design rules of the traffic-generating images, and generate traffic-generating videos based on the script structure and content design of the traffic-generating videos.

[0132] The third determination submodule is used to determine the display combination and display space requirements of the target products based on the promotional text, promotional images and promotional videos, and to determine the initial display parameters of the target products based on the display combination and display space requirements.

[0133] In one embodiment, such as Figure 4 As shown, the acquisition module 302 includes:

[0134] The adjustment submodule 3021 is used to determine the field of view data of the holographic display device, and adjust the display parameters of the holographic display device according to the field of view data to achieve content rendering and adaptation for the promotional text, promotional images and promotional videos;

[0135] The fourth determining submodule 3022 is used to configure the user's interaction triggering mechanism for the holographic display device, and to determine the timing of the user's interaction with the target product through the interaction triggering mechanism;

[0136] The first data collection submodule 3023 is used to determine multiple interactive indicators and the data collection method for each interactive indicator. Based on the interaction timing, the submodule collects the user's operation parameters for each interactive indicator and generates product interaction data.

[0137] The second data acquisition submodule 3024 is used to collect user behavior data and store environment data through a preset sensor array and camera.

[0138] In one embodiment, the adjustment module includes:

[0139] The fifth submodule is used to determine the personnel flow efficiency of the target product under the initial display parameters based on environmental data, and to determine the display conversion rate of the target product under the initial display parameters based on the personnel flow efficiency.

[0140] The confirmation submodule is used to determine whether the initial display parameters of the target product meet the traffic requirements based on the display conversion rate. If yes, it confirms that no adjustment is needed to the initial display parameters; otherwise, it confirms that the initial display parameters need to be adjusted.

[0141] The acquisition submodule is used to generate a user profile for each user based on user behavior data and product interaction data, and to obtain product preference tags and emotional state tags for each user based on the user profile.

[0142] The sixth submodule is used to determine the priority weight of product display strategies based on each user's product preference tags and emotional state tags, as well as the inventory and sales information of each product.

[0143] The second generation submodule is used to determine the focus of the display adjustment strategy based on the priority weight of the product display strategy, and generate a digital display dynamic adjustment plan based on the focus of the display adjustment strategy.

[0144] The seventh submodule is used to determine the array adjustment position parameters and array adjustment distance parameters of the target products based on the digital display dynamic adjustment plan;

[0145] The third generation submodule is used to generate the final display parameters of the target product based on the array adjustment position parameters and array adjustment distance parameters.

[0146] In one embodiment, the sales module includes:

[0147] The third acquisition submodule is used to collect user operation sequence data for the target product and the distribution of click hotspots on the product details page of the target product in the holographic display device.

[0148] The fourth generation submodule is used to integrate the click hotspot distribution and operation sequence data to generate user interaction feedback data for the target product;

[0149] The eighth submodule is used to determine the correlation index of users' purchase decisions for the target product based on interactive feedback data, and to determine the intensity index of users' purchase intention for the target product based on the correlation index of purchase decisions.

[0150] The sales submodule is used to proactively guide sales through human or intelligent robots based on a strong purchase intention index.

[0151] Those skilled in the art should understand that the terms "first" and "second" in this invention simply refer to different application stages.

[0152] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0153] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for AI agent's store digital display sales interaction, characterized in that, The method comprises the following steps: According to the preset sales flow requirements, generate the flow text, flow picture and flow video of the target product, and the initial display parameters of the target product; Display the flow text, flow picture and flow video of the target product through the holographic display device, and collect user behavior data, environmental data and product interaction data in real time; Generate a digital display dynamic adjustment scheme according to the user behavior data, environmental data and product interaction data, adjust the initial display parameters of the target product through the digital display dynamic adjustment scheme, and obtain the final display parameters; Real-time monitoring of user interaction feedback data and intelligent guidance sales of the target product; The method comprises the following steps: Collect product picture information, video explanation information and voice description information of the target product, perform image enhancement preprocessing on the product picture, denoising preprocessing on the product video, and voice enhancement preprocessing on the product description voice; Determine the target product's target sales population, core selling points, promotion strategies and brand tone through the background AI model according to the preset sales flow requirements; Determine the title formula and text structure of the flow text, and implant key words, the visual formula and design rules of the flow picture, and the script structure and content design of the flow video according to the target product's target sales population, core selling points, promotion strategies and brand tone; Generate the flow text based on the title formula and text structure of the flow text and implant key words, generate the flow picture based on the visual formula and design rules of the flow picture, and generate the flow video based on the script structure and content design of the flow video; Determine the display combination and display space requirement of the target product according to the flow text and flow picture and flow video, and determine the initial display parameters of the target product according to the display combination and display space requirement; The method comprises the following steps: Determine the personnel flow efficiency of the target product under the initial display parameters according to the environmental data, and determine the display conversion rate of the target product under the initial display parameters according to the personnel flow efficiency; Determine whether the initial display parameters of the target product meet the traffic demand based on the display conversion rate, if yes, confirm that the initial display parameters do not need to be adjusted, if not, confirm that the initial display parameters need to be adjusted; Generate a user portrait of each user according to the user behavior data and product interaction data, and obtain the product preference label and emotional state label of each user according to the user portrait; Determine the product display strategy priority weight according to the product preference label and emotional state label of each user and the inventory and sales information of each product; Determine the display adjustment strategy focus object according to the product display strategy priority weight, and generate a digital display dynamic adjustment scheme according to the display adjustment strategy focus object; Determine the array adjustment position parameters and array adjustment distance parameters of the target product according to the digital display dynamic adjustment scheme; The final display parameters of the target product are generated according to the array adjustment position parameters and the array adjustment distance parameters.

2. The AI agent's method for digital in-store display sales interaction according to claim 1, wherein, The flow text, the flow picture and the flow video of the target product are displayed by the holographic display device, and user behavior data, environmental data and product interaction data are collected in real time, and the method comprises the following steps: The field of view angle data of the holographic display device is determined, and the display parameters of the holographic display device are adjusted according to the field of view angle data to realize the content rendering and adaptation of the flow text, the flow picture and the flow video; The interaction trigger mechanism of the user for the holographic display device is configured, and the interaction opportunity of the user and the target product is determined through the interaction trigger mechanism; A plurality of interaction indexes and the collection mode of each interaction index are determined, and the operation parameters of the user for each interaction index are collected based on the interaction opportunity through the collection mode to generate product interaction data; The behavior data of the user in the store and the store environmental data are collected through the preset sensor array and the camera.

3. The AI agent's method for digital in-store display sales interaction according to claim 1, wherein, The interaction feedback data of the user for the target product is monitored in real time, and intelligent guidance and sales are carried out, comprising the following steps: The operation sequence data of the user for the target product and the click hot area distribution of the user for the product detail page about the target product in the holographic display device are collected; The click hot area distribution and the operation sequence data are integrated to generate the interaction feedback data of the user for the target product; The purchase decision correlation index of the user for the target product is determined according to the interaction feedback data, and the purchase willingness intensity index of the user for the target product is determined according to the purchase decision correlation index; Based on the purchase willingness intensity index, artificial or intelligent robots are used for intelligent active intervention and guidance and sales.

4. A store digital display sales interaction system of an AI agent, characterized in that, The system comprises: A generation module for generating the flow text, the flow picture and the flow video of the target product and the initial display parameters of the target product according to the preset sales flow requirements; A collection module for displaying the flow text, the flow picture and the flow video of the target product by the holographic display device and collecting user behavior data, environmental data and product interaction data in real time; An adjustment module for generating a digital display dynamic adjustment scheme according to the user behavior data, the environmental data and the product interaction data, adjusting the initial display parameters of the target product through the digital display dynamic adjustment scheme, and obtaining the final display parameters; A sales module for monitoring the interaction feedback data of the user for the target product in real time and carrying out intelligent guidance and sales; The generation module comprises: A data collection and preprocessing submodule for collecting product picture information, video explanation information and voice description information of the target product, pre-processing the product picture through image enhancement, pre-processing the product video through noise reduction, and pre-processing the product description voice through voice enhancement; A first determination submodule for determining the target product sales population target, the core selling point, the promotion strategy and the brand tone according to the preset sales flow requirements through a background AI model; A second determination submodule for determining the title formula and the text structure and the implanted key words of the flow text, the visual formula and the design rules of the flow picture, and the script structure and the content design of the flow video according to the target product sales population target, the core selling point, the promotion strategy and the brand tone. The first generation submodule is configured to generate the lead text based on a title formula and a text structure of the lead text and implanted keywords, generate the lead picture based on a visual formula and design rules of the lead picture, and generate the lead video based on a script structure and content design of the lead video. The third determination submodule is configured to determine a display combination and a display space requirement of the target product according to the lead text, the lead picture and the lead video, and determine initial display parameters of the target product according to the display combination and the display space requirement. The adjustment module comprises: The fifth determination submodule is configured to determine a personnel flow efficiency of the target product under the initial display parameters according to the environmental data, and determine a display conversion rate of the target product under the initial display parameters according to the personnel flow efficiency. The confirmation submodule is configured to determine whether the initial display parameters of the target product meet the traffic demand based on the display conversion rate, confirm that the initial display parameters do not need to be adjusted if yes, and confirm that the initial display parameters need to be adjusted if no. The acquisition submodule is configured to generate a user portrait of each user according to the user behavior data and the product interaction data, and acquire a product preference label and an emotional state label of each user according to the user portrait. The sixth determination submodule is configured to determine a product display strategy priority weight according to the product preference label and the emotional state label of each user and inventory and sales information of each product. The second generation submodule is configured to determine a display adjustment strategy focus object according to the product display strategy priority weight, and generate a digital display dynamic adjustment scheme according to the display adjustment strategy focus object. The seventh determination submodule is configured to determine an array adjustment position parameter and an array adjustment distance parameter of the target product according to the digital display dynamic adjustment scheme. The third generation submodule is configured to generate final display parameters of the target product according to the array adjustment position parameter and the array adjustment distance parameter.

5. The AI agent's store digital display sales interaction system of claim 4, wherein, The acquisition module comprises: The adjustment submodule is configured to determine field of view angle data of the holographic display device, and adjust display parameters of the holographic display device according to the field of view angle data to realize content rendering and adaptation of the lead text, the lead picture and the lead video. The fourth determination submodule is configured to configure an interactive trigger mechanism of the holographic display device by a user, and determine an interaction opportunity of the user and the target product through the interactive trigger mechanism. The first acquisition submodule is configured to determine a plurality of interaction indexes and an acquisition manner of each interaction index, and acquire operation parameters of the user for each interaction index based on the interaction opportunity through the acquisition manner and generate product interaction data. The second acquisition submodule is configured to acquire behavior data of the user in the store and store environment data through a preset sensor array and a camera.

6. The AI agent's store digital display sales interaction system of claim 4, wherein, The promotion module comprises: The third acquisition submodule is configured to acquire operation sequence data of the user for the target product and a click hot area distribution of the user for a product detail page about the target product in the holographic display device. The fourth generation submodule is configured to integrate the click hot area distribution and the operation sequence data to generate interaction feedback data of the user for the target product. an eighth determining sub-module, configured to determine a purchase decision relevance index of the user for the target product according to the interaction feedback data, and determine a purchase willingness intensity index of the user for the target product according to the purchase decision relevance index; a promotion sub-module, configured to promote the target product by manual or intelligent robot intervention and guidance based on the purchase willingness intensity index.

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