Sales platform

Abstract

The invention relates to the technical field of sales platforms, and discloses a sales platform, which comprises the steps of determining a first push strategy according to historical purchase records of a user in the recent year and commodities corresponding to keywords searched by the user, and pushing the commodities to the user according to the first push strategy; if the user completes purchasing in the commodities pushed under the first pushing strategy, pushing is not carried out any more, and if the user does not complete purchasing in the commodities pushed under the first pushing strategy, whether the pushing strategy needs to be adjusted or not is judged; if the push strategy needs to be adjusted, executing a second push strategy to push the commodity to the user; if the user completes purchasing in the commodities pushed under the second pushing strategy, pushing is not carried out any more; if the user does not complete purchase in the commodities pushed under the second pushing strategy; adjusting a pushing strategy according to the browsing data of the user on the commodity and acquiring a primary pushing strategy of the user; according to the sales platform, the accuracy of pushing commodities to the user is improved, and the shopping experience of the user is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of sales platforms, in particular to a sales platform. Background Art

[0002] With the increasing penetration of the Internet, e-commerce has become one of the mainstream shopping methods. More and more consumers tend to shop online because they provide convenience, diversity and 24-hour uninterrupted service. Therefore, online sales platforms can meet the growing online shopping needs of consumers. Therefore, a sales platform that can adjust the product push strategy according to user needs is crucial.

[0003] Traditional sales platforms still use a one-size-fits-all approach to push the same product information to all users. They do not adjust recommended content based on users’ purchase history, browsing history, or search behavior, and ignore users’ personalized needs and preferences. As a result, the products pushed often do not match users’ actual needs, causing users to lose interest in the recommended content or even feel disgusted.

[0004] When traditional sales platforms judge users' purchasing intention based on their browsing data, they often use the time users spend browsing the products and the time users communicate with customer service during the browsing process as the basis for judgment. However, in reality, there is invalid communication. Therefore, simply using the time users communicate with customer service during the browsing process as one of the judgment bases cannot truly reflect users' purchasing intention.

[0005] Traditional sales platforms cannot adjust their push strategies in a timely manner when users have little desire to purchase the products being pushed, resulting in a poor user experience. Users will gradually become disgusted with the platform, reducing user satisfaction, which may lead to user loss and switching to other sales platforms. Summary of the invention

[0006] The present invention provides a sales platform for facilitating solving the problems mentioned in the above background technology.

[0007] The present invention provides the following technical solution: a sales platform, comprising:

[0008] The search term entry module is used to obtain the keywords of the user's search terms when the user searches for products on the sales platform;

[0009] The record acquisition module is used to obtain the user's historical purchase records in the past year;

[0010] The data integration module is used to determine the first push strategy based on the user's historical purchase records in the past year and the products corresponding to the keywords on the sales platform;

[0011] A data browsing module, used to obtain the browsing data of the user on the product under the first push strategy;

[0012] Adjust the push module and determine whether the push strategy needs to be adjusted based on the browsing data of the user's historical purchase records in the past year.

[0013] Optionally, a sales method for the sales platform, comprising:

[0014] When users search for products on the sales platform;

[0015] Get the keywords of the user's search terms;

[0016] Obtain the user's historical purchase records in the past year;

[0017] Obtain products corresponding to keywords on the sales platform;

[0018] Determine the first push strategy based on the user's purchase history in the past year and the products corresponding to the keywords on the sales platform;

[0019] Push products to users according to the first push strategy;

[0020] Obtain the user's browsing data on products under the first push strategy;

[0021] If the user completes the purchase of the product pushed under the first push strategy, it will no longer be pushed;

[0022] If the user does not complete the purchase of the product pushed under the first push strategy;

[0023] Combine the browsing data of the user's historical purchase records in the past year to determine whether the push strategy needs to be adjusted;

[0024] If you need to adjust the push strategy;

[0025] The adjusted push strategy is recorded as the second push strategy;

[0026] Pushing products to users according to the second push strategy;

[0027] Obtaining the user's browsing data on products under the second push strategy;

[0028] If the user completes the purchase of the product pushed under the second push strategy, it will no longer be pushed;

[0029] If the user does not complete the purchase of the product pushed under the second push strategy;

[0030] Adjust push strategies based on users’ browsing data of products;

[0031] Record the push strategy corresponding to the product that the user has completed purchasing as the user's primary push strategy;

[0032] When a user searches for a product, the primary push strategy is executed first to push the product to the user.

[0033] Optional,

[0034] The first push strategy is determined based on the user's historical purchase records in the past year and the products corresponding to the keywords on the platform, specifically:

[0035] The products in the user's historical purchase records in the past year are recorded as target products;

[0036] Obtain after-sales data of target products;

[0037] The after-sales data includes whether the user applies for after-sales service after completing the purchase of the product and the type of evaluation made, which includes positive and negative evaluations;

[0038] If the user does not apply for after-sales service after completing the purchase of the target product and gives a favorable review of the product, the target product will be recorded as a first-class product;

[0039] The products corresponding to the keywords other than the target products on the sales platform are recorded as second-category products;

[0040] Get the number of second-category goods, denoted by N;

[0041] Obtain sales data of N second-category products on the sales platform in the past year;

[0042] The sales data specifically refers to the sales volume and the number of favorable comments of the product;

[0043] Pick any second-category product;

[0044] Calculate the favorable review rate of these two categories of products;

[0045] The positive review rate is specifically the ratio of the number of positive reviews of a product to the number of sales;

[0046] Get the number of users who purchased the second category of goods more than or equal to 2 times in the past year;

[0047] Get the total number of users who purchased these two categories of goods in the past year;

[0048] Calculate the repurchase rate of these two categories of goods;

[0049] The repurchase rate is specifically the ratio of the number of users who have purchased a certain product more than twice to the total number of users who have purchased the product.

[0050] Calculate the praise rate and repurchase rate of N second-category products respectively.

[0051] Optional,

[0052] The method of pushing the product to the user according to the first push strategy is as follows:

[0053] Create set A, set B and set C;

[0054] According to the sales quantity, the second category of goods are listed in set A from high to low;

[0055] According to the repurchase rate, the second category of goods are listed in set B from high to low;

[0056] According to the praise rate, the second category of products are listed in set C in descending order;

[0057] Create a set D;

[0058] If there is a category of products corresponding to the keyword in the target products;

[0059] List a category of target products corresponding to the keywords into set D;

[0060] If there is no product of the same category as the keyword in the target product, no processing will be done;

[0061] If there is no second-category product in set D, push the first, second, third, and tenth products in set A to set D;

[0062] Compare the first item in set B with the items in set D;

[0063] If the first item in set B does not exist in the items in set D, the first item in the target set is added to set D;

[0064] If the first product in set B already exists in the products in set D, then the second product in set B is selected and compared with the products in set D.

[0065] If the second item in set B does not exist in the items in set D, then the second item in set B is included in set D;

[0066] If the second product in set B already exists in the products in set D, then select the third product in set B and compare it with the products in set D.

[0067] If the third item in set B does not exist in the items in set D, then the third item in set B is included in set D;

[0068] If the third product in the target set does not exist in the products in set D, then select products in set B and compare them with the products in set D in turn until the number of products in set B included in set D is equal to 10;

[0069] If the number of commodities in set B included in set D is equal to 10, the commodities in set C are added to set D in sequence until the number of commodities in set C included in set D is equal to 10;

[0070] If there are two types of products in set D, the products in sets A, B and C are included in set D according to the product screening strategy;

[0071] The product screening strategy is specifically as follows:

[0072] Select a set at random and record it as the target set;

[0073] Compare the first item in the target set with the items in set D;

[0074] If the first item in the target set does not exist in the items in set D, then the first item in the target set is added to set D;

[0075] If the first product in the target set already exists in the products in set D, then the second product in the target set is selected and compared with the products in set D;

[0076] If the second item in the target set does not exist in the items in set D, the second item in the target set is added to set D;

[0077] If the second product in the target set already exists in the products in set D, then the third product in the target set is selected and compared with the products in set D.

[0078] If the third item in the target set does not exist in the items in set D, the third item in the target set is added to set D;

[0079] If the third product in the target set does not exist in the products in set D, then select products in the target set and compare them with the products in set D in turn until the number of products in the target set included in set D is equal to 10;

[0080] Push the products in set D to the user.

[0081] Optional,

[0082] The obtaining of the user's browsing data of the product under the first push strategy is specifically as follows:

[0083] Get the average browsing time of each target product, and record the average as T1;

[0084] S1. Establish a keyword set;

[0085] S2. Select a product at random;

[0086] S3. Users who purchased this product within the past year are recorded as category 1 users;

[0087] S4. Randomly select a user of the first category, and after the user of the first category agrees to the authorization, obtain the text record of the communication between the user of the first category and the customer service when purchasing the product;

[0088] S5, extracting all keywords related to the product in the text record, and listing all keywords in a keyword set;

[0089] S6. If this type of user does not agree to the authorization, no processing will be done;

[0090] S7, perform S4-S6 operation steps for all users of the first category, and then the keyword set of this product is obtained;

[0091] Get the keyword set of all target products;

[0092] Randomly select a target product and obtain the number of different keywords in the keyword set corresponding to the target product, and record the number as X;

[0093] Obtain the text records of the user's communication with customer service when browsing this target product;

[0094] Extract all keywords related to the target product in the text record, and obtain the number of different keywords, which is recorded as Y;

[0095] Then the user's effective communication value for this target product = Y ÷ X;

[0096] Calculate the effective communication value of the user for each target product, and obtain the average value of the effective communication value of the user for all target products, which is recorded as T2;

[0097] Get the user's browsing time for each product in set D respectively;

[0098] Obtain the user's effective communication value for each product in set D respectively;

[0099] If there are products in set D;

[0100] The user's browsing time for this product is ≥ T1 and the user's effective communication value for this product is ≥ T2;

[0101] Record this product as a potential product;

[0102] Get the number of potential products in a category in set D;

[0103] Calculate the ratio of the number of potential products in a category to the number of products in set D;

[0104] The ratio is recorded as the first ratio.

[0105] Optional,

[0106] The adjusted push strategy is recorded as the second push strategy, which is:

[0107] Set the threshold Z;

[0108] If the first ratio ≥ Z, the first push strategy is maintained to push the product to the user;

[0109] If the first ratio is less than Z, the second push strategy is executed, which is:

[0110] Get the high-frequency search terms on the sales platform in the past three days;

[0111] If there are high-frequency search terms that are the same as the user's search terms;

[0112] Then record this high-frequency search term as the target search term;

[0113] The products on the sales platform corresponding to the target search terms are recorded as three categories of products;

[0114] Get the number of items in set D, denoted by M;

[0115] Get the sales quantity of all three categories of goods in the past three days;

[0116] Create a set E;

[0117] According to sales quantity, the three categories of goods are listed in set E from largest to smallest;

[0118] Add the first, second, third, ...Mth items in set E to set F;

[0119] Push the products in collections F and D to the user.

[0120] Optional,

[0121] The obtaining of the user's browsing data of the product under the second push strategy is specifically as follows:

[0122] Get the user's browsing time for each product in set F respectively;

[0123] Obtain the user's effective communication value for each product in set F respectively;

[0124] If there are products in set F;

[0125] The user's browsing time for this product is ≥ T1 and the user's effective communication value for this product is ≥ T2;

[0126] Record this product as a potential second-class product;

[0127] Get the number of potential products of the second category in set F;

[0128] Calculate the ratio of the number of potential products in the second category to the number of products in set F;

[0129] The ratio is recorded as the second ratio.

[0130] Optional,

[0131] The push strategy is adjusted according to the user's browsing data of the product, specifically:

[0132] If the first ratio> the second ratio;

[0133] Then execute the first push strategy;

[0134] If the first ratio = the second ratio;

[0135] Then execute the second push strategy;

[0136] If the first ratio is less than the second ratio;

[0137] Then execute the third push strategy;

[0138] The third push strategy is specifically:

[0139] When pushing products to users, only the products in set F are pushed.

[0140] The present invention has the following beneficial effects:

[0141] 1. The sales platform divides the commodities into target commodities, first-category commodities and second-category commodities by analyzing the users' search keywords and historical purchase records. The second-category commodities are included in the collection according to the sales volume, favorable comment rate and repurchase rate of the second-category commodities. The repurchase rate reflects the users' satisfaction and loyalty to the commodities, while the favorable comment rate provides the users with direct feedback on the commodity quality. The first-category commodities and the second-category commodities in each collection are pushed to the users according to the first push strategy. Through the first push strategy, the sales platform can give priority to recommending the commodities that are both popular and well-received. This method not only improves the quality of the recommended commodities, but also effectively reduces the probability of users' dissatisfaction after purchase.

[0142] 2. The sales platform monitors the user's purchase intention for the recommended products in real time based on the user's browsing data for the products under the first push strategy. If the user does not complete the purchase, the system will collect new data and adjust the push strategy accordingly to generate a second push strategy. This dynamic adjustment mechanism enables the sales platform to flexibly respond to changes in user needs, thereby improving user engagement and satisfaction.

[0143] 3. The sales platform determines whether the user is influenced by the high-frequency search terms on the sales platform when purchasing goods based on the user's browsing data of goods under the second push strategy. If the user is influenced by the high-frequency search terms on the sales platform when purchasing goods and prefers goods corresponding to the high-frequency search terms, the third push strategy is executed. If the user has no preference, the first push strategy or the second push strategy is executed based on the browsing data. Through this comprehensive data analysis method, the recommendation results can better reflect user expectations, increase user shopping satisfaction, and thus improve the overall sales performance of the platform.

[0144] 4. After the user authorizes, the sales platform can extract keywords related to the product and calculate the effective communication value by analyzing the communication records between the user and the customer service. This indicator reflects the user's attention to and willingness to buy a certain product. By combining these data, the system can more accurately judge the user's willingness to buy, thereby pushing more accurate recommendations, avoiding interference from irrelevant products, improving the relevance of recommendations, and ultimately promoting sales.

[0145] 5. The sales platform has established sets A, B and C to screen products based on sales volume, repurchase rate and praise rate respectively; this multi-dimensional screening mechanism ensures that the products pushed to users are high-quality products that have been strictly evaluated; users can not only find products with high sales volume in the recommendations they receive, but also see products with good reputation. This combination can better meet the actual needs of users, thereby improving user satisfaction and purchase rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0146] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0147] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0148] Embodiment 1, a sales platform, comprising:

[0149] The search term entry module is used to obtain the keywords of the user's search terms when the user searches for products on the sales platform;

[0150] The record acquisition module is used to obtain the user's historical purchase records in the past year;

[0151] The data integration module is used to determine the first push strategy based on the user's historical purchase records in the past year and the products corresponding to the keywords on the sales platform;

[0152] A data browsing module, used to obtain the browsing data of the user on the product under the first push strategy;

[0153] Adjust the push module and determine whether the push strategy needs to be adjusted based on the browsing data of the user's historical purchase records in the past year.

[0154] Embodiment 2, a sales method of a sales platform, referring to Figure 1 :

[0155] When users search for products on the sales platform;

[0156] Get the keywords of the user's search terms;

[0157] Obtain the user's historical purchase records in the past year;

[0158] Obtain products corresponding to keywords on the sales platform;

[0159] Determine the first push strategy based on the user's purchase history in the past year and the products corresponding to the keywords on the sales platform;

[0160] Push products to users according to the first push strategy;

[0161] Obtain the user's browsing data on products under the first push strategy;

[0162] If the user completes the purchase of the product pushed under the first push strategy, it will no longer be pushed;

[0163] If the user does not complete the purchase of the product pushed under the first push strategy;

[0164] Combine the browsing data of the user's historical purchase records in the past year to determine whether the push strategy needs to be adjusted;

[0165] If you need to adjust the push strategy;

[0166] The adjusted push strategy is recorded as the second push strategy;

[0167] Pushing products to users according to the second push strategy;

[0168] Obtaining the user's browsing data on products under the second push strategy;

[0169] If the user completes the purchase of the product pushed under the second push strategy, it will no longer be pushed;

[0170] If the user does not complete the purchase of the product pushed under the second push strategy;

[0171] Adjust push strategies based on users’ browsing data of products;

[0172] Record the push strategy corresponding to the product that the user has completed purchasing as the user's primary push strategy;

[0173] When a user searches for a product, the primary push strategy is executed first to push the product to the user.

[0174] The first push strategy is determined based on the user's historical purchase records in the past year and the products corresponding to the keywords on the platform, specifically:

[0175] The products in the user's historical purchase records in the past year are recorded as target products;

[0176] Obtain after-sales data of target products;

[0177] The after-sales data includes whether the user applies for after-sales service after completing the purchase of the product and the type of evaluation made, which includes positive and negative evaluations;

[0178] If the user does not apply for after-sales service after purchasing the target product and gives a favorable review of the product, it means that the user has a good shopping experience with the target product, and the target product is recorded as a first-class product;

[0179] The products corresponding to the keywords other than the target products on the sales platform are recorded as second-category products;

[0180] Get the number of second-category goods, denoted by N;

[0181] Obtain sales data of N second-category products on the sales platform in the past year;

[0182] The sales data specifically refers to the sales volume and the number of favorable comments of the product;

[0183] Pick any second-category product;

[0184] Calculate the favorable review rate of these two categories of products;

[0185] The positive review rate is specifically the ratio of the number of positive reviews of a product to the number of sales;

[0186] Get the number of users who purchased the second category of goods more than or equal to 2 times in the past year;

[0187] Get the total number of users who purchased these two categories of goods in the past year;

[0188] Calculate the repurchase rate of these two categories of goods;

[0189] The repurchase rate is specifically the ratio of the number of users who have purchased a certain product more than twice to the total number of users who have purchased the product.

[0190] Calculate the praise rate and repurchase rate of N second-category products respectively.

[0191] The method of pushing the product to the user according to the first push strategy is as follows:

[0192] Create set A, set B and set C;

[0193] According to the sales quantity, the second category of goods are listed in set A from high to low;

[0194] According to the repurchase rate, the second category of goods are listed in set B from high to low;

[0195] According to the praise rate, the second category of products are listed in set C in descending order;

[0196] We have established sets A, B, and C to screen products based on sales volume, repurchase rate, and favorable comment rate. This multi-dimensional screening mechanism ensures that the products pushed to users are high-quality products that have been rigorously evaluated. Users can find not only products with high sales volume, but also products with good reputation in the recommendations they receive. This combination can better meet users' actual needs, thereby improving user satisfaction and purchase rate.

[0197] Create a set D;

[0198] If there is a category of products corresponding to the keyword in the target products;

[0199] List a category of target products corresponding to the keywords into set D;

[0200] If there is no product of the same category as the keyword in the target product, no processing will be done;

[0201] If there is no second-category product in set D, push the first, second, third, and tenth products in set A to set D;

[0202] Compare the first item in set B with the items in set D;

[0203] If the first item in set B does not exist in the items in set D, the first item in the target set is added to set D;

[0204] If the first product in set B already exists in the products in set D, then the second product in set B is selected and compared with the products in set D.

[0205] If the second item in set B does not exist in the items in set D, then the second item in set B is included in set D;

[0206] If the second product in set B already exists in the products in set D, then select the third product in set B and compare it with the products in set D.

[0207] If the third item in set B does not exist in the items in set D, then the third item in set B is included in set D;

[0208] If the third product in the target set does not exist in the products in set D, then select products in set B and compare them with the products in set D in turn until the number of products in set B included in set D is equal to 10;

[0209] If the number of commodities in set B included in set D is equal to 10, the commodities in set C are added to set D in sequence until the number of commodities in set C included in set D is equal to 10;

[0210] If there are two types of products in set D, the products in sets A, B and C are included in set D according to the product screening strategy;

[0211] The product screening strategy is specifically as follows:

[0212] Select a set at random and record it as the target set;

[0213] Compare the first item in the target set with the items in set D;

[0214] If the first item in the target set does not exist in the items in set D, then the first item in the target set is added to set D;

[0215] If the first product in the target set already exists in the products in set D, then the second product in the target set is selected and compared with the products in set D;

[0216] If the second item in the target set does not exist in the items in set D, the second item in the target set is added to set D;

[0217] If the second product in the target set already exists in the products in set D, then the third product in the target set is selected and compared with the products in set D.

[0218] If the third item in the target set does not exist in the items in set D, the third item in the target set is added to set D;

[0219] If the third product in the target set does not exist in the products in set D, then select products in the target set and compare them with the products in set D in turn until the number of products in the target set included in set D is equal to 10;

[0220] Push the products in set D to the user;

[0221] By analyzing the user's search keywords and historical purchase records, the products are divided into target products, Category I products and Category II products. Category II products are included in the collection based on their sales volume, praise rate and repurchase rate. The repurchase rate reflects the user's satisfaction and loyalty to the product, while the praise rate provides the user with direct feedback on the quality of the product. Category I products and Category II products in each collection are pushed to users according to the first push strategy. Through the first push strategy, the sales platform can give priority to recommending products that are both best-selling and well-received. This method not only improves the quality of recommended products, but also effectively reduces the probability of user dissatisfaction after purchase.

[0222] The obtaining of the user's browsing data of the product under the first push strategy is specifically as follows:

[0223] Get the average browsing time of each target product, and record the average as T1;

[0224] S1. Establish a keyword set;

[0225] S2. Select a product at random;

[0226] S3. Users who purchased this product within the past year are recorded as category 1 users;

[0227] S4. Randomly select a user of the first category, and after the user of the first category agrees to the authorization, obtain the text record of the communication between the user of the first category and the customer service when purchasing the product;

[0228] S5, extracting all keywords related to the product in the text record, and listing all keywords in a keyword set;

[0229] S6. If this type of user does not agree to the authorization, no processing will be done;

[0230] S7, perform S4-S6 operation steps for all users of the first category, and then the keyword set of this product is obtained;

[0231] Get the keyword set of all target products;

[0232] Randomly select a target product and obtain the number of different keywords in the keyword set corresponding to the target product, and record the number as X;

[0233] Obtain the text records of the user's communication with customer service when browsing this target product;

[0234] Extract all keywords related to the target product in the text record, and obtain the number of different keywords, which is recorded as Y;

[0235] Then the user's effective communication value for this target product = Y ÷ X;

[0236] Calculate the effective communication value of the user for each target product, and obtain the average value of the effective communication value of the user for all target products, which is recorded as T2;

[0237] Get the user's browsing time for each product in set D respectively;

[0238] Obtain the user's effective communication value for each product in set D respectively;

[0239] If there are products in set D;

[0240] The user's browsing time for this product is ≥ T1 and the user's effective communication value for this product is ≥ T2;

[0241] Record this product as a potential product;

[0242] Get the number of potential products in a category in set D;

[0243] Calculate the ratio of the number of potential products in a category to the number of products in set D;

[0244] The ratio is recorded as the first ratio;

[0245] After the user authorizes, by analyzing the communication records between the user and customer service, we can extract keywords related to the product and calculate the effective communication value; this indicator reflects the user's attention to and willingness to buy a certain product; by combining these data, the system can more accurately judge the user's purchasing intention, and thus push more accurate recommendations, avoiding interference from irrelevant products, improving the relevance of recommendations, and ultimately promoting sales.

[0246] The adjusted push strategy is recorded as the second push strategy, which is:

[0247] Setting a threshold Z. By setting the threshold Z, the system can determine whether to maintain the first push strategy or switch to the second push strategy according to the performance of the user's browsing data;

[0248] If the first ratio ≥ Z, the first push strategy is maintained to push the product to the user;

[0249] If the first ratio is less than Z, the second push strategy is executed, which is:

[0250] Get the high-frequency search terms on the sales platform in the past three days;

[0251] If there are high-frequency search terms that are the same as the user's search terms;

[0252] Then record this high-frequency search term as the target search term;

[0253] The products on the sales platform corresponding to the target search terms are recorded as three categories of products;

[0254] Get the number of items in set D, denoted by M;

[0255] Get the sales quantity of all three categories of goods in the past three days;

[0256] Create a set E;

[0257] According to sales quantity, the three categories of goods are listed in set E from largest to smallest;

[0258] Add the first, second, third, ...Mth items in set E to set F;

[0259] Push the products in collections F and D to the user.

[0260] The obtaining of the user's browsing data of the product under the second push strategy is specifically as follows:

[0261] Get the user's browsing time for each product in set F respectively;

[0262] Obtain the user's effective communication value for each product in set F respectively;

[0263] If there are products in set F;

[0264] The user's browsing time for this product is ≥ T1 and the user's effective communication value for this product is ≥ T2;

[0265] Record this product as a potential second-class product;

[0266] Get the number of potential products of the second category in set F;

[0267] Calculate the ratio of the number of potential products in the second category to the number of products in set F;

[0268] The ratio is recorded as the second ratio;

[0269] Based on the user's browsing data of products under the first push strategy, the user's purchase intention for the recommended products is monitored in real time. If the user does not complete the purchase, the system will collect new data and adjust the push strategy accordingly to generate a second push strategy. This dynamic adjustment mechanism enables the sales platform to flexibly respond to changes in user needs, thereby improving user engagement and satisfaction.

[0270] The push strategy is adjusted according to the user's browsing data of the product, specifically:

[0271] If the first ratio> the second ratio;

[0272] Then execute the first push strategy;

[0273] If the first ratio = the second ratio;

[0274] Then execute the second push strategy;

[0275] If the first ratio is less than the second ratio;

[0276] Then execute the third push strategy;

[0277] The third push strategy is specifically:

[0278] When pushing products to users, only push products in set F;

[0279] Based on the user's browsing data of goods under the second push strategy, determine whether the user is influenced by the high-frequency search terms on the sales platform when purchasing goods. If the user is influenced by the high-frequency search terms on the sales platform when purchasing goods and prefers goods corresponding to the high-frequency search terms, the third push strategy is executed. If the user has no preference, the first push strategy or the second push strategy is executed based on the browsing data. Through this comprehensive data analysis method, the recommendation results can better reflect user expectations, increase user shopping satisfaction, and thus improve the overall sales performance of the platform.

[0280] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants 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.

[0281] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A sales platform, characterized by: include: The search term entry module is used to obtain the keywords of the user's search terms when the user searches for products on the sales platform; The record acquisition module is used to obtain the user's historical purchase records in the past year; The data integration module is used to determine the first push strategy based on the user's historical purchase records in the past year and the products corresponding to the keywords on the sales platform; A data browsing module, used to obtain the browsing data of the user on the product under the first push strategy; Adjust the push module and determine whether the push strategy needs to be adjusted based on the browsing data of the user's historical purchase records in the past year.

2. A sales method based on the sales platform of claim 1, characterized in that: include; When users search for products on the sales platform; Get the keywords of the user's search terms; Obtain the user's historical purchase records in the past year; Obtain products corresponding to keywords on the sales platform; Determine the first push strategy based on the user's purchase history in the past year and the products corresponding to the keywords on the sales platform; Push products to users according to the first push strategy; Obtain the user's browsing data on products under the first push strategy; If the user completes the purchase of the product pushed under the first push strategy, it will no longer be pushed; If the user does not complete the purchase of the product pushed under the first push strategy; Combine the browsing data of the user's historical purchase records in the past year to determine whether the push strategy needs to be adjusted; If you need to adjust the push strategy; The adjusted push strategy is recorded as the second push strategy; Pushing products to users according to the second push strategy; Obtaining the user's browsing data on products under the second push strategy; If the user completes the purchase of the product pushed under the second push strategy, it will no longer be pushed; If the user does not complete the purchase of the product pushed under the second push strategy; Adjust push strategies based on users’ browsing data of products; Record the push strategy corresponding to the product that the user has completed purchasing as the user's primary push strategy; When a user searches for a product, the primary push strategy is executed first to push the product to the user.

3. The sales method of the sales platform according to claim 2, characterized in that: The first push strategy is determined based on the user's historical purchase records in the past year and the products corresponding to the keywords on the platform, specifically: The products in the user's historical purchase records in the past year are recorded as target products; Obtain after-sales data of target products; The after-sales data includes whether the user applies for after-sales service after completing the purchase of the product and the type of evaluation made, which includes positive and negative evaluations; If the user does not apply for after-sales service after completing the purchase of the target product and gives a favorable review of the product, the target product will be recorded as a first-class product; The products corresponding to the keywords other than the target products on the sales platform are recorded as second-category products; Get the number of second-category goods, denoted as N; Obtain sales data of N second-category products on the sales platform in the past year; The sales data specifically refers to the sales volume and the number of favorable comments of the product; Choose any second-category product; Calculate the favorable review rate of these two categories of products; The positive review rate is specifically the ratio of the number of positive reviews of a product to the number of sales; Get the number of users who purchased the second category of goods more than or equal to 2 times in the past year; Get the total number of users who purchased these two categories of goods in the past year; Calculate the repurchase rate of these two categories of goods; The repurchase rate is specifically the ratio of the number of users who have purchased a certain product more than twice to the total number of users who have purchased the product. Calculate the praise rate and repurchase rate of N second-category products respectively.

4. The sales method of the sales platform according to claim 2 or 3, characterized in that: The method of pushing the product to the user according to the first push strategy is as follows: Create set A, set B and set C; According to the sales quantity, the second category of goods are listed in set A from high to low; According to the repurchase rate, the second category of goods are listed in set B from high to low; According to the praise rate, the second category of products are listed in the collection C from high to low; Create a set D; If there is a category of products corresponding to the keyword in the target products; List a category of target products corresponding to the keywords into set D; If there is no product of the same category as the keyword in the target product, no processing will be done; If there is no second-category product in set D, push the first, second, third, and tenth products in set A to set D; Compare the first item in set B with the items in set D; If the first item in set B does not exist in the items in set D, the first item in the target set is added to set D; If the first product in set B already exists in the products in set D, then the second product in set B is selected and compared with the products in set D; If the second item in set B does not exist in the items in set D, then the second item in set B is included in set D; If the second product in set B already exists in the products in set D, then select the third product in set B and compare it with the products in set D; If the third item in set B does not exist in the items in set D, then the third item in set B is included in set D; If the third product in the target set does not exist in the products in set D, then select products in set B and compare them with the products in set D in turn until the number of products in set B included in set D is equal to 10; If the number of commodities in set B included in set D is equal to 10, the commodities in set C are added to set D in sequence until the number of commodities in set C included in set D is equal to 10; If there are two types of products in set D, the products in sets A, B and C are included in set D according to the product screening strategy; The product screening strategy is specifically as follows: Select a set at random and record it as the target set; Compare the first item in the target set with the items in set D; If the first item in the target set does not exist in the items in set D, then the first item in the target set is added to set D; If the first product in the target set already exists in the products in set D, then the second product in the target set is selected and compared with the products in set D; If the second item in the target set does not exist in the items in set D, the second item in the target set is added to set D; If the second product in the target set already exists in the products in set D, then the third product in the target set is selected and compared with the products in set D. If the third item in the target set does not exist in the items in set D, the third item in the target set is added to set D; If the third product in the target set does not exist in the products in set D, then select products in the target set and compare them with the products in set D in turn until the number of products in the target set included in set D is equal to 10; Push the products in set D to the user.

5. The sales method of the sales platform according to claim 4, characterized in that: The obtaining of the user's browsing data of the product under the first push strategy is specifically as follows: Get the average browsing time of each target product, and record the average as T1; S1. Establish a keyword set; S2. Select a product at random; S3. Users who purchased this product within the past year are recorded as category 1 users; S4. Randomly select a user of the first category, and after the user of the first category agrees to the authorization, obtain the text record of the communication between the user of the first category and the customer service when purchasing the product; S5, extracting all keywords related to the product in the text record, and listing all keywords in a keyword set; S6. If this type of user does not agree to the authorization, no processing will be done; S7, perform S4-S6 operation steps for all users of the first category, and then the keyword set of this product is obtained; Get the keyword set of all target products; Randomly select a target product and obtain the number of different keywords in the keyword set corresponding to the target product, and record the number as X; Obtain the text records of the user's communication with customer service when browsing this target product; Extract all keywords related to the target product in the text record, and obtain the number of different keywords, which is recorded as Y; Then the user's effective communication value for this target product = Y ÷ X; Calculate the effective communication value of the user for each target product, and obtain the average value of the effective communication value of the user for all target products, which is recorded as T2; Get the user's browsing time for each product in set D respectively; Obtain the user's effective communication value for each product in set D respectively; If there are products in set D; The user's browsing time for this product is ≥ T1 and the user's effective communication value for this product is ≥ T2; Record this product as a potential product; Get the number of potential products in a category in set D; Calculate the ratio of the number of potential products in a category to the number of products in set D; The ratio is recorded as the first ratio.

6. The sales method of the sales platform according to claim 5, characterized in that: The adjusted push strategy is recorded as the second push strategy, which is: Set the threshold Z; If the first ratio ≥ Z, the first push strategy is maintained to push the product to the user; If the first ratio is less than Z, the second push strategy is executed, which is: Get the high-frequency search terms on the sales platform in the past three days; If there are high-frequency search terms that are the same as the user's search terms; Then this high-frequency search term is recorded as the target search term; The products on the sales platform corresponding to the target search terms are recorded as three categories of products; Get the number of items in set D, denoted by M; Get the sales quantity of all three categories of goods in the past three days; Create a set E; According to sales quantity, the three categories of goods are listed in set E from largest to smallest; Add the first, second, third, ..., Mth items in set E to set F; Push the products in collections F and D to the user.

7. The sales method of the sales platform according to claim 6, characterized in that: The obtaining of the user's browsing data of the product under the second push strategy is specifically as follows: Get the user's browsing time for each product in set F respectively; Obtain the user's effective communication value for each product in set F respectively; If there are products in set F; The user's browsing time for this product is ≥ T1 and the user's effective communication value for this product is ≥ T2; Record this product as a potential second-class product; Get the number of potential products of the second category in set F; Calculate the ratio of the number of potential products in the second category to the number of products in set F; The ratio is recorded as the second ratio.

8. The sales method of the sales platform according to claim 7, characterized in that: The push strategy is adjusted according to the user's browsing data of the product, specifically: If the first ratio> the second ratio; Then execute the first push strategy; If the first ratio = the second ratio; Then execute the second push strategy; If the first ratio is less than the second ratio; Then execute the third push strategy; The third push strategy is specifically: When pushing products to users, only the products in set F are pushed.

Images