技术领域Technical field
本发明属于电商平台产品智能更换领域，涉及到一种基于数据分析的电商平台产品智能更换系统。The invention belongs to the field of intelligent replacement of e-commerce platform products and relates to an intelligent replacement system for e-commerce platform products based on data analysis.
背景技术Background technique
当今社会，随着互联网的普及和技术的发展，人们对电商平台的使用越来越频繁。电商平台产品推荐功能可以帮助消费者找到符合自己需求的商品，提高购买体验和满意度，而商铺首页面的产品推荐展示可以促进销售增长和库存优化，对电商平台的发展具有重要意义。In today's society, with the popularization of the Internet and the development of technology, people use e-commerce platforms more and more frequently. The product recommendation function of e-commerce platforms can help consumers find products that meet their needs and improve purchasing experience and satisfaction. The product recommendation display on the store home page can promote sales growth and inventory optimization, which is of great significance to the development of e-commerce platforms.
在现有的电商平台产品展示功能中，当用户登录至某商铺首页后，该商铺首页推荐展位对应的产品多为固定顺序，没有针对具体用户进行智能更换展示，在产品推荐模式上缺乏灵活变动性，用户在进入店铺浏览商品时总是看到相同的产品，会让他们感到无聊和疲惫。并且，只是提供固定顺序的产品展示，很难满足市场的需求和变化，限制了平台的发展潜力。In the existing e-commerce platform product display function, when a user logs in to a store's homepage, the products corresponding to the recommended booths on the store's homepage are mostly in a fixed order. There is no intelligent replacement display for specific users, and there is a lack of flexibility in the product recommendation model. Variability, users always see the same products when they enter the store to browse products, which will make them feel bored and tired. Moreover, it is difficult to meet the needs and changes of the market by only providing a fixed order of product display, which limits the development potential of the platform.
同时，商铺首页推荐展位对应的产品往往是根据平台综合售出情况和平台内综合用户购买情况进行分析，忽略了产品退货情况以及具体用户对产品的各方面期待情况，例如产品价格是否在用户接受程度内、产品是否为用户购买后确认退货产品，从而使得推荐产品不能满足某些用户的个性化需求。At the same time, the products corresponding to the recommended booths on the store homepage are often analyzed based on the comprehensive sales situation of the platform and the comprehensive user purchase situation within the platform, ignoring the situation of product returns and specific user expectations for the product, such as whether the product price is acceptable to the user. Within the scope, whether the product is a product that is confirmed to be returned after the user purchases it, thus making the recommended products unable to meet the personalized needs of some users.
发明内容Contents of the invention
鉴于此，为解决上述背景技术中所提出的问题，现提出一种基于数据分析的电商平台产品智能更换系统。In view of this, in order to solve the problems raised in the above background technology, an intelligent replacement system for e-commerce platform products based on data analysis is now proposed.
本发明的目的可以通过以下技术方案实现：本发明提供一种基于数据分析的电商平台产品智能更换系统，该系统包括：产品销售需求分析模块：用于当目标用户登录目标商铺首页时，获取目标商铺对应各产品库存数目和产品单价，以此分析目标商铺的各产品曝光需求度。The object of the present invention can be achieved through the following technical solutions: The present invention provides an intelligent replacement system for e-commerce platform products based on data analysis. The system includes: a product sales demand analysis module: used to obtain when the target user logs in to the homepage of the target store. The target store corresponds to the inventory quantity and product unit price of each product, so as to analyze the exposure demand of each product in the target store.
产品热度分析模块：用于提取目标商铺的各产品相关数据，各产品相关数据包括各产品在当前季度内的进货量、库存量和退货量，以此分析目标商铺的各产品销售热度。Product popularity analysis module: used to extract data related to each product of the target store. The data related to each product includes the purchase volume, inventory volume and return volume of each product in the current quarter, in order to analyze the sales popularity of each product in the target store.
产品展位评估模块：用于基于目标商铺的各产品曝光需求度和各产品销售热度，综合分析目标商铺的各产品综合销售需求指数，进而得到目标商铺各推荐展位当前产品。Product booth evaluation module: It is used to comprehensively analyze the comprehensive sales demand index of each product in the target store based on the exposure demand of each product and the sales popularity of each product in the target store, and then obtain the current products of each recommended booth in the target store.
用户数据采集模块：用于提取目标用户对各产品的行为记录，行为记录包括各产品的浏览记录、购买记录和购买记录关联的评价记录，并从浏览记录中提取浏览信息、从购买记录中提取购买信息，从评价记录中提取评价信息。User data collection module: used to extract the target user's behavior records for each product. The behavior records include the browsing records, purchase records and evaluation records associated with the purchase records of each product, and extract browsing information from the browsing records and extract from the purchase records. Purchase information, extract evaluation information from evaluation records.
数据处理分析模块：用于基于目标用户行为记录，构建目标用户对各产品的兴趣度。Data processing and analysis module: used to construct target users' interest in each product based on target user behavior records.
展位更换解析模块：用于基于目标用户对各产品的兴趣度，综合计算目标商铺各推荐展位当前产品的更换需求系数，进而将目标商铺在目标用户显示平台的推荐展位当前产品进行更换。Booth replacement analysis module: used to comprehensively calculate the replacement demand coefficient of the current products in each recommended booth of the target store based on the target user's interest in each product, and then replace the current products of the target store's recommended booth on the target user display platform.
数据库，用于存储各库存数目对应的曝光需求影响因子，存储好评词汇库、中评词汇库和差评词汇库对应的各关键词,并存储各产品对应各特征值。The database is used to store the exposure demand influencing factors corresponding to each inventory number, store the keywords corresponding to the good review vocabulary database, the medium review vocabulary database and the negative review vocabulary database, and store the characteristic values corresponding to each product.
本发明的具体实施例中，所述分析目标商铺的各产品曝光需求度相应分析方式为：从目标商铺对应数据存储库中获取目标商铺在当前时刻的各产品总库存数目Di和各产品单价Yi，i为产品编号，i＝1,2,…,m。In a specific embodiment of the present invention, the corresponding analysis method for analyzing the exposure demand of each product of the target store is: obtaining the total inventory number Di and unit price of each product of the target store at the current moment from the corresponding data storage database of the target store. Yi , i is the product number, i=1,2,…,m.
将Di、Yi代入公式得到目标商铺的各产品曝光需求度,其中，Di'、Yi'分别为设定的第i产品的参照库存数目和参照单价，/>分别为设定的产品库存数目和产品单价对应影响占比权重。Substitute Di and Yi into the formula Obtain the exposure demand of each product of the target store, where Di ' and Yi ' are respectively the set reference inventory quantity and reference unit price of the i-th product,/> These are the corresponding impact weights of the set product inventory quantity and product unit price.
本发明的具体实施例中，所述分析目标商铺的各产品销售热度的分析方式为：从目标商铺对应数据存储库中获取目标商铺的各产品在当前季度内对应的进货量、库存量和退货量，记为h1i、h2i、h3i，根据以下计算公式得到目标商铺的各产品销售率影响因子和目标商铺的各产品退货率对应的影响因子式中K1、K2为设定的参照销售率和参照退货率，e为自然常数。In a specific embodiment of the present invention, the analysis method for analyzing the sales popularity of each product of the target store is: obtaining the corresponding purchase volume, inventory volume and returns of each product of the target store in the current quarter from the corresponding data storage database of the target store. The quantity is recorded as h1i , h2i , h3i . According to the following calculation formula, the influencing factors of the sales rate of each product of the target store are obtained. The influencing factors corresponding to the return rate of each product of the target store In the formula, K1 and K2 are the set reference sales rate and reference return rate, and e is a natural constant.
将φ1i、φ2i代入公式得到目标商铺的各产品销售热度，其中l为设定的产品销售热度偏差修正因子。Substitute φ1i and φ2i into the formula Obtain the sales popularity of each product in the target store, where l is the set product sales popularity deviation correction factor.
本发明的具体实施例中，所述综合分析目标商铺的各产品综合销售需求指数的具体方式为：将各产品总库存数目与数据库中各库存数目对应的曝光需求影响因子进行对比，得到目标商铺在当前时刻的各产品总库存数目对应的曝光需求影响因子In a specific embodiment of the present invention, the specific method of comprehensively analyzing the comprehensive sales demand index of each product of the target store is: comparing the total inventory number of each product with the exposure demand impact factor corresponding to each inventory number in the database, to obtain the target store The exposure demand influencing factors corresponding to the total inventory quantity of each product at the current moment
将目标商铺的各产品曝光需求度和目标商铺的各产品销售热度代入公式X为设定常数，X>1,得到目标商铺的各产品综合销售需求指数。Substitute the exposure demand of each product of the target store and the sales popularity of each product of the target store into the formula X is a set constant, X>1, and the comprehensive sales demand index of each product of the target store is obtained.
获取目标商铺在目标用户显示平台的推荐展位数量，将目标商铺的各产品综合销售需求指数进行相互对比，并按从大到小顺序对各产品综合销售需求指数对应产品进行排序，进而从排序结果中选取符合推荐展位数量的产品，作为目标商铺各推荐展位当前产品。Obtain the number of recommended booths of the target store on the target user display platform, compare the comprehensive sales demand index of each product of the target store with each other, and sort the products corresponding to the comprehensive sales demand index of each product in descending order, and then use the sorting results Select products that match the number of recommended booths and use them as the current products of each recommended booth in the target store.
本发明的具体实施例中，所述浏览信息包括浏览次数和各次浏览时长。In a specific embodiment of the present invention, the browsing information includes the number of browsing times and the duration of each browsing time.
购买信息包括购买产品价格和购买产品是否确认退货。Purchase information includes the price of the purchased product and whether the purchased product is returned.
评价信息包括评价等级和各子评价关键词。The evaluation information includes evaluation levels and keywords for each sub-evaluation.
本发明的具体实施例中，所述构建目标用户对各产品的兴趣度的方式为：A1、基于购买记录对应的购买信息中购买产品是否确认退货，由此从购买记录中筛选出已确认退货的购买记录，进而将该购买记录中的购买产品与目标商铺对应各产品进行对比，若产品匹配成功，则获取目标商铺对应该产品编号，并将目标用户对该编号相应产品的兴趣度记为ε。In a specific embodiment of the present invention, the method for constructing the target user's interest in each product is: A1. Based on the purchase information corresponding to the purchase record, whether the return of the purchased product is confirmed, thereby filtering out the confirmed return from the purchase record purchase record, and then compare the purchased products in the purchase record with the products corresponding to the target store. If the products match successfully, obtain the product number corresponding to the target store, and record the target user's interest in the product corresponding to the number as ε.
A2、从购买记录对应的购买信息中提取购买产品价格，进而将目标用户在目标商铺中各产品对应各条购买记录的购买产品价格进行均值计算，得到目标用户在目标商铺的平均支付价格Q，进而由得到目标用户对各产品价格的接受度,其中△Q为产品支付价格偏差设定值。A2. Extract the purchase product price from the purchase information corresponding to the purchase record, and then average the purchase product prices of each product in the target store corresponding to each purchase record by the target user to obtain the average payment price Q of the target user in the target store. And then by Obtain the target user's acceptance of each product price, where △Q is the product price deviation set value.
A3、从目标用户对各产品的浏览信息中获取目标用户对各产品的浏览次数Fi和各次浏览时长，将各产品对应的各次浏览时长进行汇总，得到各产品对应的综合浏览时长Ti，将Fi、Ti代入公式得到目标用户对各产品的关注度，F'、T'分别为设定的产品参照浏览次数和参照浏览时长，△F、△T分别为产品浏览次数和浏览时长对应偏差设定值，χ1、χ2分别为设定的浏览次数和浏览时长对应影响占比权重。A3. Obtain the number of times Fi and the browsing time of each product by the target user from the browsing information of each product, summarize the browsing time corresponding to each product, and obtain the comprehensive browsing time T corresponding to each product.i , substitute Fi and Ti into the formula Obtain the target user's attention to each product, F' and T' are the set product reference browsing times and reference browsing duration respectively, △F and △T are the corresponding deviation setting values of product browsing times and browsing duration respectively, χ1, χ2 is the corresponding influence weight of the set number of views and browsing time respectively.
A4、基于各产品对应各条购买记录关联的评价记录相应评价信息，计算目标用户对各产品的偏好程度指数A4. Based on the corresponding evaluation information of the evaluation record associated with each purchase record of each product, calculate the target user's preference index for each product.
A5、由综合分析公式得到目标用户对各产品的兴趣度，即目标用户对各产品的兴趣度为θi＝ε或φi。A5. Based on the comprehensive analysis formula The target user's interest in each product is obtained, that is, the target user's interest in each product is θi =ε or φi .
本发明的具体实施例中，所述计算目标用户对各产品的偏好程度指数的具体步骤为：G1、从各产品对应各条购买记录关联的评价记录相应评价信息中提取各产品对应各评价关键词，将其与数据库中的好评词汇库、中评词汇库和差评词汇库对应的各关键词进行对比，统计得到目标用户对各产品的好评关键词数量B1i和中评关键词数量B2i。In a specific embodiment of the present invention, the specific steps for calculating the target user's preference index for each product are: G1. Extract each product's corresponding evaluation key from the corresponding evaluation information of the evaluation record associated with each purchase record corresponding to each product. words, compare them with the keywords corresponding to the good review vocabulary library, medium review vocabulary library and negative review vocabulary library in the database, and statistically obtain the number of good review keywords B1i and the number of medium review keywords for each product by the target users B2i .
G2、计算目标用户对各产品的偏好程度指数Si为目标用户对第i个产品的评价等级，Si为整数且Si∈[1，5]，U为设定常数，U>1,B0i为目标用户第i个产品的评价关键词总数量，γ为设定的偏好程度指数对应的偏差修正因子。G2. Calculate target users’ preference index for each product Si is the evaluation level of the i-th product by the target user, Si is an integer and Si ∈ [1, 5], U is a set constant, U>1, B0i is the evaluation of the i-th product by the target user The total number of keywords, γ is the bias correction factor corresponding to the set preference index.
本发明的具体实施例中，所述计算目标商铺各推荐展位当前产品的更换需求系数对应步骤为：J1、将目标用户对各产品的兴趣度和目标商铺的各产品综合销售需求指数代入公式，计算得到目标商铺各产品在目标用户显示平台的综合推荐系数In a specific embodiment of the present invention, the corresponding steps for calculating the replacement demand coefficient of the current product in each recommended booth of the target store are: J1. Substituting the target user's interest in each product and the comprehensive sales demand index of each product of the target store into the formula, Calculate the comprehensive recommendation coefficient of each product of the target store on the target user display platform
J2、将目标商铺各产品在目标用户显示平台的综合推荐系数进行相互对比，并按从大到小顺序对各产品在目标用户显示平台的综合推荐系数对应产品进行排序，从排序结果中选取符合推荐展位数量的产品，得到目标商铺各推荐展位对应最终显示产品。J2. Compare the comprehensive recommendation coefficients of each product in the target store on the target user display platform with each other, and sort the products corresponding to the comprehensive recommendation coefficients of each product on the target user display platform in descending order, and select the products that meet the requirements from the sorting results. Recommend the number of products in the booth, and get the final display products corresponding to each recommended booth in the target store.
J3、基于目标商铺各推荐展位对应最终显示产品的各特征值、目标商铺各推荐展位当前产品的各特征值，计算得到各推荐展位对应最终显示产品与其相应当前产品的特征相似度(cosα)r，r为推荐展位编号，r＝1,2,…,c。J3. Based on the characteristic values of the final display products corresponding to each recommended booth of the target store and the characteristic values of the current products of each recommended booth of the target store, calculate the characteristic similarity (cosα)r of the final displayed product corresponding to each recommended booth and its corresponding current product. , r is the recommended booth number, r=1,2,…,c.
J4、由分析公式得到目标商铺各推荐展位当前产品的更换需求系数，λ为设定的更换需求系数阈值，△λ为设定的更换需求系数偏差允许值。J4. From the analytical formula Obtain the replacement demand coefficient of the current products in each recommended booth of the target store, λ is the set replacement demand coefficient threshold, and △λ is the set replacement demand coefficient deviation allowable value.
本发明的具体实施例中，所述各推荐展位对应最终显示产品与其相应当前产品的特征相似度具体计算过程为：从数据库中提取目标商铺各推荐展位对应最终显示产品的各特征值，得到其特征向量同理得到目标商铺各推荐展位当前产品的特征向量/>j为特征值编号，j＝1,2,…,d。In a specific embodiment of the present invention, the specific calculation process of the characteristic similarity between each recommended booth corresponding to the final displayed product and its corresponding current product is: extracting each characteristic value corresponding to the final displayed product at each recommended booth of the target store from the database, and obtaining the characteristic similarity Feature vector In the same way, the feature vectors of the current products in each recommended booth of the target store are obtained/> j is the eigenvalue number, j=1,2,…,d.
由计算公式得到各推荐展位对应最终显示产品与其相应当前产品的特征相似度。By calculation formula Obtain the feature similarity between the final display product corresponding to each recommended booth and its corresponding current product.
本发明的具体实施例中，所述将目标商铺在目标用户显示平台的推荐展位当前产品进行更换的具体步骤为：将目标商铺各推荐展位当前产品的更换需求系数与设定的更换需求系数阈值进行对比，若目标商铺某推荐展位当前产品的更换需求系数大于或等于设定的更换需求系数阈值，则将目标商铺该推荐展位当前产品更换为对应推荐展位的最终显示产品。In the specific embodiment of the present invention, the specific steps of replacing the current products of the target store in the recommended booth of the target user display platform are: comparing the replacement demand coefficient of the current product of each recommended booth of the target store with the set replacement demand coefficient threshold For comparison, if the replacement demand coefficient of the current product in a recommended booth of the target store is greater than or equal to the set replacement demand coefficient threshold, the current product of the recommended booth of the target store will be replaced with the final display product of the corresponding recommended booth.
相较于现有技术，本发明的有益效果如下：(1)本发明结合商家层面和用户层面，基于目标商铺的各产品综合销售需求指数和目标用户对各产品的兴趣度，综合判断是否对显示平台的推荐展位当前产品进行智能更换，丰富了商铺内产品推荐模式的同时从多维度分析用户偏好，更好地满足了商家和用户的双重需求，并且增强了商家与用户之间的联结性。Compared with the existing technology, the beneficial effects of the present invention are as follows: (1) The present invention combines the merchant level and the user level, based on the comprehensive sales demand index of each product of the target store and the target user's interest in each product, to comprehensively determine whether it is appropriate. The current products in the recommended booths on the display platform are intelligently replaced, which enriches the product recommendation model in the store and analyzes user preferences from multiple dimensions, better meets the dual needs of merchants and users, and enhances the connection between merchants and users. .
(2)本发明在分析目标商铺的各产品综合销售需求指数时，保证商铺内产品库存量充足的同时考虑了商铺内产品利润和退货情况，据此得出目标商铺各推荐展位的推荐产品，可以提高商铺内的产品销售效率，并且可以确定哪些产品需要大量进货，哪些产品需要少量进货，从而降低库存成本。(2) When analyzing the comprehensive sales demand index of each product in the target store, the present invention ensures that the product inventory in the store is sufficient and also considers the profit and returns of the products in the store. Based on this, the recommended products for each recommended booth of the target store are obtained. It can improve the efficiency of product sales in the store and determine which products need to be purchased in large quantities and which products need to be purchased in small quantities, thereby reducing inventory costs.
(3)本发明针对具体用户在具体商铺的购买记录和浏览记录，分析目标用户对各产品的兴趣度，通过减少购买产品中确认退货产品和目标用户不感兴趣的产品价格对兴趣度的影响，可以推荐更加符合目标用户需求的产品，从而提高目标用户的购物体验。此外，商铺服务也是用户产生购物欲的一项重要指标，通过增强商家与用户之间的互动性，有助于增加商家的服务知名度。(3) This invention analyzes the target user's interest in each product based on the purchase records and browsing records of specific users in specific stores, and reduces the impact on the interest of purchased products by reducing the price of confirmed returned products and products that the target user is not interested in. It can recommend products that better meet the needs of target users, thus improving the shopping experience of target users. In addition, store services are also an important indicator of users' desire to shop. By enhancing the interaction between merchants and users, they help increase the merchant's service visibility.
附图说明Description of drawings
为了更清楚地说明本发明实施例的技术方案，下面将对实施例描述所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。In order to explain the technical solutions of the embodiments of the present invention more clearly, the drawings needed to describe the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without exerting creative efforts.
图1为本发明系统模块连接示意图。Figure 1 is a schematic connection diagram of system modules of the present invention.
具体实施方式Detailed ways
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.
请参阅图1所示，本发明提供了一种基于数据分析的电商平台产品智能更换系统，该系统包括：产品销售需求分析模块、产品热度分析模块、产品展位评估模块、用户数据采集模块、数据处理分析模块、展位更换解析模块和数据库。所述产品展位评估模块分别与产品销售需求分析模块、产品热度分析模块和展位更换解析模块连接，用户数据采集模块与数据处理分析模块连接，数据处理分析模块与展位更换解析模块连接，数据库分别与产品展位评估模块、数据处理分析模块和展位更换解析模块连接。Referring to Figure 1, the present invention provides an intelligent replacement system for e-commerce platform products based on data analysis. The system includes: a product sales demand analysis module, a product popularity analysis module, a product booth evaluation module, and a user data collection module. Data processing and analysis module, booth replacement analysis module and database. The product booth evaluation module is connected to the product sales demand analysis module, product popularity analysis module and booth replacement analysis module respectively, the user data collection module is connected to the data processing and analysis module, the data processing analysis module is connected to the booth replacement analysis module, and the database is respectively connected to The product booth evaluation module, data processing analysis module and booth replacement analysis module are connected.
所述产品销售需求分析模块用于当目标用户登录目标商铺首页时，获取目标商铺对应各产品库存数目和产品单价，以此分析目标商铺的各产品曝光需求度。The product sales demand analysis module is used to obtain the inventory quantity and product unit price of each product corresponding to the target store when the target user logs in to the homepage of the target store, thereby analyzing the exposure demand of each product of the target store.
作为一种优选的方案，所述分析目标商铺的各产品曝光需求度相应分析方式为：从目标商铺对应数据存储库中获取目标商铺在当前时刻的各产品总库存数目Di和各产品单价Yi，i为产品编号，i＝1,2,…,m。As a preferred solution, the corresponding analysis method for analyzing the exposure demand of each product of the target store is: obtaining the total inventory number Di and unit price Y of each product of the target store at the current moment from the corresponding data storage database of the target store.i , i is the product number, i=1,2,…,m.
将Di、Yi代入公式得到目标商铺的各产品曝光需求度,其中，Di'、Yi'分别为设定的第i产品的参照库存数目和参照单价，/>分别为设定的产品库存数目和产品单价对应影响占比权重。Substitute Di and Yi into the formula Obtain the exposure demand of each product of the target store, where Di ' and Yi ' are respectively the set reference inventory quantity and reference unit price of the i-th product,/> These are the corresponding impact weights of the set product inventory quantity and product unit price.
需要说明的，所述目标商铺的各产品曝光需求度是从商家层面进行分析，目标商铺中某产品总库存数目越多，则表示目标商铺对该产品的售出需求度越大，进而目标商铺对该产品的曝光需求度与该产品总库存数目成正比关系；目标商铺中某产品单价越高，则表示目标商铺对该产品的售出利润越大，进而目标商铺对该产品的曝光需求度与该产品单价成正比关系。It should be noted that the exposure demand of each product of the target store is analyzed from the merchant level. The greater the total inventory of a certain product in the target store, the greater the sales demand of the product in the target store, and thus the target store The exposure demand for the product is directly proportional to the total inventory of the product; the higher the unit price of a product in the target store, the greater the target store's profit from selling the product, and thus the target store's exposure demand for the product. Directly proportional to the unit price of the product.
所述产品热度分析模块用于提取目标商铺的各产品相关数据，各产品相关数据包括各产品在当前季度内的进货量、库存量和退货量，以此分析目标商铺的各产品销售热度。The product popularity analysis module is used to extract the relevant data of each product of the target store. The relevant data of each product includes the purchase volume, inventory volume and return volume of each product in the current quarter, so as to analyze the sales popularity of each product of the target store.
作为一种优选的方案，所述分析目标商铺的各产品销售热度的分析方式为：从目标商铺对应数据存储库中获取目标商铺的各产品在当前季度内对应的进货量、库存量和退货量，记为h1i、h2i、h3i，根据以下计算公式得到目标商铺的各产品销售率影响因子和目标商铺的各产品退货率对应的影响因子式中K1、K2为设定的参照销售率和参照退货率，e为自然常数。As a preferred solution, the analysis method for analyzing the sales popularity of each product of the target store is: obtaining the corresponding purchase volume, inventory volume, and return volume of each product of the target store in the current quarter from the corresponding data storage database of the target store. , recorded as h1i , h2i , h3i , according to the following calculation formula, the influencing factors of each product sales rate of the target store are obtained The influencing factors corresponding to the return rate of each product of the target store In the formula, K1 and K2 are the set reference sales rate and reference return rate, and e is a natural constant.
将φ1i、φ2i代入公式得到目标商铺的各产品销售热度，其中l为设定的产品销售热度偏差修正因子。Substitute φ1i and φ2i into the formula Obtain the sales popularity of each product in the target store, where l is the set product sales popularity deviation correction factor.
所述产品展位评估模块用于基于目标商铺的各产品曝光需求度和各产品销售热度，综合分析目标商铺的各产品综合销售需求指数，进而得到目标商铺各推荐展位当前产品。The product booth evaluation module is used to comprehensively analyze the comprehensive sales demand index of each product in the target store based on the exposure demand of each product and the sales popularity of each product in the target store, and then obtain the current products of each recommended booth in the target store.
在本发明的又一优选方案中，所述产品热度分析模块内容还包括：将目标商铺的各产品销售热度与设定的产品销售热度进行对比，若某产品销售热度大于或等于设定的产品销售热度，则按设定划分原则对该产品销售热度的占比权重进行划分，进而在下一季度进货时，基于该产品销售热度的占比权重，对该产品进货量进行相应调整。In another preferred embodiment of the present invention, the content of the product popularity analysis module also includes: comparing the sales popularity of each product in the target store with the set product sales popularity, if the sales popularity of a certain product is greater than or equal to the set product For sales popularity, the proportional weight of the product's sales popularity will be divided according to the set division principle, and then when purchasing in the next quarter, based on the proportional weight of the product's sales popularity, the purchase volume of the product will be adjusted accordingly.
示例性的，当某产品销售热度的占比权重为时，/>作为下一季度该产品进货量。For example, when the proportion weight of a product's sales popularity is When,/> As the purchase volume of this product in the next quarter.
作为一种优选的方案，所述综合分析目标商铺的各产品综合销售需求指数的具体方式为：将各产品总库存数目与数据库中各库存数目对应的曝光需求影响因子进行对比，得到目标商铺在当前时刻的各产品总库存数目对应的曝光需求影响因子As a preferred solution, the specific method of comprehensively analyzing the comprehensive sales demand index of each product of the target store is: comparing the total inventory number of each product with the exposure demand influencing factors corresponding to each inventory number in the database, and obtaining the target store's sales demand index. The exposure demand influencing factors corresponding to the total inventory quantity of each product at the current moment
将目标商铺的各产品曝光需求度和目标商铺的各产品销售热度代入公式X为设定常数，X>1,得到目标商铺的各产品综合销售需求指数。Substitute the exposure demand of each product of the target store and the sales popularity of each product of the target store into the formula X is a set constant, X>1, and the comprehensive sales demand index of each product of the target store is obtained.
获取目标商铺在目标用户显示平台的推荐展位数量，将目标商铺的各产品综合销售需求指数进行相互对比，并按从大到小顺序对各产品综合销售需求指数对应产品进行排序，进而从排序结果中选取符合推荐展位数量的产品，作为目标商铺各推荐展位当前产品。Obtain the number of recommended booths of the target store on the target user display platform, compare the comprehensive sales demand index of each product of the target store with each other, and sort the products corresponding to the comprehensive sales demand index of each product in descending order, and then use the sorting results Select products that match the number of recommended booths and use them as the current products of each recommended booth in the target store.
示例性的，当目标商铺在目标用户显示平台的推荐展位数量为5时，获取排在前五位的产品综合销售需求指数对应的产品，作为目标商铺各推荐展位当前产品。For example, when the number of recommended booths of the target store on the target user display platform is 5, the products corresponding to the comprehensive sales demand index of the top five products are obtained as the current products of each recommended booth of the target store.
本发明在分析目标商铺的各产品综合销售需求指数时，保证商铺内产品库存量充足的同时考虑了商铺内产品利润和退货情况，据此得出目标商铺各推荐展位的推荐产品，可以提高商铺内的产品销售效率，并且可以确定哪些产品需要大量进货，哪些产品需要少量进货，从而降低库存成本。When analyzing the comprehensive sales demand index of each product of the target store, the present invention ensures that the product inventory in the store is sufficient and also considers the profit and return situation of the products in the store. Based on this, the recommended products for each recommended booth of the target store are obtained, which can improve the store. The product sales efficiency within the system can be determined, and which products need to be purchased in large quantities and which products need to be purchased in small quantities, thereby reducing inventory costs.
所述用户数据采集模块用于提取目标用户对各产品的行为记录，行为记录包括各产品的浏览记录、购买记录和购买记录关联的评价记录，并从浏览记录中提取浏览信息、从购买记录中提取购买信息，从评价记录中提取评价信息。The user data collection module is used to extract the target user's behavior records for each product. The behavior records include the browsing records, purchase records and evaluation records associated with the purchase records of each product, and extracts browsing information from the browsing records, and extracts browsing information from the purchase records. Extract purchase information and extract evaluation information from evaluation records.
作为一种优选的方案，所述浏览信息包括浏览次数和各次浏览时长。As a preferred solution, the browsing information includes the number of browsing times and the duration of each browsing time.
购买信息包括包括购买产品价格和购买产品是否确认退货。Purchase information includes the price of the purchased product and whether the purchased product is returned.
评价信息包括评价等级和各子评价关键词。The evaluation information includes evaluation levels and keywords for each sub-evaluation.
所述数据处理分析模块用于基于目标用户行为记录，构建目标用户对各产品的兴趣度。The data processing and analysis module is used to construct the target user's interest in each product based on the target user's behavior records.
作为一种优选的方案，所述构建目标用户对各产品的兴趣度的方式为：A1、基于购买记录对应的购买信息中购买产品是否确认退货，由此从购买记录中筛选出已确认退货的购买记录，进而将该购买记录中的购买产品与目标商铺对应各产品进行对比，若产品匹配成功，则获取目标商铺对应该产品编号，并将目标用户对该编号相应产品的兴趣度记为ε。As a preferred solution, the method of constructing the target user's interest in each product is: A1. Based on the purchase information corresponding to the purchase record, whether the return of the purchased product is confirmed, thereby filtering out the confirmed returns from the purchase record purchase record, and then compare the purchased products in the purchase record with the products corresponding to the target store. If the products match successfully, obtain the product number corresponding to the target store, and record the target user's interest in the product corresponding to the number as ε .
A2、从购买记录对应的购买信息中提取购买产品价格，进而将目标用户在目标商铺中各产品对应各条购买记录的购买产品价格进行均值计算，得到目标用户在目标商铺的平均支付价格Q，进而由得到目标用户对各产品价格的接受度,其中△Q为产品支付价格偏差设定值。A2. Extract the purchase product price from the purchase information corresponding to the purchase record, and then average the purchase product prices of each product in the target store corresponding to each purchase record by the target user to obtain the average payment price Q of the target user in the target store. And then by Obtain the target user's acceptance of each product price, where △Q is the product price deviation set value.
A3、从目标用户对各产品的浏览信息中获取目标用户对各产品的浏览次数Fi和各次浏览时长，将各产品对应的各次浏览时长进行汇总，得到各产品对应的综合浏览时长Ti，将Fi、Ti代入公式得到目标用户对各产品的关注度，F'、T'分别为设定的产品参照浏览次数和参照浏览时长，△F、△T分别为产品浏览次数和浏览时长对应偏差设定值，χ1、χ2分别为设定的浏览次数和浏览时长对应影响占比权重。A3. Obtain the number of times Fi and the browsing time of each product by the target user from the browsing information of each product, summarize the browsing time corresponding to each product, and obtain the comprehensive browsing time T corresponding to each product.i , substitute Fi and Ti into the formula Obtain the target user's attention to each product, F' and T' are the set product reference browsing times and reference browsing duration respectively, △F and △T are the corresponding deviation setting values of product browsing times and browsing duration respectively, χ1, χ2 is the corresponding influence weight of the set number of views and browsing time respectively.
需要说明的，当目标用户未浏览某产品时，相应的目标用户对该产品的浏览次数和浏览时长均为0。It should be noted that when the target user has not browsed a certain product, the corresponding target user's number of views and browsing time for the product are both 0.
A4、基于各产品对应各条购买记录关联的评价记录相应评价信息，计算目标用户对各产品的偏好程度指数A4. Based on the corresponding evaluation information of the evaluation record associated with each purchase record of each product, calculate the target user's preference index for each product.
A5、由综合分析公式得到目标用户对各产品的兴趣度，即目标用户对各产品的兴趣度为θi＝ε或φi。A5. Based on the comprehensive analysis formula The target user's interest in each product is obtained, that is, the target user's interest in each product is θi =ε or φi .
作为一种优选的方案，所述计算目标用户对各产品的偏好程度指数的具体步骤为：G1、从各产品对应各条购买记录关联的评价记录相应评价信息中提取各产品对应各评价关键词，将其与数据库中的好评词汇库、中评词汇库和差评词汇库对应的各关键词进行对比，统计得到目标用户对各产品的好评关键词数量B1i和中评关键词数量B2i。As a preferred solution, the specific steps for calculating the target user's preference index for each product are: G1. Extract the evaluation keywords corresponding to each product from the evaluation information corresponding to the evaluation records associated with each purchase record corresponding to each product. , compare it with the keywords corresponding to the good review vocabulary library, medium review vocabulary library and negative review vocabulary library in the database, and statistically obtain the number of good review keywords B1i and the number of medium review keywords B for each product by the target users2i.
G2、计算目标用户对各产品的偏好程度指数Si为目标用户对第i个产品的评价等级，Si为整数且Si∈[1，5]，U为设定常数，U>1,B0i为目标用户第i个产品的评价关键词总数量，γ为设定的偏好程度指数对应的偏差修正因子。G2. Calculate target users’ preference index for each product Si is the evaluation level of the i-th product by the target user, Si is an integer and Si ∈ [1, 5], U is a set constant, U>1, B0i is the evaluation of the i-th product by the target user The total number of keywords, γ is the bias correction factor corresponding to the set preference index.
需要说明的，所述各产品对应各评价关键词获取方式为：将各产品对应各条购买记录关联的评价记录相应评价信息中的各子评价关键词进行汇总，得到各产品对应各评价关键词。It should be noted that the method for obtaining the evaluation keywords corresponding to each product is: summarizing the sub-evaluation keywords in the evaluation information corresponding to the evaluation records associated with each purchase record of each product, to obtain the evaluation keywords corresponding to each product. .
所述展位更换解析模块用于基于目标用户对各产品的兴趣度，综合计算目标商铺各推荐展位当前产品的更换需求系数，进而将目标商铺在目标用户显示平台的推荐展位当前产品进行更换。The booth replacement analysis module is used to comprehensively calculate the replacement demand coefficient of the current products in each recommended booth of the target store based on the target user's interest in each product, and then replace the current products of the target store's recommended booth on the target user display platform.
作为一种优选的方案，所述计算目标商铺各推荐展位当前产品的更换需求系数对应步骤为：J1、将目标用户对各产品的兴趣度和目标商铺的各产品综合销售需求指数代入公式，计算得到目标商铺各产品在目标用户显示平台的综合推荐系数As a preferred solution, the corresponding steps for calculating the replacement demand coefficient of the current products in each recommended booth of the target store are: J1. Substitute the target user's interest in each product and the comprehensive sales demand index of each product of the target store into the formula, and calculate Obtain the comprehensive recommendation coefficient of each product of the target store on the target user display platform
J2、将目标商铺各产品在目标用户显示平台的综合推荐系数进行相互对比，并按从大到小顺序对各产品在目标用户显示平台的综合推荐系数对应产品进行排序，从排序结果中选取符合推荐展位数量的产品，得到目标商铺各推荐展位对应最终显示产品。J2. Compare the comprehensive recommendation coefficients of each product in the target store on the target user display platform with each other, and sort the products corresponding to the comprehensive recommendation coefficients of each product on the target user display platform in descending order, and select the products that meet the requirements from the sorting results. Recommend the number of products in the booth, and get the final display products corresponding to each recommended booth in the target store.
J3、基于目标商铺各推荐展位对应最终显示产品的各特征值、目标商铺各推荐展位当前产品的各特征值，计算得到各推荐展位对应最终显示产品与其相应当前产品的特征相似度(cosα)r，r为推荐展位编号，r＝1,2,…,c。J3. Based on the characteristic values of the final display products corresponding to each recommended booth of the target store and the characteristic values of the current products of each recommended booth of the target store, calculate the characteristic similarity (cosα)r of the final displayed product corresponding to each recommended booth and its corresponding current product. , r is the recommended booth number, r=1,2,…,c.
J4、由分析公式得到目标商铺各推荐展位当前产品的更换需求系数，λ为设定的更换需求系数阈值，△λ为设定的更换需求系数偏差允许值。J4. From the analytical formula Obtain the replacement demand coefficient of the current products in each recommended booth of the target store, λ is the set replacement demand coefficient threshold, and △λ is the set replacement demand coefficient deviation allowable value.
作为一种优选的方案，所述各推荐展位对应最终显示产品与其相应当前产品的特征相似度具体计算过程为：从数据库中提取目标商铺各推荐展位对应最终显示产品的各特征值，得到其特征向量同理得到目标商铺各推荐展位当前产品的特征向量/>j为特征值编号，j＝1,2,…,d。As a preferred solution, the specific calculation process of the characteristic similarity between each recommended booth corresponding to the final displayed product and its corresponding current product is: extracting each characteristic value corresponding to the final displayed product at each recommended booth of the target store from the database to obtain its characteristics vector In the same way, the feature vectors of the current products in each recommended booth of the target store are obtained/> j is the eigenvalue number, j=1,2,…,d.
由计算公式得到各推荐展位对应最终显示产品与其相应当前产品的特征相似度，其中0≤cosα≤1，当cosα＝1时，表示两个特征向量完全相似；当cosα＝0时，表示两个特征向量完全不相似。By calculation formula Obtain the feature similarity of the final display product corresponding to each recommended booth and its corresponding current product, where 0 ≤ cos α ≤ 1. When cos α = 1, it means that the two feature vectors are completely similar; when cos α = 0, it means that the two feature vectors are completely similar. not similar.
作为一种优选的方案，所述将目标商铺在目标用户显示平台的推荐展位当前产品进行更换的具体步骤为：将目标商铺各推荐展位当前产品的更换需求系数与设定的更换需求系数阈值进行对比，若目标商铺某推荐展位当前产品的更换需求系数大于或等于设定的更换需求系数阈值，则将目标商铺该推荐展位当前产品更换为对应推荐展位的最终显示产品。As a preferred solution, the specific steps for replacing the current products of the recommended booths of the target store on the target user display platform are: comparing the replacement demand coefficient of the current products of each recommended booth of the target store with the set replacement demand coefficient threshold. In contrast, if the replacement demand coefficient of the current product in a recommended booth of the target store is greater than or equal to the set replacement demand coefficient threshold, the current product of the recommended booth of the target store will be replaced with the final display product of the corresponding recommended booth.
本发明针对具体用户在具体商铺的购买记录和浏览记录，分析目标用户对各产品的兴趣度，通过减少购买产品中确认退货产品和目标用户不感兴趣的产品价格对兴趣度的影响，可以推荐更加符合目标用户需求的产品，从而提高目标用户的购物体验。此外，商铺服务也是用户产生购物欲的一项重要指标，通过增强商家与用户之间的互动性，有助于增加商家的服务知名度。This invention analyzes the target user's interest in each product based on the purchase records and browsing records of specific users in specific stores, and can recommend more products by reducing the impact on the interest of products that are confirmed to be returned and products that the target user is not interested in. Products that meet the needs of target users, thereby improving their shopping experience. In addition, store services are also an important indicator of users' desire to shop. By enhancing the interaction between merchants and users, they help increase the merchant's service visibility.
所述数据库用于存储各库存数目对应的曝光需求影响因子，存储好评词汇库、中评词汇库和差评词汇库对应的各关键词,并存储各产品对应各特征值。The database is used to store the exposure demand influencing factors corresponding to each inventory number, store the keywords corresponding to the good review vocabulary library, the medium review vocabulary library and the negative review vocabulary library, and store the characteristic values corresponding to each product.
本发明结合商家层面和用户层面，基于目标商铺的各产品综合销售需求指数和目标用户对各产品的兴趣度，综合判断是否对显示平台的推荐展位当前产品进行智能更换，丰富了商铺内产品推荐模式的同时从多维度分析用户偏好，提高了推荐的精准度和准确性，更好地满足了商家和用户的双重需求，并且增强了商家与用户之间的联结性。This invention combines the merchant level and the user level, based on the comprehensive sales demand index of each product in the target store and the target user's interest in each product, to comprehensively determine whether to intelligently replace the current product in the recommended booth of the display platform, enriching product recommendations in the store The model simultaneously analyzes user preferences from multiple dimensions, improves the precision and accuracy of recommendations, better meets the dual needs of merchants and users, and enhances the connection between merchants and users.
以上内容仅仅是对本发明的构思所作的举例和说明，所属本技术领域的技术人员对所描述的具体实施例做各种各样的修改或补充或采用类似的方式替代，只要不偏离发明的构思或者超越本发明所定义的范围，均应属于本发明的保护范围。The above contents are only examples and explanations of the concept of the invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or substitute them in similar ways, as long as they do not deviate from the concept of the invention. Or beyond the scope defined by the present invention, all shall belong to the protection scope of the present invention.
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| CN202311197931.0ACN117217868B (en) | 2023-09-15 | 2023-09-15 | Intelligent electronic commerce platform product replacement system based on data analysis |
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| CN118195690A (en)* | 2024-05-15 | 2024-06-14 | 浙江卡赢信息科技有限公司 | Intelligent commodity shelf selection method for point exchange mall based on bank user |
| CN118840046A (en)* | 2024-09-14 | 2024-10-25 | 北京奥维云网大数据科技股份有限公司 | Retail data processing method, device, computer equipment and computer storage medium |
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| CN113112334A (en)* | 2021-04-29 | 2021-07-13 | 潘丽璇 | Electronic commerce platform based on cloud computing |
| CN113139857A (en)* | 2021-05-17 | 2021-07-20 | 武汉阿杜拉电子商务有限公司 | Electronic commerce platform merchant store intelligent management method, system, equipment and computer storage medium |
| CN114693350A (en)* | 2022-03-29 | 2022-07-01 | 武汉历历晴川网络科技有限公司 | Commodity information processing method and equipment and computer storage medium |
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| KR20210066514A (en)* | 2019-11-28 | 2021-06-07 | (주)양유 | Marketing solution system that can analyze and manage the impact of the influencer and Marketing solution method using the same |
| CN113112334A (en)* | 2021-04-29 | 2021-07-13 | 潘丽璇 | Electronic commerce platform based on cloud computing |
| CN113139857A (en)* | 2021-05-17 | 2021-07-20 | 武汉阿杜拉电子商务有限公司 | Electronic commerce platform merchant store intelligent management method, system, equipment and computer storage medium |
| CN114693350A (en)* | 2022-03-29 | 2022-07-01 | 武汉历历晴川网络科技有限公司 | Commodity information processing method and equipment and computer storage medium |
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| CN118195690A (en)* | 2024-05-15 | 2024-06-14 | 浙江卡赢信息科技有限公司 | Intelligent commodity shelf selection method for point exchange mall based on bank user |
| CN118840046A (en)* | 2024-09-14 | 2024-10-25 | 北京奥维云网大数据科技股份有限公司 | Retail data processing method, device, computer equipment and computer storage medium |
| CN119323401A (en)* | 2024-12-19 | 2025-01-17 | 南昌航天广信科技有限责任公司 | Inventory management method for electronic commerce |
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