CN115170253B - Commodity information pushing method and device in sales promotion activities - Google Patents
Commodity information pushing method and device in sales promotion activities Download PDFInfo
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Abstract
The embodiment of the invention provides a method and a device for pushing commodity information in promotion activities, wherein the method comprises the following steps: determining a preferred trademark/preferred type, a preferred necessity and a user purchasing power range of the user based on the historical order; establishing a preference function according to the consumption amount and the promotion amplitude of the goods with the preference trademark/preference type, and calculating a first recommendation score of the promoted goods in the promotion activity at the time by combining the promotion amplitude of the preference trademark/preference type in the promotion activity at the time; acquiring consumption records of the latest preference necessities of the user in the historical order, and determining a second recommendation score of the user in the current sales promotion activity; and adjusting the recommended scores according to the commodity price standard line to obtain the total commodity recommended scores in the sales promotion activity, and determining the priority and the pushing frequency of commodity information pushing based on the total commodity recommended scores. By adopting the method, more targeted and more accurate commodity recommendation can be obtained for the target user.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a method and a device for pushing commodity information in sales promotion activities.
Background
With the increasing adaptation of users to purchase goods on the internet, the e-commerce platform is also developed vigorously in China at present, and more sales promotion activities such as 618, twenty-one and twenty-two are provided to match with various sales promotion activities of merchants, so that more and more users purchase goods on the e-commerce platform in the sales promotion activities, and the e-commerce platform is convenient for users and also promotes the development of the e-commerce platform.
However, in the prior art, in each sales promotion activity, various merchants of the transaction platform have various sales promotion activities, different commodities of the same merchant also have different sales promotion activities, and it is troublesome for the buyer to find the goods to be purchased.
Disclosure of Invention
Aiming at the problems in the prior art, the embodiment of the invention provides a method and a device for pushing commodity information in promotion activities.
The embodiment of the invention provides a method for pushing commodity information in promotion activities, which comprises the following steps:
acquiring historical orders of a target user in historical promotion activities on a trading platform, acquiring order keywords in the historical orders, and determining a preferred trademark/preferred type, a preferred requisite and a user purchasing power range of the target user according to the order keywords;
acquiring the consumption amount and the corresponding promotion amplitude of the target user for the goods with the preference trademark/preference type in the historical order, calculating a preference function of the target user for the preference trademark/preference type according to the consumption amount and the corresponding promotion amplitude, and calculating a first recommendation score of the promotion goods with the preference trademark/preference type in the promotion activity according to the promotion amplitude of the promotion goods with the preference trademark/preference type in the promotion activity;
acquiring a consumption record of the preference necessities of the target user in the historical order, calculating the residual service life of the preference necessities according to the consumption record, and calculating a second recommendation score of the preference necessities according to the residual service life and by combining a preset correlation function between the service life of the goods and the recommendation score;
determining a commodity price standard line of a target user according to the purchasing power range of the user, comparing the promotion commodities with the preference trademarks/preference types and the preference necessities with the commodity price standard line, determining corresponding adjusting weights according to comparison results, and adjusting the corresponding first recommendation scores and second recommendation scores according to the adjusting weights to obtain total commodity recommendation scores in the promotion activity;
and adjusting the commodity information pushing priority and the pushing frequency of the target user during the sales promotion activity based on the total commodity recommendation score.
In one embodiment, the method further comprises:
acquiring time corresponding to the promotion amplitude of the promotion commodities in the promotion activity, generating a promotion activity time axis, and generating a goods pre-purchase time axis of the user by combining the preference function;
when the actual shopping record of the target user for the goods with the preference trademark/preference type in the current sales promotion activity is different from the goods pre-shopping time axis and the corresponding difference amount is larger than a preset threshold value, generating the preference weight of the preference trademark/preference type of the target user according to the difference amount, and adjusting the first recommendation score of the sales promotion goods with the preference trademark/preference type through the preference weight.
In one embodiment, the method further comprises:
acquiring an actual shopping record of the target user for the preference necessities in the sales promotion activity, and generating corresponding similar goods adjusting weights based on the goods types and the goods quantity in the actual shopping record of the preference necessities;
and adjusting a second recommendation score of preference necessities of the same type as the goods type based on the same kind goods adjusting weight.
In one embodiment, the method further comprises:
acquiring user order big data in historical promotion activities of a transaction platform, wherein the method comprises the following steps: the method comprises the steps of determining a user order total, an order goods type and an order goods amount, and determining a corresponding user consumption level according to the user order total;
deleting abnormal order goods amount in the order goods type, and calculating a commodity price standard line corresponding to the user consumption level based on the order goods type and the order goods amount of the user in the user consumption level;
the step of determining the commodity price standard line of the target user according to the user purchasing power range comprises the following steps:
and determining the user consumption grade of the target user according to the user purchasing power range, and further determining a corresponding commodity price standard line.
In one embodiment, the method further comprises:
the consumption record comprises the purchase quantity and the purchase time of the preference necessities;
calculating the service life of the preference necessities by combining the average product life of the preference necessities based on the purchase quantity;
calculating a remaining useful life of the preference requisite based on the purchase time.
In one embodiment, the method further comprises:
acquiring a user consumption record in a preset time period before the promotion activity, and detecting whether the user consumption record is larger than a preset consumption threshold value, wherein the preset consumption threshold value is correspondingly set according to the user purchasing power range;
and when the user consumption record is larger than a preset consumption threshold value, reducing the purchasing power range of the user.
The embodiment of the invention provides a commodity information pushing device in promotion activities, which comprises:
the acquisition module is used for acquiring historical orders of a target user in historical promotional activities on a trading platform, acquiring order keywords in the historical orders, and determining preferred trademark/preferred type, preferred necessities and user purchasing power range of the target user according to the order keywords;
the first calculation module is used for acquiring the consumption amount and the corresponding promotion amplitude of the target user for the goods with the preference trademark/preference type in the historical order, calculating a preference function of the target user for the preference trademark/preference type according to the consumption amount and the corresponding promotion amplitude, and calculating a first recommendation score of the promotion goods with the preference trademark/preference type in the promotion activity according to the promotion amplitude of the promotion goods with the preference trademark/preference type in the promotion activity;
the second calculation module is used for acquiring the consumption record of the preference necessities of the target user in the historical order, calculating the residual service life of the preference necessities according to the consumption record, and calculating a second recommendation score of the preference necessities according to the residual service life and by combining a preset correlation function between the service life of the goods and the recommendation score;
the adjusting module is used for determining a commodity price standard line of a target user according to the purchasing power range of the user, comparing the promotion commodities with the preference trademarks/preference types and the preference necessities with the commodity price standard line, determining a corresponding adjusting weight according to a comparison result, and adjusting the corresponding first recommendation score and the second recommendation score according to the adjusting weight to obtain a total commodity recommendation score in the promotion activity;
and the pushing module is used for adjusting the commodity information pushing priority and the pushing frequency of the target user during the sales promotion activity based on the total commodity recommendation score.
In one embodiment, the apparatus further comprises:
the second acquisition module is used for acquiring the time corresponding to the promotion amplitude of the promotion commodities in the promotion activity, generating a promotion activity time axis and generating a goods pre-purchase time axis of the user by combining the preference function;
and the second adjusting module is used for generating a preference weight of the preference trademark/preference type of the target user according to the difference amount when the actual shopping record of the target user for the goods with the preference trademark/preference type in the current promotion activity is different from the goods pre-purchase time axis and the corresponding difference amount is greater than a preset threshold value, and adjusting the first recommendation score of the promotion goods with the preference trademark/preference type according to the preference weight.
The embodiment of the invention provides electronic equipment, which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the program to realize the steps of the commodity information pushing method in the promotion activities.
An embodiment of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the method for pushing information about goods in a promotion event.
The commodity information pushing method and device in the sales promotion activities, provided by the embodiment of the invention, are used for acquiring historical orders of target users in historical sales promotion activities on a trading platform, acquiring order keywords in the historical orders, and determining preferred trademarks/preferred types, preferred necessities and user purchasing power ranges of the target users according to the order keywords; acquiring the consumption amount and the corresponding promotion amplitude of the target user for the goods with the preferred trademark/preferred type in the historical order, calculating a preference function of the target user for the preferred trademark/preferred type according to the consumption amount and the corresponding promotion amplitude, and calculating a first recommendation score of the promotion goods with the preferred trademark/preferred type in the promotion activity according to the promotion amplitude of the promotion goods with the preferred trademark/preferred type in the promotion activity; acquiring a consumption record of the target user's latest preference necessities in the historical order, calculating the remaining service life of the preference necessities according to the consumption record, and calculating a second recommendation score of the preference necessities according to the remaining service life and by combining a preset correlation function between the service life of the goods and the recommendation score; determining a commodity price standard line of a target user according to the purchasing power range of the user, comparing the promotion commodities with the preferred trademarks/preferred types and the preferred necessities with the commodity price standard line, determining a corresponding adjusting weight according to the comparison result, and adjusting the corresponding first recommendation score and second recommendation score according to the adjusting weight to obtain a total commodity recommendation score in the promotion activity; and based on the total commodity recommendation score, adjusting the commodity information push priority and push frequency of the target user in the sales promotion activity. Therefore, the goods purchasing demand of the user can be determined based on the preference and the necessities of the user, the goods purchasing demand is integrally regulated and controlled through the purchasing power of the user, the demand score of goods is generated, and accordingly more targeted and more accurate commodity recommendation is obtained.
Drawings
In order to more clearly illustrate the embodiments or technical solutions of the present invention, the drawings used in the embodiments or technical solutions in the prior art are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flowchart illustrating a method for pushing merchandise information during a promotion event according to an embodiment of the present invention;
FIG. 2 is a block diagram of an apparatus for pushing merchandise information during a promotion event according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device in an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flow chart of a method for pushing commodity information in a promotional event according to an embodiment of the present invention, and as shown in fig. 1, the method for pushing commodity information in a promotional event according to an embodiment of the present invention includes:
step S101, obtaining a historical order of a target user in historical promotion activities on a trading platform, obtaining order keywords in the historical order, and determining a preferred trademark/preferred type, a preferred necessity and a user purchasing power range of the target user according to the order keywords.
Specifically, historical sales promotion activities of target users needing to carry out commodity information pushing in the past year on a trading platform are obtained, for example, historical orders in 618, twenty-one and twenty-two sales promotion activities are obtained, and order keywords corresponding to the users in the historical orders are obtained, wherein the order keywords can be various same-brand articles and quantities purchased by the users, various same-type articles and quantities, various necessities (various living goods such as tissues, bathing goods and the like), and the total consumption amount of each sales promotion activity. Then, according to the articles and the quantity of various trademarks purchased by the user, the preferred trademark/preferred type of the user can be determined according to the various articles and the quantity of various trademarks, for example, the user likes to purchase the preferred trademarks such as plum, nike and the like in a historical order, most of the preferred trademarks are the trademarks favored by the user, for example, the preferred types of the preferred trademarks are various earrings, various fishing gears, various handcrafts and the like, and most of the preferred trademarks/preferred types are related to the interests and hobbies of the user, so that the preferred trademark/preferred type of the user is determined; generally speaking, some types of necessities are used by users to purchase on a trading platform, and some types of necessities are used by supermarkets to purchase, so that preferred necessities preferred by users to purchase on the trading platform are determined according to historical order records of various necessities; and determining the purchasing power range of the user according to the floating interval of the total consumption amount of each promotion activity.
Step S102, the consumption amount of the target user on the goods with the preferred trademark/preferred type and the corresponding promotion amplitude in the historical order are obtained, the preference function of the target user on the preferred trademark/preferred type is calculated according to the consumption amount and the corresponding promotion amplitude, and the first recommendation score of the promotion goods with the preferred trademark/preferred type in the promotion activity is calculated according to the promotion amplitude of the promotion goods with the preferred trademark/preferred type in the promotion activity.
Specifically, the consumption amount and the corresponding promotion amplitude of each order of the goods with the preferred trademark/preferred type by the target user in the historical order are obtained, and a corresponding data set is generated, wherein the data set can comprise: "nike": (698 yuan, 7 folds), (1298 yuan, 5.5 folds) \ 8230; "plum ning": the data of (398 yuan, 6 folds), (598 yuan, 6.5 folds) \ 8230, and the like, according to the preference trademark/preference type of the user, the preference function relationship of the user under the preference trademark/preference type is calculated, such as the preference function relationship of the user under the ' nike ' condition and the preference function relationship of the user under the ' leining condition, wherein the calculation method of the preference function relationship is determined according to the shopping habits of the user, some users are linear function relationships, some users are nonlinear function relationships, but both the function relationships follow the following conditions: the larger the promotion amplitude is, the larger the consumption amount of the user is, by combining with the purchase data set of the user in the historical order, drawing a shopping curve of the user so as to determine a preference function relationship of the user, and then by combining with the promotion amplitude of the promotion goods with the preference trademark/preference type in the promotion activity, determining a corresponding first recommendation score according to the difference between the promotion amplitude of the promotion goods and the corresponding preference function relationship, for example, when the promotion amplitude of the promotion goods is on a function curve corresponding to the preference function relationship, the first recommendation score is 100, and when the promotion amplitude is reduced, the first recommendation score is correspondingly reduced.
Step S103, obtaining a consumption record of the preference necessities of the target user in the history order, calculating the remaining service life of the preference necessities according to the consumption record, and calculating a second recommendation score of the preference necessities according to the remaining service life and by combining a preset correlation function between the service life of the goods and the recommendation score.
Specifically, a consumption record of the target user's last preferred necessities in the historical order is obtained, where the consumption record may include a purchase quantity and a purchase time of the preferred necessities, for example, if the user purchases two boxes of paper towels and two boxes of shower gel at 2022 year 618, then based on the purchase quantity, the service life of the preferred necessities purchased last time by the user is calculated in combination with the average product life of the preferred necessities, and then when the current sales promotion activity is determined according to the purchase time, the corresponding remaining service life of the preferred necessities is calculated, for example, when the paper towels reach the service life, the corresponding second recommendation score is 100 for all the paper towels, and the shower gel does not reach, and then according to the remaining service life, the corresponding correlation function is determined according to the type of the necessities, for example, when the remaining service life is 10% of the total service life, the corresponding 10% of the second recommendation score may be deducted, for example, 90 minutes.
And step S104, determining a commodity price standard line of a target user according to the purchasing power range of the user, comparing the promotion commodities with the preference trademarks/preference types and the preference necessities with the commodity price standard line, determining a corresponding adjusting weight according to a comparison result, and adjusting the corresponding first recommendation score and second recommendation score according to the adjusting weight to obtain the total commodity recommendation score in the promotion activity.
Specifically, user order big data in historical promotion activities in each trading platform is obtained, wherein the user order big data may include: the method comprises the steps of determining a corresponding user consumption grade according to the user order total, such as dividing the user order total in a sales promotion activity into a first grade with the user order total being less than 1000, a second grade with the user order total being 1000 to 5000, a third grade with the user order total being 5000 to 10000, a fourth grade with the user order total being 10000 to 50000 and the like, and then deleting abnormal order goods amount in the order goods type, wherein the abnormal order goods amount is specific to abnormal amount of a certain grade, such as customers in the second grade of 1000 to 5000, and the price is normally selected to be 300 yuan to 15000 yuan when purchasing shoes, and for customers in the second grade, order data which is far more than 1500 yuan, such as 3000 yuan, or far less than 300 yuan, such as 50 yuan (abnormal order goods amount) appears when purchasing shoes (order types), calculating commodity price standard lines corresponding to the user consumption level based on the user order commodity type and the order commodity amount in the user consumption level, wherein the specific calculation method comprises but is not limited to a calculation method combining a median, a mean, a variance and a standard deviation, in addition, the commodity price standard lines can be not only fixed values, but also a certain data range, then comparing sales promotion commodities and necessities with preferred trademarks/preferred types with the corresponding commodity price standard lines, and determining corresponding adjustment weights according to the price difference between the prices of the sales promotion commodities and the preferred necessities and the commodity price standard lines in the comparison result, for example, when the price difference is basically 0, the corresponding adjustment weight is 1, and when a certain price difference exists, the corresponding adjustment weight is determined according to the ratio of the price difference to the commodity price standard lines, for example, when the price difference is 20% of the product price standard line, the corresponding adjustment weight may be 0.8, and the corresponding first recommendation score and the second recommendation score are adjusted according to the corresponding weights to obtain the total product recommendation score of all the products in the current sales promotion activity, for example, in step S104, the corresponding second recommendation score is 100 for all the tissues, but the corresponding product price standard line is 150 yuan/box to 200 yuan/box for the target user, the paper towel price is the paper towel a in 150 yuan/box to 200 yuan/box, the corresponding adjustment weight is 1, the recommendation of the paper towel a in the total product recommendation score is 100, the paper towel price is the paper towel a in 300 yuan/box, the corresponding adjustment weight is 0.5, and the recommendation of the paper towel B in the total product recommendation score is 50.
And step S105, based on the total commodity recommendation score, adjusting the commodity information push priority and push frequency of the target user in the current promotion activity.
Specifically, after total commodity recommendation scores of the target user for all commodities (preferred trademarks/preferred types and preferred necessities) are obtained, the commodity information pushing priority and the pushing frequency of the target user during the current sales promotion activity are adjusted according to the total commodity recommendation scores and in combination with a preset pushing algorithm of a trading platform.
In addition, user consumption records in a preset time period before the current promotion activity are obtained, and whether the user consumption records are larger than a preset consumption threshold value or not is detected, wherein the preset time period can be correspondingly set according to a consumption cycle of the user, the preset consumption threshold value is correspondingly set according to a user purchasing power range, for example, if the user carries out online shopping for two months, the preset time period can be one month before the promotion activity, the user purchasing power range is 15000 yuan to 20000 yuan, the corresponding threshold value can be 30% of the upper limit of the user purchasing power range, for example, if the total value of commodities purchased by the user in the previous month of twenty-one exceeds 6000 yuan, the user purchasing power range is correspondingly reduced, the reduction range is correspondingly set according to the specific total consumption amount of the user in the previous month of twenty-one, and generally, the higher the total consumption amount is, the more numerical values are reduced.
The commodity information pushing method in the sales promotion activities, provided by the embodiment of the invention, comprises the steps of obtaining historical orders of target users in historical sales promotion activities on a trading platform, obtaining order keywords in the historical orders, and determining preferred trademarks/preferred types, preferred necessities and user purchasing power ranges of the target users according to the order keywords; acquiring the consumption amount and the corresponding promotion amplitude of the target user for the goods with the preference brand/preference type in the historical order, calculating a preference function of the target user for the preference brand/preference type according to the consumption amount and the corresponding promotion amplitude, and calculating a first recommendation score of the promotion goods with the preference brand/preference type in the promotion activity according to the promotion amplitude of the promotion goods with the preference brand/preference type in the promotion activity; acquiring a consumption record of the target user's preference of the necessities in the historical order, calculating the residual service life of the preference necessities according to the consumption record, and calculating a second recommendation score of the preference necessities according to the residual service life and by combining a preset correlation function between the service life of the goods and the recommendation score; determining a commodity price standard line of a target user according to the purchasing power range of the user, comparing the promotion commodities with the preferred trademarks/preferred types and the preferred necessities with the commodity price standard line, determining a corresponding adjusting weight according to the comparison result, and adjusting the corresponding first recommendation score and second recommendation score according to the adjusting weight to obtain a total commodity recommendation score in the promotion activity; and based on the total commodity recommendation score, adjusting the commodity information push priority and push frequency of the target user in the sales promotion activity. Therefore, the goods purchasing demand of the user can be determined based on the preference and the necessities of the user, the goods purchasing demand is integrally regulated and controlled through the purchasing power of the user, the demand score of goods is generated, and accordingly more targeted and more accurate commodity recommendation is obtained.
On the basis of the above embodiment, the method for pushing commodity information in a promotion activity further includes:
acquiring time corresponding to the promotion amplitude of the promotion commodities in the promotion activity, generating a promotion activity time axis, and generating a goods pre-purchase time axis of the user by combining the first recommendation score of the promotion commodities;
when the actual shopping record of the target user for the goods with the preference trademark/preference type in the current sales promotion activity is different from the goods pre-shopping time axis and the corresponding difference amount is larger than a preset threshold value, generating the preference weight of the preference trademark/preference type of the target user according to the difference amount, and adjusting the first recommendation score of the sales promotion goods with the preference trademark/preference type through the preference weight.
In the embodiment of the invention, because of the continuity of the promotion activity, the time corresponding to the promotion amplitude in the promotion activity is acquired, a promotion activity time line is generated, for example, a one-time twenty-one promotion activity, which usually lasts for one month, and the promotion activities in each day in one month are different, then according to the promotion activity time line, in combination with the preference function of the target user for the preference trademark/preference type, a pre-purchase time line for the goods of the preference trademark/preference type by the user is generated, for example, on the first day of the promotion activity, the promotion activity of the preference trademark "nike" of the user exists, then the user is expected to purchase the goods of the "nike" on the first day, the consumption amount is about XX yuan, on the 15 th day of the promotion activity, the promotion activity of the preference type "earring" of the user exists, and the consumption amount is about XX yuan.
Then obtaining the difference between the actual shopping record of the goods with the preference trademark/preference type and the goods pre-shopping time axis after the promotion activity of the user is started, and when the difference exists and the difference amount is larger than a preset threshold value, it indicates that the preference degree of the user for the preference trademark/preference type in the promotion activity of the user is changed, wherein the preset threshold value can be correspondingly set according to the purchase amount of the historical promotion activity with the preference trademark/preference type, a preference weight of the preference trademark/preference type of the user is generated according to the difference amount, for example, the difference amount is 50% of the purchase amount of the historical promotion activity with the preference trademark/preference type, the weight can be set to 0.5, then a first recommendation score of the goods with the corresponding preference trademark/preference type is adjusted according to the preference weight, for example, after the user purchases the goods with the "nike" on the first day, the preference weight of the "nike" is calculated, and then for the promotion activity with the "nike" on the day 15 ", the first recommendation score of the corresponding goods with the original recommendation score is the corresponding preference recommendation score multiplied by the preference score so as to be the corresponding preference recommendation score.
In this embodiment, when it is detected that the actual shopping record differs from the pre-shopping time axis of the goods, the first recommendation score of the sales promotion product of the preference trademark/preference type is adjusted in time, so that more accurate pushing of the goods information can be provided in a period of long-term sales promotion activity, such as twenty-one that lasts for one month, in a subsequent sales promotion period.
On the basis of the above embodiment, the method for pushing commodity information in a promotion activity further includes:
acquiring an actual shopping record of the target user for the preference necessities in the current promotion activity, and generating corresponding similar goods adjusting weights based on the goods types and the goods quantity in the actual shopping record of the preference necessities;
adjusting a second recommendation score for preference necessities of the same type as the category of the good based on the category good adjustment weight.
In the embodiment of the invention, the actual shopping record of the target user for the goods with preference for the necessities in the sales promotion activity is obtained, after the target user carries out shopping, the corresponding adjustment weight of the same goods is generated according to the goods types and the goods quantity in the actual shopping record, when the goods quantity is more, the adjustment weight of the same goods with the corresponding goods types is smaller, for example, the user buys 2 boxes of paper towels in the first day of the sales promotion activity, the adjustment weight of the same goods with the goods type of 'paper towels' is generated according to the quantity of the 2 boxes of paper towels, for example, the adjustment weight is 0.2, and then the second recommendation score of the preference necessities with the same types as the goods types is adjusted based on the adjustment weight of the same goods, namely the second recommendation scores of the preference necessities with the same goods types need to be adjusted through the adjustment weight of the same goods.
In this embodiment, after it is detected that the target user has an actual shopping record for the preference necessities in the current sales promotion activity, the recommendation scores of the preference necessities of the same type are adjusted in time, so that more accurate commodity information push can be provided in a subsequent sales promotion time period in a long-time sales promotion activity, such as twenty-one that lasts for one month.
Fig. 2 is a device for pushing information of commodities in a promotional event according to an embodiment of the present invention, including: the system comprises an acquisition module S201, a first calculation module S202, a second calculation module S203, an adjustment module S204 and a push module S205, wherein:
the acquisition module S201 is used for acquiring a historical order of a target user in a historical promotion activity on a trading platform, acquiring an order keyword in the historical order, and determining a preferred trademark/preferred type, a preferred necessity and a user purchasing power range of the target user according to the order keyword.
The first calculating module S202 is configured to obtain a consumption amount of the target user for the goods of the preferred trademark/preferred type and a corresponding promotion amplitude in the historical order, calculate a preference function of the target user for the preferred trademark/preferred type according to the consumption amount and the corresponding promotion amplitude, and calculate a first recommendation score of the promotional goods of the preferred trademark/preferred type in the current promotional activity in combination with the promotion amplitude of the promotional goods of the preferred trademark/preferred type in the current promotional activity.
The second calculating module S203 is configured to obtain a consumption record of a favorite requirement of the target user in the history order last time, calculate a remaining service life of the favorite requirement according to the consumption record, and calculate a second recommendation score of the favorite requirement according to the remaining service life and by combining a preset correlation function between the cargo life and the recommendation score.
The adjusting module S204 is used for determining a commodity price standard line of a target user according to the purchasing power range of the user, comparing the promotion commodities with the preference trademarks/preference types and the preference necessities with the commodity price standard line, determining a corresponding adjusting weight according to a comparison result, and adjusting the corresponding first recommendation score and the second recommendation score according to the adjusting weight to obtain a total commodity recommendation score in the promotion activity.
The pushing module S205 is configured to adjust, based on the total commodity recommendation score, a priority and a pushing frequency of commodity information pushing of the target user during the current sales promotion activity.
In one embodiment, the apparatus may further comprise:
and the second acquisition module is used for acquiring the time corresponding to the promotion amplitude of the promotion commodities in the promotion activity, generating a promotion activity time axis and generating a goods pre-purchase time axis of the user by combining the preference function.
And the second adjusting module is used for generating a preference weight of the preference trademark/preference type of the target user according to the difference amount when the difference exists between the actual shopping record of the target user for the goods with the preference trademark/preference type and a goods pre-shopping time axis in the current sales promotion activity and the corresponding difference amount is larger than a preset threshold value, and adjusting the first recommendation score of the sales promotion goods with the preference trademark/preference type according to the preference weight.
For specific limitations of the merchandise information pushing device in the promotion activity, reference may be made to the above limitations on the merchandise information pushing method in the promotion activity, and details thereof are not described herein. The modules in the goods information pushing device in the promotion event can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
Fig. 3 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 3: a processor (processor) 301, a memory (memory) 302, a communication Interface (Communications Interface) 303 and a communication bus 304, wherein the processor 301, the memory 302 and the communication Interface 303 are configured to communicate with each other via the communication bus 304. The processor 301 may call logic instructions in the memory 302 to perform the following method: acquiring historical orders of target users in historical sales promotion activities on a trading platform, acquiring order keywords in the historical orders, and determining preferred trademarks/preferred types, preferred necessities and user purchasing power ranges of the target users according to the order keywords; acquiring the consumption amount and the corresponding promotion amplitude of the target user for the goods with the preferred trademark/preferred type in the historical order, calculating a preference function of the target user for the preferred trademark/preferred type according to the consumption amount and the corresponding promotion amplitude, and calculating a first recommendation score of the promotion goods with the preferred trademark/preferred type in the promotion activity according to the promotion amplitude of the promotion goods with the preferred trademark/preferred type in the promotion activity; acquiring a consumption record of the target user's latest preference necessities in the historical order, calculating the remaining service life of the preference necessities according to the consumption record, and calculating a second recommendation score of the preference necessities according to the remaining service life and by combining a preset correlation function between the service life of the goods and the recommendation score; determining a commodity price standard line of a target user according to the purchasing power range of the user, comparing the promotion commodities with the preferred trademarks/preferred types and the preferred necessities with the commodity price standard line, determining a corresponding adjusting weight according to the comparison result, and adjusting the corresponding first recommendation score and second recommendation score according to the adjusting weight to obtain a total commodity recommendation score in the promotion activity; and based on the total commodity recommendation score, adjusting the commodity information push priority and push frequency of the target user in the sales promotion activity.
Furthermore, the logic instructions in the memory 302 may be implemented in software functional units and stored in a computer readable storage medium when sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk, and various media capable of storing program codes.
In another aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented to perform the transmission method provided in the foregoing embodiments when executed by a processor, for example, the method includes: acquiring historical orders of target users in historical sales promotion activities on a trading platform, acquiring order keywords in the historical orders, and determining preferred trademarks/preferred types, preferred necessities and user purchasing power ranges of the target users according to the order keywords; acquiring the consumption amount and the corresponding promotion amplitude of the target user for the goods with the preference brand/preference type in the historical order, calculating a preference function of the target user for the preference brand/preference type according to the consumption amount and the corresponding promotion amplitude, and calculating a first recommendation score of the promotion goods with the preference brand/preference type in the promotion activity according to the promotion amplitude of the promotion goods with the preference brand/preference type in the promotion activity; acquiring a consumption record of the target user's latest preference necessities in the historical order, calculating the remaining service life of the preference necessities according to the consumption record, and calculating a second recommendation score of the preference necessities according to the remaining service life and by combining a preset correlation function between the service life of the goods and the recommendation score; determining a commodity price standard line of a target user according to the purchasing power range of the user, comparing the promotion commodities with the preferred trademarks/preferred types and the preferred necessities with the commodity price standard line, determining a corresponding adjusting weight according to the comparison result, and adjusting the corresponding first recommendation score and second recommendation score according to the adjusting weight to obtain a total commodity recommendation score in the promotion activity; and adjusting the commodity information push priority and push frequency of the target user during the sales promotion activity based on the total commodity recommendation score.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. A method for pushing commodity information in promotion activities is characterized by comprising the following steps:
acquiring a historical order of a target user in historical promotion activities on a trading platform, acquiring order keywords in the historical order, and determining a preferred trademark/preferred type, a preferred necessity and a user purchasing power range of the target user according to the order keywords;
acquiring the consumption amount and the corresponding promotion amplitude of the target user for the goods with the preferred trademark/preferred type in the historical order, calculating a preference function of the target user for the preferred trademark/preferred type according to the consumption amount and the corresponding promotion amplitude, and calculating a first recommendation score of the promotion goods with the preferred trademark/preferred type in the promotion activity according to the promotion amplitude of the promotion goods with the preferred trademark/preferred type in the promotion activity;
acquiring a consumption record of the latest preference necessities of the target user in the historical order, calculating the remaining service life of the preference necessities according to the consumption record, and calculating a second recommendation score of the preference necessities according to the remaining service life and by combining a preset correlation function between the service life of the goods and the recommendation score, wherein the correlation function is determined according to the type of the preference necessities;
determining a commodity price standard line of a target user according to the user purchasing power range, comparing the promotion commodity with the preference trademark/preference type and the preference necessities with the commodity price standard line, determining a corresponding adjusting weight according to a comparison result, and adjusting a corresponding first recommendation score and a corresponding second recommendation score according to the adjusting weight to obtain a total commodity recommendation score in the promotion activity;
based on the total commodity recommendation score, adjusting the commodity information pushing priority and the pushing frequency of the target user in the current sales promotion activity;
the calculating a preference function of the target user for the preferred trademark/preferred type according to the consumption amount and the corresponding promotion amplitude, and calculating a first recommendation score of the promotion commodity of the preferred trademark/preferred type in the promotion activity according to the promotion amplitude of the promotion commodity of the preferred trademark/preferred type in the promotion activity, wherein the calculation comprises the following steps:
acquiring a preset function rule, calculating a preference function of the target user for the preferred trademark/preferred type by combining with order data in the historical order, determining a corresponding first recommendation score by combining with the promotion amplitude of the promotion commodity with the preferred trademark/preferred type in the promotion activity, and according to the difference between the promotion amplitude of the promotion commodity and the corresponding preference function relationship, wherein the preset function rule comprises the following steps: the larger the promotion amplitude is, the larger the user consumption amount is;
calculating the remaining service life of the preference necessities according to the consumption record, comprising:
the consumption record comprises the purchase quantity and the purchase time of the preference necessities;
calculating the service life of the preference necessities by combining the average product life of the preference necessities based on the purchase quantity;
calculating a remaining useful life of the preference requisite based on the purchase time;
the method further comprises the following steps:
acquiring user order big data in historical promotion activities of a trading platform, comprising the following steps: the method comprises the steps of determining a user order total amount, an order goods type and an order goods amount, and determining a corresponding user consumption level according to the user order total amount;
deleting abnormal order goods amount in the order goods type, and calculating a commodity price standard line corresponding to the user consumption level based on the order goods type and the order goods amount of the user in the user consumption level;
the determining of the commodity price standard line of the target user according to the user purchasing power range comprises the following steps:
and determining the user consumption grade of the target user according to the user purchasing power range, and further determining a corresponding commodity price standard line.
2. A method for pushing information on an item during a promotional activity according to claim 1, wherein said method further comprises: acquiring time corresponding to the promotion amplitude of the promotion commodities in the promotion activity, generating a promotion activity time axis, and generating a goods pre-purchase time axis of the user by combining the preference function;
when the actual shopping record of the target user for the goods with the preference trademark/preference type in the current sales promotion activity is different from the goods pre-shopping time axis and the corresponding difference amount is larger than a preset threshold value, generating the preference weight of the preference trademark/preference type of the target user according to the difference amount, and adjusting the first recommendation score of the sales promotion goods with the preference trademark/preference type through the preference weight.
3. A method for pushing information on an item during a promotional activity according to claim 1, wherein said method further comprises: acquiring an actual shopping record of the target user for the preference necessities in the current promotion activity, and generating corresponding similar goods adjusting weights based on the goods types and the goods quantity in the actual shopping record of the preference necessities;
adjusting a second recommendation score for preference necessities of the same type as the category of the good based on the category good adjustment weight.
4. A method for pushing information on an item during a promotional activity according to claim 1, wherein said method further comprises: acquiring a user consumption record in a preset time period before the promotion activity, and detecting whether the user consumption record is larger than a preset consumption threshold value, wherein the preset consumption threshold value is correspondingly set according to the purchasing power range of the user;
and when the user consumption record is larger than a preset consumption threshold value, reducing the purchasing power range of the user.
5. An apparatus for pushing information on an article during a promotional activity, the apparatus comprising:
the acquisition module is used for acquiring historical orders of target users in historical sales promotion activities on a trading platform, acquiring order keywords in the historical orders, and determining preferred trademarks/preferred types, preferred necessities and user purchasing power ranges of the target users according to the order keywords;
the first calculation module is used for acquiring the consumption amount and the corresponding promotion amplitude of the target user for the goods with the preference trademark/preference type in the historical order, calculating a preference function of the target user for the preference trademark/preference type according to the consumption amount and the corresponding promotion amplitude, and calculating a first recommendation score of the promotion goods with the preference trademark/preference type in the promotion activity according to the promotion amplitude of the promotion goods with the preference trademark/preference type in the promotion activity;
the second calculation module is used for acquiring the consumption record of the preference necessities of the target user in the historical order, calculating the residual service life of the preference necessities according to the consumption record, and calculating a second recommendation score of the preference necessities according to the residual service life and by combining a preset correlation function between the service life of the goods and the recommendation score, wherein the correlation function is determined according to the type of the preference necessities;
the adjusting module is used for determining a commodity price standard line of a target user according to the purchasing power range of the user, comparing the promotion commodities with the preference trademark/preference type and the preference necessities with the commodity price standard line, determining a corresponding adjusting weight according to a comparison result, and adjusting a corresponding first recommendation score and a corresponding second recommendation score according to the adjusting weight to obtain a total commodity recommendation score in the promotion activity;
the pushing module is used for adjusting the commodity information pushing priority and the pushing frequency of the target user in the current sales promotion activity based on the total commodity recommendation score;
the calculating a preference function of the target user for the preference trademark/preference type according to the consumption amount and the corresponding promotion amplitude, and calculating a first recommendation score of the promotion commodity of the preference trademark/preference type in the promotion activity according to the promotion amplitude of the promotion commodity of the preference trademark/preference type in the promotion activity, wherein the calculation comprises the following steps:
acquiring a preset function rule, calculating a preference function of the target user for the preferred trademark/preferred type by combining with order data in the historical order, determining a corresponding first recommendation score by combining with the promotion amplitude of the promotion commodity with the preferred trademark/preferred type in the promotion activity, and according to the difference between the promotion amplitude of the promotion commodity and the corresponding preference function relationship, wherein the preset function rule comprises the following steps: the larger the promotion amplitude is, the larger the user consumption amount is;
calculating the remaining service life of the preference necessities according to the consumption record, wherein the method comprises the following steps:
the consumption record comprises the purchase quantity and the purchase time of the preference necessities;
calculating the service life of the preference necessities based on the purchase quantity and by combining the average product life of the preference necessities;
calculating a remaining useful life of the preference requisite based on the purchase time;
the device further comprises:
acquiring user order big data in historical promotion activities of a trading platform, comprising the following steps: the method comprises the steps of determining a user order total, an order goods type and an order goods amount, and determining a corresponding user consumption level according to the user order total;
deleting abnormal order goods amount in the order goods type, and calculating a commodity price standard line corresponding to the user consumption level based on the order goods type and the order goods amount of the user in the user consumption level;
the step of determining the commodity price standard line of the target user according to the user purchasing power range comprises the following steps:
and determining the user consumption grade of the target user according to the user purchasing power range, and further determining a corresponding commodity price standard line.
6. A promotional information on merchandise pushing device according to claim 5 wherein said device further comprises:
the second acquisition module is used for acquiring the time corresponding to the promotion amplitude of the promotion commodities in the promotion activity, generating a promotion activity time axis and generating a goods pre-purchase time axis of the user by combining the preference function;
and the second adjusting module is used for generating a preference weight of the preference trademark/preference type of the target user according to the difference amount when the difference exists between the actual shopping record of the target user for the goods with the preference trademark/preference type and a goods pre-shopping time axis in the current sales promotion activity and the corresponding difference amount is larger than a preset threshold value, and adjusting the first recommendation score of the sales promotion goods with the preference trademark/preference type according to the preference weight.
7. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method for pushing information on an item in a promotional activity according to any of claims 1 to 4 when executing the program.
8. A non-transitory computer readable storage medium, storing thereon a computer program, wherein the computer program, when executed by a processor, implements the steps of the method for pushing information on an item in a promotional activity according to any of claims 1 to 4.
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