Commodity recommendation method and device, storage medium and computer program product
By analyzing the shopping behavior and product information of e-commerce users and pushing shopping guidance information, it solves the problem that users in e-commerce have difficulty placing orders quickly, and improves shopping efficiency and merchant efficiency.
Patent Information
- Application Number
- CN202410989707.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-07-23
- Publication Date
- 2025-01-07
AI Technical Summary
In e-commerce shopping, due to the diversity of similar products, it is difficult for users to place orders quickly, and the order conversion rate is low, which affects shopping efficiency and merchant sales efficiency.
By obtaining relevant information in the list of items to be shopping and user operation behaviors, analyzing the decisive factors of users when judging whether to purchase, and pushing corresponding shopping guidance information, including product series, performance, price and appearance information, to guide users to quickly download one.
It improves user purchasing efficiency, saves time and costs, and promotes merchants' sales efficiency. By analyzing the differential information under the same product category, it provides targeted shopping guidance to help users quickly select suitable products.
Smart Images
Figure CN119273419A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the technical field of Internet shopping, and in particular to a commodity recommendation method, device, storage medium and computer program product. Background Art
[0002] With the development of Internet technology, there are more and more Internet-based applications. Based on e-commerce applications, users can buy all kinds of goods they need without leaving home. When purchasing goods, users can learn about the category, pictures or reviews of the goods through the product details page, and decide whether to buy the goods based on this. Although the product details page has given enough information for users to fully understand the product, due to the differences in style, price or appearance of similar products, users often cannot place orders quickly during the shopping process, hesitate, and waste a lot of time, resulting in a low order conversion rate and poor user purchasing efficiency. Summary of the invention
[0003] The present disclosure provides a product recommendation method, device, storage medium and computer program product, which can guide users to determine target products, realize rapid order placement and purchase, and improve product order conversion rate.
[0004] In a first aspect, the present disclosure provides a product recommendation method, comprising the following steps:
[0005] Obtain relevant information of the items to be purchased in the list of items to be purchased;
[0006] Determining the decision factors that the user considers when deciding whether to purchase the product to be purchased based on the relevant information of the product to be purchased and the user's behavior when operating the product to be purchased in the list of products to be purchased;
[0007] Corresponding shopping guidance information is pushed to the user according to the decision factors.
[0008] In some embodiments, the user's actions when operating the items to be purchased in the list of items to be purchased include:
[0009] The user's operation behavior of adding and / or deleting the items to be purchased in the list of items to be purchased.
[0010] In some embodiments, the determining factors that the user considers when deciding whether to purchase the product include at least one of product series, product performance, product price, and product appearance.
[0011] In some embodiments, the pushing corresponding shopping guidance information to the user according to the consideration factors includes:
[0012] When the determining factor includes a product series, the shopping guidance information pushed to the user includes relevant information for introducing the product series to which the product to be purchased belongs;
[0013] When the determining factor includes product performance, the shopping guidance information pushed to the user includes relevant information about product performance parameters; the relevant information about product performance parameters includes comparison information about performance differences under the same function;
[0014] When the determining factor includes commodity price, the shopping guidance information pushed to the user includes relevant information for introducing the price discount of the commodity to be purchased;
[0015] When the determining factor includes the appearance of the product, the shopping guidance information pushed to the user includes relevant information about the appearance of the product, and the relevant information about the appearance of the product includes the size and / or color of the product.
[0016] In some embodiments, determining the decision factors considered by the user when determining whether to purchase the product to be purchased based on the relevant information of the product to be purchased and the user's behavior when operating the product to be purchased in the list of products to be purchased includes:
[0017] Determining the commodity category to which the commodity to be purchased in the list of commodities to be purchased belongs according to the relevant information of the commodity to be purchased;
[0018] For the to-be-purchased products belonging to the same product category, analyzing the user's behavior when operating the to-be-purchased products belonging to the product category in the to-be-purchased product list;
[0019] The determining factors considered by the user when judging whether to purchase the commodity to be purchased belonging to the commodity category are determined according to the behavior analysis result.
[0020] In some embodiments, after determining the commodity category to which the commodity in the list of commodities to be purchased belongs according to the relevant information of the commodity to be purchased, the method further comprises the following steps:
[0021] When the items to be purchased in the list of items to be purchased have at least two categories, the items to be purchased in the category that meet preset conditions are selected as target objects, and the user's behavior when operating the target objects in the list of items to be purchased is analyzed.
[0022] In some embodiments, for the to-be-purchased products belonging to the same product category, analyzing the user's behavior when operating the to-be-purchased products belonging to the product category in the to-be-purchased product list, and determining the determining factors considered by the user when determining whether to purchase the to-be-purchased products belonging to the product category according to the behavior analysis results, includes:
[0023] When there are at least two commodities to be purchased belonging to the same commodity category, the commodities to be purchased under the commodity category are compared to determine difference information between the commodities to be purchased;
[0024] Analyzing the user's behavior when operating the to-be-purchased goods belonging to the product category in the to-be-purchased goods list;
[0025] The determining factors considered by the user when judging whether to purchase the goods to be purchased are determined based on the difference information between the goods to be purchased and the behavior of the user when operating the goods to be purchased belonging to the goods category in the goods to be purchased list.
[0026] In a second aspect, the present disclosure provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the above aspect.
[0027] In a third aspect, the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method described in the above aspects when executed by a processor.
[0028] In a fourth aspect, the present disclosure provides a computer program product, including a computer program / instructions, which implements the steps of the method described in the above aspects when the computer program is executed by a processor.
[0029] Compared with the prior art, one or more embodiments of the above scheme may have the following advantages or beneficial effects:
[0030] The present disclosure provides a product recommendation method, device, storage medium and computer program product, the recommendation method comprising: obtaining relevant information of products to be purchased in a list of products to be purchased; determining the decision factors that the user considers when judging whether to purchase the products to be purchased based on the relevant information of the products to be purchased and the user's behavior when operating the products to be purchased in the list of products to be purchased; and pushing corresponding shopping guidance information to the user based on the decision factors. By analyzing the user's shopping behavior and relevant information of the goods to be purchased in the shopping cart, it is possible to determine the decisive factors that the user considers when deciding whether to purchase the goods to be purchased, thereby providing customers with shopping guidance information based on the decisive factors, guiding customers to place orders quickly, improving the purchasing efficiency of goods, saving time costs, and promoting the efficiency of merchants selling goods; by analyzing the product categories of the goods to be purchased in the shopping cart, filtering the product categories that the user wants to purchase, and then recommending from multiple products to be purchased in the product category, it is possible to filter and recommend under multiple categories of goods in the shopping cart, which is conducive to guiding users to place orders quickly; by analyzing the difference information between the goods to be purchased under the same product category, it is possible to accurately find out the user's current decisive factors, thereby providing targeted shopping guidance information, facilitating the solution of the problem points considered by the user, selecting suitable goods, and improving the user's ordering efficiency. BRIEF DESCRIPTION OF THE DRAWINGS
[0031] The present disclosure will be described in more detail below based on embodiments and with reference to the accompanying drawings:
[0032] Figure 1 An exemplary flow chart of a commodity recommendation method provided in Embodiment 1 of the present disclosure;
[0033] Figure 2 This is an exemplary flow chart of determining whether to provide a recommendation before step S1 of the product recommendation method in the embodiment of the present disclosure;
[0034] Figure 3 The embodiment of the present disclosure corresponds to Figure 1 An exemplary flow chart of S2;
[0035] Figure 4 The embodiment of the present disclosure corresponds to Figure 3 An exemplary flow chart of S22-S23;
[0036] Figure 5 The embodiment of the present disclosure corresponds to Figure 1 A further exemplary flow chart of S3;
[0037] Figure 6 This is an exemplary page display diagram of an application example of the third embodiment of the present disclosure;
[0038] Figure 7 This is an exemplary page display diagram of an application example of the fourth embodiment of the present disclosure;
[0039] Figure 8 This is an exemplary page display diagram of an application example of the fifth embodiment of the present disclosure;
[0040] Fig. 9 A schematic block diagram of a computer device provided in an embodiment of the present disclosure;
[0041] Fig.10 A schematic diagram of a readable storage medium provided in an embodiment of the present disclosure.
[0042] In the drawings, the same reference numerals are used for the same components, and the drawings are not drawn to scale. DETAILED DESCRIPTION
[0043] In order to enable those skilled in the art to better understand the technical solution of the present disclosure, and to fully understand and implement how the present disclosure applies technical means to solve technical problems and achieve the corresponding technical effects, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only embodiments of a part of the present disclosure, not all of the embodiments. The embodiments of the present disclosure and the various features in the embodiments can be combined with each other without conflict, and the technical solutions formed are all within the scope of protection of the present disclosure. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present disclosure.
[0044] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.
[0045] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.
[0046] With the development of Internet technology, the e-commerce industry has emerged. More and more people are accustomed to shopping online. People spend more and more time shopping online. At the same time, various styles of goods are emerging in an endless stream. In order to meet user needs in many aspects, merchants usually offer multiple optional goods for the same category of products. Each product includes multiple series of products, products with different attribute data, products with different prices, and products with different appearances. As a result, although users have the need to buy such products, they will be hesitant because of the large number of choices of such products. They are not sure which one is more suitable for them, which wastes a lot of time and affects shopping efficiency, order conversion rate and merchant sales efficiency.
[0047] The disclosed embodiment provides a commodity recommendation method, which includes the following steps: obtaining relevant information of the commodities to be purchased in the list of commodities to be purchased; determining the decision factors considered by the user when judging whether to purchase the commodities to be purchased based on the relevant information of the commodities to be purchased and the behavior of the user when operating the commodities to be purchased in the list of commodities to be purchased; and pushing corresponding shopping guidance information to the user based on the decision factors. By analyzing the user's shopping behavior and the relevant information of the commodities to be purchased in the shopping cart, it is possible to determine the decision factors considered by the user when judging whether to purchase the commodities to be purchased, thereby providing shopping guidance information to the customer based on the decision factors, guiding the customer to place an order quickly, improving the purchase efficiency of commodities, saving time costs, and promoting the efficiency of merchants selling goods.
[0048] Embodiment 1
[0049] Figure 1 The flowchart of a commodity recommendation method provided by the embodiment of the present disclosure is as follows. Figure 1 As shown, a commodity recommendation method includes steps S1-S3, specifically:
[0050] S1. Obtain relevant information of the items to be purchased in the list of items to be purchased.
[0051] In some embodiments, when a user uses a shopping app, he or she usually selects the goods that he or she intends to buy and adds them to the shopping cart first, and then places an order to buy them. When the goods added to the shopping cart have not been paid for a long time, a product recommendation is provided. In this embodiment, the list of goods to be purchased is a shopping cart list.
[0052] In some embodiments, Figure 2 As shown, before step S1, the product recommendation method further includes:
[0053] S01, displaying a shopping cart page and recording the display time of the page, and determining the length of time a user stays on the shopping cart page;
[0054] S02, determining whether the stay duration exceeds a preset duration threshold;
[0055] If so, it is determined to provide the user with a product purchase recommendation, and the steps of the product recommendation method are executed.
[0056] In this embodiment, the preset time threshold can be 5 seconds to 5 minutes, which can be adjusted according to the actual experience, so as to facilitate determining the purpose of the user staying on the shopping cart page and improve the user's shopping experience.
[0057] In some embodiments, when the stay time exceeds a preset time threshold, a pop-up window is displayed on the shopping cart page to prompt the user whether to activate the product recommendation. When the user agrees to activate the product recommendation, it is determined to provide the user with product purchase recommendations and execute the steps of the product recommendation method. By providing the user with a selection window, it is convenient for the user to make choices according to their own needs, thereby improving the user's shopping experience.
[0058] In some embodiments, the relevant information of the goods to be purchased in step S1 includes at least one of the series, performance, price and appearance of the goods to be purchased. Usually, for the convenience of users to view, all the relevant information can be displayed to facilitate users to accurately choose goods to purchase.
[0059] S2. Determine the decision factors that the user considers when deciding whether to purchase the goods to be purchased based on the relevant information of the goods to be purchased and the user's behavior when operating the goods to be purchased in the list of goods to be purchased.
[0060] In some embodiments, the user's behavior when operating the items to be purchased in the list of items to be purchased includes: the user's operation behavior when adding and / or deleting the items to be purchased in the list of items to be purchased.
[0061] In some embodiments, the user's operation of adding items to the shopping list includes the process from the user searching for the items to be purchased to adding them to the shopping cart, so that when analyzing the user behavior, it is possible to determine the product information that the user cares about through the keywords searched by the user, and then determine the factors that determine whether the user purchases the product.
[0062] In some embodiments, step S2, such as Figure 3 As shown, specifically including:
[0063] S21, determining the commodity category to which the commodity to be purchased in the list of commodities to be purchased belongs according to the relevant information of the commodity to be purchased;
[0064] S22, for the to-be-purchased products belonging to the same product category, analyzing the user's behavior when operating the to-be-purchased products belonging to the product category in the to-be-purchased product list;
[0065] S23. Determine, based on the behavior analysis result, the determining factors that the user considers when deciding whether to purchase the commodity to be purchased belonging to the commodity category.
[0066] By determining the commodity category to which the to-be-purchased goods belong, it is possible to analyze the to-be-purchased goods of the same commodity category, thereby facilitating targeted recommendations when there are multiple commodity categories in the shopping cart, thereby improving the user's ordering efficiency.
[0067] In some embodiments, when the items to be purchased in the list of items to be purchased have at least two categories of items, different categories of items can be analyzed separately to find out the determining factors of each category of items, so as to facilitate users to choose and purchase items to be purchased in different categories. Even if there are multiple categories of items in the list of items to be purchased, product recommendations can be provided one by one for ordering, thereby improving user ordering efficiency and shopping experience.
[0068] In some embodiments, between step S21 and step S22, step S2 further includes:
[0069] When the items to be purchased in the list of items to be purchased have at least two categories, the items to be purchased in the category that meet preset conditions are selected as target objects, and the user's behavior when operating the target objects in the list of items to be purchased is analyzed.
[0070] In this embodiment, by selecting a commodity category that meets the conditions from a plurality of commodity categories, shopping guidance can be provided for the commodity category that meets the user's current concerns, so as to provide shopping guidance accurately according to the user's needs.
[0071] Specifically, the preset conditions include commodity categories whose number of commodities to be purchased ranks in accordance with preset rankings. Usually, the first to third ranked commodity categories can be selected for analysis. The more commodities to be purchased in a commodity category, the more complex the decision factors considered by users for the commodity category, and the more difficult it is to place an order. By analyzing the commodities to be purchased in the commodity category, it can better meet the user's current shopping mentality, thereby improving the user's ordering efficiency and shopping experience.
[0072] Furthermore, the preset conditions also include that after filtering out the commodity categories that meet the preset ranking, the filtered commodity categories are arranged in order through a window for the user to select, so that after the user's selection, the commodity category that the user wants to provide commodity recommendations is determined, and then the next step is entered for analysis and processing. By allowing the user to select the commodity category for commodity recommendation by himself, the user's decision factors can be analyzed more specifically, thereby improving the user's shopping experience and ordering efficiency.
[0073] In some embodiments, there may be multiple items to be purchased in the same product category in the list of items to be purchased. Based on this, steps S22-S23, such as Figure 4 As shown, including:
[0074] S221, when there are at least two commodities to be purchased belonging to the same commodity category, compare the commodities to be purchased under the commodity category to determine difference information between the commodities to be purchased;
[0075] S222, analyzing the user's behavior when operating the to-be-purchased goods belonging to the goods category in the to-be-purchased goods list;
[0076] S231. Determine the factors that the user considers when deciding whether to purchase the goods to be purchased based on the difference information between the goods to be purchased and the user's behavior when operating the goods to be purchased belonging to the goods category in the list of goods to be purchased.
[0077] In some embodiments, when using shopping software, users will search according to their needs. For example, if they search for a 1-horsepower air conditioner, multiple styles of 1-horsepower air conditioners will be presented, and the user can select one or more from the search list and add them to the shopping cart. This behavior is the user's operation behavior of adding the items to be purchased to the list of items to be purchased; at the same time, the user adds or deletes or modifies the selected styles, specifications, etc. of the multiple target items added to the shopping cart on the shopping cart page, which also reflects the user's operation behavior on the list of items to be purchased; among them, the process from the user's search keyword to the addition of the item to the shopping cart and the user's modification behavior on the shopping cart page can determine the search factors of this type of target product, thereby facilitating and accurately determining the user's decision factors and improving the user's purchasing efficiency.
[0078] In some embodiments, the determining factors that the user considers when deciding whether to purchase the commodity to be purchased include at least one of the determining factors of the commodity series, commodity performance, commodity price, and commodity appearance. Usually, in order to achieve healthy competition among internal products, merchants will sell multiple commodity series for the same category of commodities. At the same time, they configure commodities with different commodity performance to increase the commodity coverage, and present commodities with different commodity prices based on different material costs to meet the needs of users in different price ranges, or design different appearances to meet the aesthetic tastes of different users. Therefore, when purchasing commodities, users usually consider at least one of the determining factors of the commodity series, commodity performance, commodity price, and commodity appearance. By analyzing user behavior, the user's determining factors are accurately determined, which facilitates the subsequent targeted introduction based on the determining factors, and improves the accuracy of guiding users to place orders.
[0079] S3. Push corresponding shopping guidance information to the user according to the decision factors.
[0080] In some embodiments, Figure 5 As shown, pushing corresponding shopping guidance information to the user according to the consideration factors includes:
[0081] S31, when the determining factor includes a product series, the shopping guidance information pushed to the user includes relevant information for introducing the product series to which the product to be purchased belongs;
[0082] S32: When the determining factor includes product performance, the shopping guidance information pushed to the user includes relevant information about product performance parameters; the relevant information about product performance parameters includes comparison information about performance differences under the same function;
[0083] S33, when the determining factor includes commodity price, the shopping guidance information pushed to the user includes relevant information for introducing the price discount of the commodity to be purchased;
[0084] S34: When the determining factor includes product appearance, the shopping guidance information pushed to the user includes relevant information about product appearance, where the relevant information about product appearance includes size and / or color of the product.
[0085] In some embodiments, the relevant information of the product performance parameters includes the applicable usage environment of the product performance parameters. Therefore, when the determining factor includes product performance, the shopping guidance information pushed to the user includes question and answer information for determining the user's usage environment for the product to be purchased, and then recommends appropriate product performance parameters according to the user's usage environment. Among them, the question and answer information can adopt AI question and answer, and each question is a multiple-choice question. Through the content selected by the user, the user's specific usage environment is guided, so as to facilitate the targeted provision of product selection suggestions. In step S33, the shopping guidance information pushed to the user also includes coupon information provided by the merchant of the current product to be purchased or the most favorable purchase method of the current merchant's preferential activities, so as to prompt the user to purchase at the best price and improve the user's order efficiency.
[0086] In some embodiments, in order to facilitate and accurately push shopping guidance information to users, step S3 includes: pushing a selection window to the user whether to agree to provide shopping guidance information based on the decision factors; when the user agrees, pushing shopping guidance information corresponding to the decision factors to the user.
[0087] Among them, if the user has multiple decision factors, the shopping guidance information corresponding to each decision factor can be pushed in turn, or the shopping guidance information can be provided specifically by the user selecting the decision factor required by the user, so as to improve the accuracy of product recommendations and the user's shopping experience.
[0088] In some embodiments, when the corresponding shopping guidance information is pushed to the user, if the shopping guidance information has a large amount of content, the content can be displayed one by one by sliding to switch the display content, so that the user can switch pages to view it conveniently.
[0089] In some embodiments, shopping guidance information may be presented to the user in the form of text or video playback or list comparison.
[0090] The commodity recommendation method provided by the embodiment of the present disclosure can determine the decisive factors considered by the user when judging whether to purchase the commodity to be purchased by analyzing the user's shopping behavior and the information of the commodities to be purchased in the shopping cart, thereby providing customers with solutions based on the decisive factors, pushing shopping guidance information to users, guiding customers to place orders quickly, improving the purchasing efficiency of commodities, saving time costs, and promoting the efficiency of merchants selling goods; by analyzing multiple commodity categories in the shopping cart, screening the commodity categories that the user wants to purchase, and thus recommending the commodities to be purchased in the commodity category, it is possible to make targeted recommendations under multiple commodities in the shopping cart, which is conducive to guiding users to place orders quickly; by analyzing the difference information of multiple commodities to be purchased under the same commodity category, it is possible to quickly clarify the decisive factors currently considered by the user, thereby providing targeted shopping guidance information, facilitating solving user concerns, selecting suitable commodities, and improving user ordering efficiency.
[0091] Embodiment 2
[0092] Based on the above embodiments, this embodiment provides an application example.
[0093] This embodiment takes the home appliance shopping APP as an example. When the user selects the home appliance shopping APP in the mobile phone to purchase electrical appliances, the user searches according to his own needs, such as searching for an air conditioner of 1 horsepower, and selects a "Tianli 1 horsepower" in the search list and adds it to the shopping cart. Another 1 horsepower air conditioner of another series is selected in the list and added to the shopping cart. At this time, the user behavior is analyzed through the commodity recommendation method in the first embodiment. The user may be unsure about the difference between different series of air conditioners and have questions. A pop-up window is displayed on the shopping cart page to prompt the user whether a recommendation is needed. If the user needs a recommendation, an explanation button is displayed after each air conditioner in the shopping cart page. When the user clicks the explanation button, the selected product can be explained to explain the product series. In this embodiment, the shopping guide information can be presented to the user in the form of text or video playback or list comparison. After understanding, the user can click the button to exit the explanation mode, which is convenient for the user to quickly understand the product differentiation, so as to face up to the user's own needs, choose the appropriate product for their own order, and increase the order speed.
[0094] Embodiment 3
[0095] Based on the above embodiments, this embodiment provides an application example.
[0096] This embodiment takes the home appliance shopping APP as an example. When the user selects the home appliance shopping APP on the mobile phone to purchase electrical appliances, the user searches according to his or her needs. For example, the user searches for an air conditioner with a capacity of 1 HP, selects a 1 HP air conditioner from the search list and adds it to the shopping cart. Then, the user enters "air conditioner 1.5P" in the search bar for the second time, and after searching, selects a 1.5 HP air conditioner from the list and adds it to the shopping cart. By using the recommendation method in the first embodiment to analyze user behavior, the user may be unsure about the capacity of the air conditioner and may have questions. Figure 8 As shown, the user should be reminded whether guidance is needed. After the user agrees, the user is given different capacities suitable for different rooms. The user's environmental needs are determined through questions and answers, and then the recommended air conditioner capacities are provided, and the reasons are provided, so that the user can choose the air conditioner that suits his environment and place an order. In special cases, such as the house facing south or west or on the top floor, or if the specific room size is unknown, the query function provided by the APP can be used to query the floor plan of the house to determine the purchase capacity, so that the user can quickly place an order.
[0097] Embodiment 4
[0098] Based on the above embodiments, this embodiment provides an application example.
[0099] This embodiment takes a home appliance shopping APP as an example. When a user selects the home appliance shopping APP in a mobile phone to purchase an appliance, the user selects multiple air conditioners of different prices and puts them into the shopping cart according to his / her needs. At this time, the user's consideration factor is analyzed as the price factor through the recommendation method in the first embodiment, such as Figure 7 As shown, a discount information window is displayed on the shopping cart page, through which users are prompted to collect coupons or discount methods of current activities, or a prompt that a certain air conditioner that meets the user's needs is the lowest price of the year or has a text slogan such as "buy early and enjoy early", etc., to encourage users to select the corresponding air conditioner and place an order to purchase it, so that users can quickly place an order to purchase.
[0100] Embodiment 5
[0101] Based on the above embodiments, this embodiment provides an application example.
[0102] This embodiment takes a home appliance shopping APP as an example. When a user selects the home appliance shopping APP in a mobile phone to purchase an appliance, the user selects a plurality of air conditioners with greatly different appearances and puts them into a shopping cart according to his / her needs. At this time, the user's consideration factor is analyzed by the recommendation method in the first embodiment as the appearance factor of the air conditioner, such as Figure 8As shown, a pop-up window will appear on the shopping cart page to prompt the user whether they need recommendations. If the user chooses to need recommendations, the design highlights, inspiration sources, awards, house matching, etc. of each air conditioner will be displayed, and the user can slide to switch product explanation content to provide guidance for the user's choice and facilitate the user to place an order quickly.
[0103] Embodiment 6
[0104] Based on the above embodiments, this embodiment provides a computer device, such as Fig. 9 As shown, it includes a memory 21, a processor 22 and a computer program stored in the memory 21, and the processor 22 executes the computer program to implement the steps of the method described in the above embodiment.
[0105] In some implementations of this embodiment, a computer readable storage medium is provided, such as Fig.10 As shown, a computer program 31 is stored thereon, and when the computer program 31 is executed by a processor, the steps of the method described in the above embodiment are implemented.
[0106] In some implementations of this embodiment, a computer program product is provided, including a computer program / instructions, and when the computer program is executed by a processor, the steps of the method described in the above embodiment are implemented.
[0107] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components to execute the method in the above embodiments.
[0108] The computer-readable storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, and the computer-readable storage medium may include but is not limited to, for example, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, computer storage media (e.g., hard disk, floppy disk, solid-state drive, removable disk, CD-ROM, DVD-ROM, Blu-ray disc, etc.).
[0109] The computer-readable storage medium may also store at least one computer executable program / instruction, which may be, for example, a computer-readable instruction. The computer-readable storage medium includes, but is not limited to, for example, a volatile memory and / or a non-volatile memory. The volatile memory may include, for example, a random access memory (RAM) and / or a cache memory (cache), etc. The computer-readable storage medium may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device runs the computer-readable instructions stored on the computer-readable storage medium, the various methods described above may be performed.
[0110] In addition, the computer device may also include (but not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (eg, keyboard, mouse, speaker, etc.), etc.
[0111] The processor may communicate with external devices via an I / O bus via a wired or wireless network.
[0112] In one embodiment, the at least one computer executable instruction may also be compiled into or constitute a software product / computer program product, wherein one or more computer executable instructions are executed by a processor to perform the various functions and / or method steps in the embodiments described in the present technology.
[0113] In the embodiments provided in the present disclosure, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.
[0114] It should be noted that in the present disclosure, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element limited by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.
[0115] Although the embodiments disclosed in the present disclosure are as above, the above contents are only embodiments adopted for facilitating the understanding of the present disclosure and are not intended to limit the present disclosure. Any technician in the technical field to which the present disclosure belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present disclosure, but the scope of patent protection of the present disclosure shall still be subject to the scope defined in the attached claims.
Claims
1. A product recommendation method, characterized in that: The following steps are involved: Obtain relevant information of the items to be purchased in the list of items to be purchased; Determining the decision factors that the user considers when deciding whether to purchase the product to be purchased based on the relevant information of the product to be purchased and the user's behavior when operating the product to be purchased in the list of products to be purchased; Corresponding shopping guidance information is pushed to the user according to the decision factors.
2. A commodity recommendation method according to claim 1, characterized in that: The user's behavior when operating the items to be purchased in the list of items to be purchased includes: The user's operation behavior of adding and / or deleting the items to be purchased in the list of items to be purchased.
3. A commodity recommendation method according to claim 1, characterized in that: The determining factors that the user considers when deciding whether to purchase the commodity include at least one of commodity series, commodity performance, commodity price and commodity appearance.
4. A commodity recommendation method according to claim 3, characterized in that: The pushing corresponding shopping guidance information to the user according to the consideration factors includes: When the determining factor includes a product series, the shopping guidance information pushed to the user includes relevant information for introducing the product series to which the product to be purchased belongs; When the determining factor includes product performance, the shopping guidance information pushed to the user includes relevant information about product performance parameters; the relevant information about product performance parameters includes comparison information about performance differences under the same function; When the determining factor includes commodity price, the shopping guidance information pushed to the user includes relevant information for introducing the price discount of the commodity to be purchased; When the determining factor includes the appearance of the product, the shopping guidance information pushed to the user includes relevant information about the appearance of the product, and the relevant information about the appearance of the product includes the size and / or color of the product.
5. A commodity recommendation method according to claim 1, characterized in that: Determining the decision factors that the user considers when deciding whether to purchase the product to be purchased based on the relevant information of the product to be purchased and the user's behavior when operating the product to be purchased in the list of products to be purchased includes: Determining the commodity category to which the commodity to be purchased in the list of commodities to be purchased belongs according to the relevant information of the commodity to be purchased; For the to-be-purchased products belonging to the same product category, analyzing the user's behavior when operating the to-be-purchased products belonging to the product category in the to-be-purchased product list; The determining factors considered by the user when judging whether to purchase the commodity to be purchased belonging to the commodity category are determined according to the behavior analysis result.
6. A commodity recommendation method according to claim 5, characterized in that: After determining the commodity category to which the commodity in the list of commodities to be purchased belongs based on the relevant information of the commodity to be purchased, the method further comprises the following steps: When the items to be purchased in the list of items to be purchased have at least two categories, the items to be purchased in the category that meet preset conditions are selected as target objects, and the user's behavior when operating the target objects in the list of items to be purchased is analyzed.
7. A commodity recommendation method according to claim 5, characterized in that: For the to-be-purchased products belonging to the same product category, analyzing the user's behavior when operating the to-be-purchased products belonging to the product category in the to-be-purchased product list, and determining the determining factors considered by the user when judging whether to purchase the to-be-purchased products belonging to the product category according to the behavior analysis results, includes: When there are at least two commodities to be purchased belonging to the same commodity category, the commodities to be purchased under the commodity category are compared to determine difference information between the commodities to be purchased; Analyzing the user's behavior when operating the to-be-purchased goods belonging to the product category in the to-be-purchased goods list; The determining factors considered by the user when judging whether to purchase the goods to be purchased are determined based on the difference information between the goods to be purchased and the behavior of the user when operating the goods to be purchased belonging to the goods category in the goods to be purchased list.
8. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 7.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.
10. A computer program product comprising a computer program / instructions, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.