Store customer acquisition shopping guide method based on customer behavior analysis

Abstract

The invention relates to the technical field of visual inspection, provides a store customer acquisition shopping guide method based on customer behavior analysis, and aims to screen out potential customers interested in commodities by capturing customer behavior images in real time. The method comprises the steps of customer behavior capturing, preliminary analysis, deep analysis, customer entering guiding, data collection and optimization and the like. The advertisement display strategy is dynamically adjusted by accurately judging the interest points of the customers, and the customer obtaining rate and the transaction rate are increased. And meanwhile, the customer is guided to the shopping guide, and customer information and commodity interest points are pushed, so that the shopping guide can provide personalized services conveniently. The problem that an existing advertisement playing system lacks in deep analysis of customer behaviors is effectively solved, and the shopping experience of customers and the customer obtaining rate of stores are improved.

Description

Technical Field

[0001] The present invention relates to the field of visual detection technology, and in particular to a store customer acquisition and shopping guide method based on customer behavior analysis. Background Art

[0002] Large electronic display screens are often installed in prominent locations such as store windows, doorways and streets to play product advertisements in order to attract customers' attention and promote store customer acquisition and shopping. Currently, this customer acquisition and shopping method has a lot of room for improvement in terms of advertising effectiveness, customer experience and customer acquisition rate.

[0003] First, the advertising playback system of most stores adopts a mode of looping playback of several products. Although this playback method is simple and direct, it has obvious disadvantages. When a customer passes by a store and becomes interested in a certain product, due to the characteristics of looping advertising, the customer may not be able to get a deep understanding of the product at the first time. The advertisement often flashes by, causing the product information that the customer is interested in to be quickly switched, thus missing out on potential sales opportunities and causing the loss of possible transactions.

[0004] Secondly, the current advertising system lacks in-depth analysis of customer behavior. When customers are browsing product advertisements, if they are particularly interested in a product, they will usually slow down or stop to watch. However, existing advertising systems are often unable to capture and analyze these customer behaviors in real time, and thus cannot accurately determine which products customers are really interested in. This may result in stores being unable to respond to customer needs in a timely manner, wasting opportunities to acquire customers.

[0005] In addition, even if customers have a strong desire to buy a product and want to enter the store to experience it, the current advertising system does not provide an effective guidance mechanism. Customers may feel confused or dissatisfied because they do not understand the layout of the products in the store or the shopping guide cannot accurately grasp the customer's interests, and may give up their purchase plans, resulting in the loss of customers.

[0006] Therefore, it is necessary to develop a store customer acquisition and shopping guide method based on customer behavior analysis to accurately analyze customer behavior, dynamically adjust advertising display strategies, and improve customer experience and transaction rates through effective guidance mechanisms. Summary of the invention

[0007] In order to solve the problems existing in the background technology, the present invention provides a store customer acquisition and shopping guide method based on customer behavior analysis, which comprises the following steps:

[0008] S1. Customer behavior capture:

[0009] S11. Using electronic equipment to display goods in a loop;

[0010] S12, collecting behavioral images of customers passing through the electronic device in real time;

[0011] S2. Preliminary analysis of customer behavior:

[0012] S21. Analyze factor A, including: determine whether the customer slows down;

[0013] S22. Analyze factor B, including: whether the customer looks at the electronic device when passing by it;

[0014] S3. Confirm the analysis results and switch the display:

[0015] S31. Based on the analysis results of factor A and factor B, if the results are both "yes", it is considered that the customer is interested in the currently displayed product;

[0016] S32, the electronic device switches to display the two products, products C1 and C2, displayed when the customer's gaze is directed to the electronic device, to determine the product information of interest to the customer;

[0017] S4. In-depth analysis of customer behavior:

[0018] S41, analyzing customer eye behavior to determine which product the customer is looking at;

[0019] S42, when the customer's eyes are directed to product C1, product C1 is displayed in full screen; if the customer's eyes are directed to product C2, product C2 is displayed in full screen;

[0020] S5. Guide customers into the store:

[0021] S51, lighting up the LED light strip leading to the product display area to form a guide path to guide customers;

[0022] S52, identifying the basic information of the customer's appearance, and pushing it to the shopping guide together with the information of the products that the customer is interested in. The shopping guide connects with the customer based on the pushed information and provides personalized services;

[0023] S6. Data collection and optimization:

[0024] Collect statistical data after the transaction is completed, analyze it based on the collected data, and optimize the advertising display strategy.

[0025] In a preferred solution, the specific process of step S21 includes:

[0026] The customer's movement trajectory is captured in real time through AI cameras, and analysis is performed to determine whether the customer has obvious deceleration behavior when passing by electronic device displays. The deceleration behavior is judged based on a preset speed threshold. When the customer's speed is lower than 70% of the normal walking speed, it is determined that the customer is slowing down.

[0027] In the preferred solution, the specific process of step S41 is as follows:

[0028] S411, performing grayscale, denoising, and image enhancement preprocessing on the captured customer facial image;

[0029] S412, locating a face region in the preprocessed image;

[0030] S413, within the detected face region, further identifying and locating the eye region by extracting eye contours and locating eye key points, wherein the eye key points include eye corners and pupil centers; this generally includes:

[0031] S414, tracking the up and down movement trajectory of the eyelids in real time in the located eye area;

[0032] S415. Determine which product the customer's gaze is directed to based on the result of the eye movement analysis.

[0033] In the preferred solution, the specific processing process of step S415 is as follows:

[0034] A reference template is set, wherein the reference template sets an eyelid threshold line, the position of the eyelid is tracked in real time, and the eye area image is placed in the reference template. When the upper eyelid is above the threshold line, it is determined that the customer is interested in product C1; when the upper eyelid is below the threshold line, it is determined that the customer is interested in product C2.

[0035] In a preferred solution, in S52, the basic information of the customer's appearance includes gender, estimated age, and clothing color.

[0036] In a preferred solution, the specific process of step S6 includes:

[0037] S61. Data collection and collation:

[0038] S611. Collect and record all transaction data that are guided and ultimately completed through the customer behavior analysis system, including but not limited to the duration of advertisements, volume of advertisements, duration of customer viewing, and duration of introduction by shopping guides;

[0039] S612, sorting the collected data and removing invalid or abnormal data points;

[0040] S62. Data analysis:

[0041] Analyze the impact of various control parameters on the transaction rate and generate statistical graphs. The control parameters include the duration of advertisement playback, the volume of the advertisement, the viewing time of customers, the duration of the shopping guide's introduction, and the introduction method of the shopping guide. The statistical graph contains multiple curves, each of which represents the relationship between a parameter or a combination of parameters and the transaction rate.

[0042] S63, optimal parameter settings:

[0043] By observing the shape and peak position of the curve in the statistical chart, find the highest point or optimal range of the transaction rate corresponding to each parameter, and identify which parameter setting range or parameter combination setting range is most conducive to improving the transaction rate; adjust and optimize the control parameters based on the optimal parameter settings obtained through analysis.

[0044] The preferred solution also includes the following steps: repeating steps S1-S6, continuously collecting and analyzing data, adjusting parameter settings, and evaluating adjustment effects.

[0045] In a preferred solution, the electronic device is a host and a large electronic display screen.

[0046] The beneficial effects achieved by the present invention are:

[0047] First, the present invention provides personalized product display and guidance services by accurately analyzing customer behavior, so that customers can have a better experience during the shopping process. By capturing customer interests in real time, dynamically adjusting advertising display strategies, and guiding customers into the store, the store's customer acquisition rate and transaction rate can be effectively improved. Through data collection and analysis, the details of advertising placement, such as playback duration, volume, etc., are continuously optimized to maximize the effect of advertising placement. By pushing customer information and information about products of interest, shopping guides can accurately connect with customers and improve work efficiency and transaction rates.

[0048] Second, the present invention accurately captures the initial behavior of customers in front of the store by collecting images of customer behavior passing through electronic devices in real time, providing basic data for subsequent analysis. By using AI cameras to capture the customer's movement trajectory in real time and analyze whether the customer slows down, it is helpful to preliminarily determine whether the customer is interested in the product. Analyze whether the customer's eyes are directed to the electronic device to further confirm the customer's attention to the displayed products and improve the accuracy of the analysis. Based on the preliminary analysis results, switch to display products that customers may be interested in, improve the pertinence and effectiveness of product display, and reduce the situation where customers miss products of interest due to rapid switching of advertisements.

[0049] Third, the present invention uses eye behavior analysis to accurately locate the direction of the customer's gaze and ensure the accuracy of the analysis. Based on the results of the eye analysis, the products that the customer is interested in are displayed in full screen, providing a more personalized display experience and enhancing the customer's desire to buy. By lighting up the LED light strip to form a guide path, customers are guided to the product display area, which improves the customer's store experience and reduces the situation where customers give up buying due to lack of understanding of the store layout. The customer's basic appearance information and information about the products of interest are pushed to the shopping guide, so that the shopping guide can accurately connect with the customer, provide personalized services, and improve the transaction rate.

[0050] Fourth, the present invention collects and organizes transaction data, removes invalid or abnormal data points, and ensures the accuracy of the analysis results. The impact of each control parameter on the transaction rate is analyzed, and a statistical chart is generated to help understand the relationship between each parameter and the transaction rate. According to the analysis results, the control parameters such as the duration of the advertisement and the volume of the advertisement are adjusted and optimized, so as to realize the dynamic optimization of the advertisement delivery strategy and improve the advertisement effect and transaction rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a schematic diagram of the state of the electronic device displaying the goods C1 and C2;

[0052] Figure 2 It is a status diagram for analyzing customer eye behavior. DETAILED DESCRIPTION

[0053] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. In addition, the forms of the various structures recorded in the following embodiments are merely illustrative, and the present invention is not limited to the various structures recorded in the following embodiments. All other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0054] The present invention provides a store customer acquisition and shopping guide method based on customer behavior analysis, comprising the following specific implementation steps:

[0055] S1. Customer behavior capture:

[0056] S11: Use the host and the electronic display screen to display goods in a loop. The electronic display screen is installed in a conspicuous position such as a shop window, door head or street side.

[0057] S12: AI cameras collect real-time images of customer behavior as they pass through electronic devices. The cameras are high-definition and can accurately capture customer movements and facial expressions.

[0058] S2. Preliminary analysis of customer behavior:

[0059] S21: Analyze whether the customer slows down while walking. The customer's movement trajectory is captured in real time by an AI camera, and whether the customer slows down is determined based on a preset speed threshold (such as 70% of the normal walking speed).

[0060] S22: Analyze whether the customer turns his head to look at the electronic display screen. When the customer looks at the electronic device, it is determined that the customer is interested in the displayed content.

[0061] S3. Confirm the analysis results and switch the display:

[0062] S31: If the customer satisfies both conditions of slowing down and watching the electronic device, it is considered that the customer is interested in the currently displayed product.

[0063] S32: The electronic device then switches to display the two products (product C1 and product C2) that the customer is looking at, so as to further confirm the customer's specific interest point. At this time, the large screen advertisement switches to product C1 and product C2, as shown in the upper and lower Figure 1 As shown, because there is a time difference in the previous loop playback, it is not certain which specific product the customer is interested in. Therefore, when analyzing the second customer behavior, the product C2 at that moment and the previous product C1 are combined to ensure to the greatest extent possible that the products released cover the products that the customer is interested in.

[0064] S4. In-depth analysis of customer behavior:

[0065] S41: Analyze the customer's eye behavior. First, the captured customer's facial image is pre-processed by grayscale, denoising, and image enhancement; then, the face area is located, and the eye area is further identified by extracting the eye contour and eye key points (such as the corner of the eye, the center of the pupil); finally, the up and down movement trajectory of the eyelid is tracked in real time.

[0066] S42: Based on the eye movement analysis results, determine which product the customer is looking at. The specific method is to set a reference template, which includes an eyelid threshold line. Figure 2 As shown, when the upper eyelid is above the threshold line, it is determined that the customer is interested in product C1; when the upper eyelid is below the threshold line, it is determined that the customer is interested in product C2. Then, the products that the customer is interested in are displayed in full screen.

[0067] S5. Guide customers into the store:

[0068] S51: Light up the LED light strip leading to the merchandise display area to form a clear guiding path to guide customers to the merchandise display area in the store.

[0069] S52: The customer's basic appearance information (including gender, estimated age, clothing color, etc.) is identified through the AI ​​camera, and this information is pushed to the shopping guide's terminal device together with the product information that the customer is interested in. The shopping guide accurately connects with the customer based on the received information and provides personalized services.

[0070] S6. Data collection and optimization:

[0071] S61: Data collection and organization. Collect and record all transaction data that are guided by the customer behavior analysis system and ultimately concluded, including but not limited to the duration of advertisements, volume, customer viewing time, shopping guide introduction time, etc. Organize the collected data and remove invalid or abnormal data points.

[0072] S62: Data analysis. Analyze the impact of various control parameters (such as advertising playing time, playing volume, customer viewing time, shopping guide introduction time, shopping guide introduction method) on the transaction rate, and generate a statistical chart. The statistical chart contains multiple curves, each of which represents the relationship between a parameter or parameter combination and the transaction rate.

[0073] S63: Optimal parameter setting. By observing the shape and peak position of the curve in the statistical graph, find the highest point or optimal range of the transaction rate corresponding to each parameter. Adjust and optimize the control parameters according to the analysis results to improve the advertising effect.

[0074] Repeat: Repeat steps S1 to S6 to continuously collect and analyze data, and adjust parameter settings based on the analysis results to evaluate and optimize the overall performance of the system.

[0075] The present invention analyzes customer behavior, provides personalized product display and guidance services, and improves customer shopping experience. Dynamically adjusts advertising display strategies to improve store customer acquisition and transaction rates. Through data collection and analysis, optimizes advertising details to maximize advertising effects. Customer information and information about products of interest are pushed to shopping guides, and accurate capture and analysis of customer behavior are achieved, effectively improving the store's customer acquisition capabilities and sales performance.

[0076] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for acquiring and guiding customers in stores based on customer behavior analysis, characterized in that: It includes the following steps: S1. Customer behavior capture: S11. Utilize electronic equipment to display goods in a circular manner; S12, collecting behavioral images of customers passing through the electronic device in real time; S2. Preliminary analysis of customer behavior: S21. Analyze factor A, including: determine whether the customer slows down; S22. Analyze factor B, including: whether the customer looks at the electronic device when passing by it; S3. Confirm the analysis results and switch the display: S31. Based on the analysis results of factor A and factor B, if the results are both "yes", it is considered that the customer is interested in the currently displayed product; S32, the electronic device switches to display the two products, products C1 and C2, displayed when the customer's gaze is directed to the electronic device, to determine the product information of interest to the customer; S4. In-depth analysis of customer behavior: S41, analyzing customer eye behavior to determine which product the customer is looking at; S42, when the customer's eyes are directed to product C1, product C1 is displayed in full screen; if the customer's eyes are directed to product C2, product C2 is displayed in full screen; S5. Guide customers into the store: S51, lighting up the LED light strip leading to the product display area to form a guide path to guide customers; S52, identifying the basic information of the customer's appearance, and pushing it to the shopping guide together with the information of the products that the customer is interested in. The shopping guide connects with the customer based on the pushed information and provides personalized services; S6. Data collection and optimization: Collect statistical data after the transaction is completed, analyze it based on the collected data, and optimize the advertising display strategy.

2. The method for acquiring and guiding customers in stores based on customer behavior analysis according to claim 1, characterized in that: The specific process of step S21 includes: The customer's movement trajectory is captured in real time through AI cameras, and analysis is performed to determine whether the customer has obvious deceleration behavior when passing by electronic device displays. The deceleration behavior is judged based on a preset speed threshold. When the customer's speed is lower than 70% of the normal walking speed, it is determined that the customer is slowing down.

3. The method for acquiring and guiding customers in stores based on customer behavior analysis according to claim 1, characterized in that: The specific process of step S41 is as follows: S411, performing grayscale, denoising, and image enhancement preprocessing on the captured customer facial image; S412, locating a face region in the preprocessed image; S413, within the detected face region, further identifying and locating the eye region by extracting eye contours and locating eye key points, wherein the eye key points include eye corners and pupil centers; this generally includes: S414, tracking the up and down movement trajectory of the eyelids in real time in the located eye area; S415. Determine which product the customer's gaze is directed to based on the result of the eye movement analysis.

4. The method for acquiring and guiding customers in stores based on customer behavior analysis according to claim 3 is characterized by: The specific processing process of step S415 is as follows: A reference template is set, wherein the reference template sets an eyelid threshold line, the position of the eyelid is tracked in real time, and the eye area image is placed in the reference template. When the upper eyelid is above the threshold line, it is determined that the customer is interested in product C1; when the upper eyelid is below the threshold line, it is determined that the customer is interested in product C2.

5. The method for acquiring and guiding customers in stores based on customer behavior analysis according to claim 1, characterized in that: In S52, the basic information of the customer's appearance includes gender, estimated age, and clothing color.

6. The method for acquiring and guiding customers in stores based on customer behavior analysis according to claim 5, characterized in that: The specific process of step S6 includes: S61. Data collection and collation: S611. Collect and record all transaction data that are guided and ultimately completed through the customer behavior analysis system, including but not limited to the duration of advertisements, volume of advertisements, duration of customer viewing, and duration of introduction by shopping guides; S612, sorting the collected data and removing invalid or abnormal data points; S62. Data analysis: Analyze the impact of various control parameters on the transaction rate and generate statistical graphs. The control parameters include the duration of advertisement playback, the volume of the advertisement, the viewing time of customers, the duration of the shopping guide's introduction, and the introduction method of the shopping guide. The statistical graph contains multiple curves, each of which represents the relationship between a parameter or a combination of parameters and the transaction rate. S63, optimal parameter settings: By observing the shape and peak position of the curve in the statistical chart, find the highest point or optimal range of the transaction rate corresponding to each parameter, and identify which parameter setting range or parameter combination setting range is most conducive to improving the transaction rate; adjust and optimize the control parameters based on the optimal parameter settings obtained through analysis.

7. The method for acquiring and guiding customers in stores based on customer behavior analysis according to claim 6, characterized in that: The method further includes the following steps: repeating steps S1-S6, continuously collecting and analyzing data, adjusting parameter settings, and evaluating adjustment effects.

8. The method for acquiring and guiding customers in stores based on customer behavior analysis according to claim 1, characterized in that: The electronic devices include a host computer and a large electronic display screen.

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