CN113159828A - Promotion scheme recommendation method and device and computer readable storage medium - Google Patents
Promotion scheme recommendation method and device and computer readable storage medium Download PDFInfo
- Publication number
- CN113159828A CN113159828A CN202110288787.6A CN202110288787A CN113159828A CN 113159828 A CN113159828 A CN 113159828A CN 202110288787 A CN202110288787 A CN 202110288787A CN 113159828 A CN113159828 A CN 113159828A
- Authority
- CN
- China
- Prior art keywords
- promotion scheme
- behavior
- customer
- promotion
- recommending
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 54
- 230000001960 triggered effect Effects 0.000 claims abstract description 24
- 230000000694 effects Effects 0.000 claims abstract description 13
- 230000006399 behavior Effects 0.000 claims description 117
- 230000001737 promoting effect Effects 0.000 claims description 30
- 238000010586 diagram Methods 0.000 description 10
- 239000013598 vector Substances 0.000 description 6
- 238000012986 modification Methods 0.000 description 5
- 230000004048 modification Effects 0.000 description 5
- 239000002699 waste material Substances 0.000 description 5
- 238000004891 communication Methods 0.000 description 4
- 238000013135 deep learning Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 238000001914 filtration Methods 0.000 description 3
- 239000011159 matrix material Substances 0.000 description 3
- 238000013473 artificial intelligence Methods 0.000 description 2
- 238000013527 convolutional neural network Methods 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 230000036962 time dependent Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0277—Online advertisement
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0269—Targeted advertisements based on user profile or attribute
- G06Q30/0271—Personalized advertisement
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Accounting & Taxation (AREA)
- Development Economics (AREA)
- Strategic Management (AREA)
- Finance (AREA)
- Game Theory and Decision Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a method and a device for recommending a promotion scheme and a computer readable storage medium, wherein the method comprises the following steps: when detecting behavior information triggered by a client through terminal equipment, a recommending device of the promotion scheme determines behavior time and behavior frequency corresponding to the behavior information, wherein the behavior information comprises client information, common geographical positions, browsed commodities, promotion activity information and commodity detail checking conditions; generating a promotion scheme corresponding to the behavior information, the behavior time and the behavior frequency; and pushing the promotion scheme to the terminal equipment corresponding to the customer. The invention can improve the matching rate of recommending the promotion scheme to the customer.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a method and a device for recommending a promotion scheme and a computer-readable storage medium.
Background
With the development of artificial intelligence and the continuous updating and upgrading of the internet of things, the interaction between a client and intelligent terminal equipment in daily life is more frequent, and information and resources are rapidly increased at present when the network technology is rapidly developed; this trend is particularly prominent in networks. In the face of such huge information resources on the Web, the problems of 'information lost' and 'information overload' on the Web are also aggravated, and 'sales promotion' is an effective means and way for product marketing activity popularization, so that a good sales promotion scheme is particularly important.
Disclosure of Invention
The embodiment of the invention provides a method and a device for recommending a promotion scheme and a computer-readable storage medium, and aims to solve the technical problem of low matching rate of promotion scheme recommendation to customers.
The embodiment of the invention provides a method for recommending a promotion scheme, which comprises the following steps:
when behavior information triggered by a client through terminal equipment is detected, determining behavior time and behavior frequency corresponding to the behavior information, wherein the behavior information comprises client information, common geographical positions, browsed commodities, promotion activity information and commodity detail checking conditions;
generating a promotion scheme corresponding to the behavior information, the behavior time and the behavior frequency;
and pushing the promotion scheme to the terminal equipment corresponding to the customer.
In an embodiment, the step of generating a promotion scheme corresponding to the behavior information, the behavior time, and the behavior frequency includes:
generating feature set data corresponding to the behavior information, the behavior time and the behavior frequency;
and generating a promotion scheme corresponding to the customer according to the feature set data.
In one embodiment, the step of generating a promotion scheme corresponding to the customer based on the feature set data includes:
associating a feature tag with the customer based on the feature set data;
and generating a promotion scheme corresponding to the customer according to the characteristic label associated with the customer.
In one embodiment, the step of generating a promotion scheme corresponding to the customer based on the feature set data includes:
determining whether a historical promotional program associated with the customer exists;
and when the historical promotion scheme associated with the customer exists, updating the historical promotion scheme according to the feature set data to obtain the promotion scheme corresponding to the customer.
In one embodiment, after the step of determining whether the customer has a historical promotional program, the method further comprises:
and when the historical promotion scheme associated with the customer does not exist, establishing a promotion scheme corresponding to the customer according to the feature set data.
In an embodiment, after the step of pushing the promotion scheme to the terminal device corresponding to the customer, the method further includes:
judging whether a product order or a browsing record triggered by the promotion scheme is detected within a preset time interval;
when a product order or a browsing record triggered by the promotion scheme is detected within the preset time, generating a promotion scheme according to a commodity corresponding to the product order or the browsing record, and pushing the promotion scheme to a terminal device corresponding to the customer;
and when detecting a product order or a browsing record triggered by the promotion scheme within the preset time, updating the reward information of the promotion scheme, and pushing the updated promotion scheme to the terminal equipment corresponding to the customer.
In an embodiment, when the behavior information of the client is detected, the step of determining the behavior time and the behavior frequency corresponding to the behavior information includes:
recording the browsing duration corresponding to the browsed commodities to obtain the behavior time;
and recording the browsing times corresponding to the browsed commodities to obtain the browsing frequency.
In an embodiment, after the step of generating the promotion scheme corresponding to the behavior information, the behavior time, and the behavior frequency, the method further includes:
acquiring a current time point;
and when the current time point reaches a preset pushing time point, executing the step of pushing the promotion scheme to the customer.
The embodiment of the invention also provides a device for recommending the promotion scheme, which comprises the following components: the system comprises a memory, a processor and a recommendation program of the promotion scheme, wherein the recommendation program of the promotion scheme is stored on the memory and can run on the processor, and the processor executes the recommendation program of the promotion scheme to realize the steps of the recommendation method of the promotion scheme.
The embodiment of the present invention further provides a computer-readable storage medium, where a program for recommending a promotional program is stored on the computer-readable storage medium, and when executed by a processor, the program for recommending a promotional program implements the steps of the method for recommending a promotional program as described above.
In the technical scheme of the embodiment, when behavior information triggered by a client through terminal equipment is detected, a recommending device of the promotion scheme determines behavior time and behavior frequency corresponding to the behavior information, wherein the behavior information comprises client information, common geographical positions, browsed commodities, promotion activity information and commodity detail checking conditions; generating a promotion scheme corresponding to the behavior information, the behavior time and the behavior frequency; and pushing the promotion scheme to the terminal equipment corresponding to the customer. The recommending device of the promotion scheme can acquire the behavior information triggered by the user at the terminal equipment, and then determines the promotion scheme suitable for the user based on the behavior information of the user and pushes the promotion scheme to the client terminal, so that the waste of a large amount of user behavior data is avoided, and the matching rate of recommending the promotion scheme to the client is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of a hardware architecture of a promotion recommendation device according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a first exemplary embodiment of a method for recommending a promotion scheme according to the present invention;
FIG. 3 is a flowchart illustrating a step S20 of a second embodiment of the promotion scheme recommendation method according to the present invention;
FIG. 4 is a flowchart illustrating a step S22 of a third embodiment of the promotion scheme recommendation method according to the present invention;
FIG. 5 is a flowchart illustrating a step S22 of a fourth embodiment of the promotion scheme recommendation method according to the present invention;
FIG. 6 is a flowchart illustrating a step S22 of a fifth embodiment of the promotion scheme recommendation method according to the present invention;
FIG. 7 is a flowchart illustrating a method for recommending a promotion scheme according to a sixth embodiment of the present invention;
fig. 8 is a detailed flowchart of step S10 of the seventh embodiment of the method for recommending a promotion scheme according to the present invention.
Detailed Description
For a better understanding of the above technical solutions, exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The main solution of the invention is: when behavior information triggered by a client through terminal equipment is detected, determining behavior time and behavior frequency corresponding to the behavior information, wherein the behavior information comprises client information, common geographical positions, browsed commodities, promotion activity information and commodity detail checking conditions; generating a promotion scheme corresponding to the behavior information, the behavior time and the behavior frequency; and pushing the promotion scheme to the terminal equipment corresponding to the customer.
The recommending device of the promotion scheme can acquire the behavior information triggered by the user at the terminal equipment, and then determines the promotion scheme suitable for the user based on the behavior information of the user and pushes the promotion scheme to the client terminal, so that the waste of a large amount of user behavior data is avoided, and the matching rate of recommending the promotion scheme to the client is improved.
As one implementation, the promotion scheme recommender can be as in fig. 1.
The embodiment scheme of the invention relates to a recommending device of a promotion scheme, which comprises the following components: a processor 101, e.g. a CPU, a memory 102, a communication bus 103. Wherein a communication bus 103 is used for enabling the connection communication between these components.
The memory 102 may be a high-speed RAM memory or a non-volatile memory (e.g., a disk memory). As in fig. 1, a detection program may be included in the memory 103 as a kind of computer storage medium; and the processor 101 may be configured to call the detection program stored in the memory 102 and perform the following operations:
when behavior information triggered by a client through terminal equipment is detected, determining behavior time and behavior frequency corresponding to the behavior information, wherein the behavior information comprises client information, common geographical positions, browsed commodities, promotion activity information and commodity detail checking conditions;
generating a promotion scheme corresponding to the behavior information, the behavior time and the behavior frequency;
and pushing the promotion scheme to the terminal equipment corresponding to the customer.
In one embodiment, the processor 101 may be configured to call a detection program stored in the memory 102 and perform the following operations:
the step of generating the promotion scheme corresponding to the behavior information, the behavior time and the behavior frequency comprises:
generating feature set data corresponding to the behavior information, the behavior time and the behavior frequency;
and generating a promotion scheme corresponding to the customer according to the feature set data.
In one embodiment, the processor 101 may be configured to call a detection program stored in the memory 102 and perform the following operations:
the step of generating a promotion scheme corresponding to the customer based on the feature set data comprises:
associating a feature tag with the customer based on the feature set data;
and generating a promotion scheme corresponding to the customer according to the characteristic label associated with the customer.
In one embodiment, the processor 101 may be configured to call a detection program stored in the memory 102 and perform the following operations:
the step of generating a promotion scheme corresponding to the customer based on the feature set data comprises:
determining whether a historical promotional program associated with the customer exists;
and when the historical promotion scheme associated with the customer exists, updating the historical promotion scheme according to the feature set data to obtain the promotion scheme corresponding to the customer.
In one embodiment, the processor 101 may be configured to call a detection program stored in the memory 102 and perform the following operations:
after the step of determining whether the customer has a historical promotional program, the method further comprises:
and when the historical promotion scheme associated with the customer does not exist, establishing a promotion scheme corresponding to the customer according to the feature set data.
In one embodiment, the processor 101 may be configured to call a detection program stored in the memory 102 and perform the following operations:
after the step of pushing the promotion scheme to the terminal device corresponding to the customer, the method further includes:
judging whether a product order or a browsing record triggered by the promotion scheme is detected within a preset time interval;
when a product order or a browsing record triggered by the promotion scheme is detected within the preset time, generating a promotion scheme according to a commodity corresponding to the product order or the browsing record, and pushing the promotion scheme to a terminal device corresponding to the customer;
and when detecting a product order or a browsing record triggered by the promotion scheme within the preset time, updating the reward information of the promotion scheme, and pushing the updated promotion scheme to the terminal equipment corresponding to the customer.
In one embodiment, the processor 101 may be configured to call a detection program stored in the memory 102 and perform the following operations:
recording the browsing duration corresponding to the browsed commodities to obtain the behavior time;
and recording the browsing times corresponding to the browsed commodities to obtain the browsing frequency.
In one embodiment, the processor 101 may be configured to call a detection program stored in the memory 102 and perform the following operations:
acquiring a current time point;
and when the current time point reaches a preset pushing time point, executing the step of pushing the promotion scheme to the customer.
In the technical scheme of the embodiment, the promotion scheme recommending device can acquire the behavior information triggered by the user at the terminal equipment, and then determines the promotion scheme suitable for the user based on the behavior information of the user and pushes the promotion scheme to the client terminal, so that the waste of a large amount of user behavior data is avoided, and the matching rate of promotion scheme recommendation to the client is improved.
In order to better understand the technical solution, the technical solution will be described in detail with reference to the drawings and the specific embodiments.
Referring to fig. 2, fig. 2 is a first embodiment of a method for recommending a promotion scheme according to the present invention, the method including the steps of:
step S10, when detecting the behavior information triggered by the client through the terminal device, determining the behavior time and the behavior frequency corresponding to the behavior information, wherein the behavior information includes client information, common geographical position, browsed goods, promotion activity information and goods detail viewing condition.
In this embodiment, a recommendation device of a sales promotion scheme may be in communication connection with terminal devices of users, and behavior information triggered by the users through the terminal devices may be acquired by the recommendation device of the sales promotion scheme, where the behavior information includes customer information, a common geographic location, browsed goods, sales promotion activity information, and a view situation of details of the goods, which correspond to the users when browsing shopping software, further, the customer information may be determined according to account information logged in by the users on the shopping software, the common geographic location may be determined according to positioning information of the terminal devices, a view situation of browsed goods, sales promotion activity information, and details of the goods is determined based on a browsing record of the users on the shopping software, and further, a behavior time and a behavior sales promotion frequency corresponding to the behavior information of the users may be acquired for subsequently producing the plans corresponding to the users.
Optionally, recording browsing duration corresponding to the browsed commodities to obtain behavior time; and recording the browsing times corresponding to the browsed commodities to obtain the browsing frequency. It is easy to understand that the browsing duration and the browsing frequency are low in acquisition difficulty, and the browsing records can be determined by screening based on the browsed commodities and browsing dates, so that the data acquisition difficulty can be reduced by the above acquisition method.
And step S20, generating a promotion scheme corresponding to the behavior information, the behavior time and the behavior frequency.
In this embodiment, a sales promotion plan for a suitable user is generated based on the behavior information of the user and the behavior time and the behavior frequency determined based on the behavior information.
Optionally, for the generation of the promotion scheme, the promotion scheme may be automatically generated or manually generated in advance based on the gender of the customer, the browsing duration and the browsing times of the web pages, the commodities and the detail pages: red envelope + time limit preference + gift. Further, for example: the male user + has seen the lighter commodity + has seen the detail 3 minutes + has seen 2 times, can automatically generate the sales promotion scheme: red envelope + time limit preference + gift.
And step S30, pushing the promotion scheme to the terminal equipment corresponding to the customer.
In this embodiment, after the promotion scheme is formed, the promotion scheme is pushed to the terminal device corresponding to the user.
In the technical scheme of the embodiment, the promotion scheme recommending device can acquire the behavior information triggered by the user at the terminal equipment, and then determines the promotion scheme suitable for the user based on the behavior information of the user and pushes the promotion scheme to the client terminal, so that the waste of a large amount of user behavior data is avoided, and the matching rate of promotion scheme recommendation to the client is improved.
Referring to fig. 3, fig. 3 is a second embodiment of the method for recommending a promotion scheme according to the present invention, and based on the first embodiment, the step S20 includes:
step S21, generating feature set data corresponding to the behavior information, the behavior time, and the behavior frequency.
And step S22, generating a promotion scheme corresponding to the customer according to the feature set data.
In this embodiment, the behavior information may be acquired through data collection to acquire user feature set data, where the user feature set data includes, but is not limited to, a product order, participation in a promotion event, a type of user equipment, a geographical location, browsing goods, content of the promotion event, and time information. And then generating a promotion scheme based on the feature set data.
In the technical scheme of the embodiment, the behavior information of the user is converted into the feature set data, so that the data is more simplified, and the generation efficiency of the promotion scheme is further improved.
Referring to fig. 4, fig. 4 is a second embodiment of the method for recommending a promotion scheme according to the present invention, and based on the first embodiment, the step S22 includes:
and step S221, associating a feature label to the client according to the feature set data.
Step S222, generating a promotion scheme corresponding to the customer according to the characteristic label associated with the customer.
In the embodiment, when the user feature set is constructed, data is preprocessed and standardized; classifying the users by adopting a deep learning convolutional neural network method, so that different labels can be attached to the users to form portrait data of the users; data such as the user's liking for discounting merchandise, preferring appliances, etc.; and finally, determining a promotion scheme corresponding to the user based on the label.
In the technical scheme of the embodiment, the users are classified by adopting the deep learning convolutional neural network method so as to perform label association on the users, and then the promotion scheme corresponding to the users can be generated according to the labels, so that the intelligent degree of the promotion scheme generation is improved when the promotion scheme generation efficiency is improved.
Referring to fig. 5, fig. 5 is a third embodiment of the method for recommending a promotion scheme according to the present invention, and based on any one of the first to second embodiments, step S22 includes:
step S223, determining whether there is a historical promotion scheme associated with the customer.
In the present embodiment, since the behavior information of the user is changed along with the operation of the user, the old user generally has a historical promotion scheme, and this step is used to determine whether the user has the historical promotion scheme.
Step S224, when there is a historical promotion scheme associated with the customer, updating the historical promotion scheme according to the feature set data to obtain a promotion scheme corresponding to the customer.
Optionally, when the behavior information of the user is collected, different promotion activities are abstracted into words, all promotion activities in the promotion scheme can be equivalent to form a sentence, then each type of promotion scheme is trained into a plurality of feature vectors by using a deep learning Word2vec training Word vector method, then vector similarity calculation is carried out according to the promotion scheme participated by the user and the previous promotion scheme, so that similar promotion schemes are promoted for the user, the obtained user behavior information can be combined with the user historical promotion scheme, a new promotion scheme is generated, and the generation flexibility of the promotion scheme is improved.
In this embodiment, due to the fact that the pre-detection behavior is adopted, after it is determined that the user is associated with the historical promotion scheme, the generation of the new promotion scheme can be performed on the original historical promotion scheme, a new promotion scheme does not need to be generated, and storage resource waste caused by the fact that one user has a plurality of promotion schemes is avoided.
Referring to fig. 6, fig. 6 is a fourth embodiment of the method for recommending a promotion scheme according to the present invention, based on any one of the first to third embodiments, after step S223, the method further includes:
and step S225, when the historical promotion scheme associated with the customer does not exist, establishing a promotion scheme corresponding to the customer according to the feature set data.
In the technical scheme of the embodiment, due to the fact that the advance detection behavior is adopted, a new promotion scheme can be generated after the fact that the user is associated with the historical promotion scheme is determined, and the intelligent degree of generation of the promotion scheme is improved.
Referring to fig. 7, fig. 7 is a fifth embodiment of the method for recommending a promotion scheme according to the present invention, and based on any one of the first to fourth embodiments, after step S30, the method further includes:
step S40, determining whether a product order or a browsing history triggered by the promotion scheme is detected within a preset time interval.
And step S50, when a product order or a browsing record triggered by the promotion scheme is detected within the preset time, generating the promotion scheme according to the commodity corresponding to the product order or the browsing record, and pushing the promotion scheme to the terminal equipment corresponding to the customer.
And step S60, when detecting the product order or the browsing record triggered by the promotion scheme within the preset time, updating the reward information of the promotion scheme, and pushing the updated promotion scheme to the terminal equipment corresponding to the customer.
In this embodiment, the pushing of other promotion schemes may be performed based on the behavior information of the user on the generated promotion method.
Optionally, when the user sees the promotion scheme, browsing in time and purchasing behavior, the system records the response speed of the user and purchasing time; when a user sees a promotion scheme, browsing is carried out at the first time, but no purchasing behavior occurs after browsing, wherein a similar promotion product is recommended, the price is respectively higher or lower than the promotion scheme for the purchasing behavior, and background record analysis is carried out according to the low-price promotion scheme and the high-price promotion scheme selected by the user; when the user browses and the purchasing behavior does not occur, correspondingly adjusting the content of the promotion product and the selection of promotion matching, and recording the purchasing behavior of the user in real time; when the user sees the promotion scheme, the user does not browse; the method comprises the steps that a sales promotion scheme is replaced, time-limited preferential strength is improved, gifts are added, and user feedback is recorded; and secondly, replacing the promotion scheme, replacing similar or same-class commodities, and recording user feedback.
According to the collected user information, a collaborative filtering model of the user is established according to data of the user purchasing commodities and participating in sales promotion activities, and is improved on the basis of a collaborative filtering algorithm through deep learning, specifically, recommendation is carried out on the basis of a user-item co-occurrence matrix of the collaborative filtering algorithm through the similarity of row vectors or column vectors. If we consider the same user purchase or participation item as a context, a matrix of item-contexts can be built. Furthermore, vector expression of items can be calculated on the matrix by using a word2vec model for reference, and similarity among the items can be calculated at a higher level, so that recommendation of commodities and promotion schemes among similar users can be realized.
In the technical scheme of this embodiment, the promotion scheme recommending device detects whether the user browses the generated promotion scheme and whether the user generates a purchase order through the generated promotion scheme, thereby implementing secondary pushing of other promotion schemes, and improving the intelligent degree of pushing the promotion scheme.
Referring to fig. 8, fig. 8 is a sixth embodiment of the method for recommending a promotion scheme according to the present invention, and based on any one of the first to fifth embodiments, step S10 includes:
in step S11, the current time point is acquired.
Step S12, when the current time point reaches a preset pushing time point, executing the step of pushing the promotion scheme to the customer.
In this embodiment, considering that the promotion strategy in the promotion scheme is time-dependent, for example: purchase item a with a discount of Y for N hours, so a promotion scheme push can be made based on the current point in time.
In the technical solution of this embodiment, it is important that the present embodiment can push the promotion scheme at a suitable time point, thereby improving user experience.
In order to achieve the above object, an embodiment of the present invention further provides a device for recommending a promotion scheme, where the device for recommending a promotion scheme includes: the system comprises a memory, a processor and a recommendation program of the promotion scheme, wherein the recommendation program of the promotion scheme is stored on the memory and can run on the processor, and the processor executes the recommendation program of the promotion scheme to realize the steps of the recommendation method of the promotion scheme.
To achieve the above object, an embodiment of the present invention further provides a computer-readable storage medium, on which a program for recommending a promotion scheme is stored, and the program for recommending a promotion scheme, when executed by a processor, implements the steps of the method for recommending a promotion scheme as described above.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or program product for promoting a program. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Moreover, the present invention may take the form of a recommended product program for a promotional program embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and recommender products for promotional programs in accordance with embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by recommender instructions for a promotional program. The program instructions recommended for these promotional schemes may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flow diagram flow or flows and/or block diagram block or blocks.
The program instructions for these promotional programs may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
The program instructions for these promotional programs may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A method for recommending a promotional program, the method comprising:
when behavior information triggered by a client through terminal equipment is detected, determining behavior time and behavior frequency corresponding to the behavior information, wherein the behavior information comprises client information, common geographical positions, browsed commodities, promotion activity information and commodity detail checking conditions;
generating a promotion scheme corresponding to the behavior information, the behavior time and the behavior frequency;
and pushing the promotion scheme to the terminal equipment corresponding to the customer.
2. A method for recommending a promotion scheme according to claim 1, wherein the step of generating a promotion scheme corresponding to the behavior information, the behavior time, and the behavior frequency includes:
generating feature set data corresponding to the behavior information, the behavior time and the behavior frequency;
and generating a promotion scheme corresponding to the customer according to the feature set data.
3. A method for recommending a promotional program according to claim 2, wherein said step of generating a promotional program corresponding to said customer based on said feature set data comprises:
associating a feature tag with the customer based on the feature set data;
and generating a promotion scheme corresponding to the customer according to the characteristic label associated with the customer.
4. A method for recommending a promotional program according to claim 2, wherein said step of generating a promotional program corresponding to said customer based on said feature set data comprises:
determining whether a historical promotional program associated with the customer exists;
and when the historical promotion scheme associated with the customer exists, updating the historical promotion scheme according to the feature set data to obtain the promotion scheme corresponding to the customer.
5. A method for recommending a promotional program according to claim 4, wherein after said step of determining if said customer has a historical promotional program, said method further comprises:
and when the historical promotion scheme associated with the customer does not exist, establishing a promotion scheme corresponding to the customer according to the feature set data.
6. The method for recommending a promotional program according to claim 2, wherein after the step of pushing the promotional program to the terminal device corresponding to the customer, further comprising:
judging whether a product order or a browsing record triggered by the promotion scheme is detected within a preset time interval;
when a product order or a browsing record triggered by the promotion scheme is detected within the preset time, generating a promotion scheme according to a commodity corresponding to the product order or the browsing record, and pushing the promotion scheme to a terminal device corresponding to the customer;
and when detecting a product order or a browsing record triggered by the promotion scheme within the preset time, updating the reward information of the promotion scheme, and pushing the updated promotion scheme to the terminal equipment corresponding to the customer.
7. A method for recommending a promotion scheme according to claim 2, wherein the step of determining the action time and the action frequency corresponding to the action information when the action information of the customer is detected comprises:
recording the browsing duration corresponding to the browsed commodities to obtain the behavior time;
and recording the browsing times corresponding to the browsed commodities to obtain the browsing frequency.
8. The method for recommending a promotion scheme according to claim 1, wherein the step of generating a promotion scheme corresponding to the behavior information, the behavior time, and the behavior frequency further comprises:
acquiring a current time point;
and when the current time point reaches a preset pushing time point, executing the step of pushing the promotion scheme to the customer.
9. An apparatus for recommending a promotional program, the apparatus comprising: a memory, a processor, and a program for recommending a promotional program stored on the memory and executable on the processor, the processor implementing the steps of the method for recommending a promotional program according to any of claims 1-8 when executing the program for recommending a promotional program.
10. A computer-readable storage medium, on which a program for recommending a promotional program is stored, which when executed by a processor implements the steps of the method for recommending a promotional program according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110288787.6A CN113159828A (en) | 2021-03-17 | 2021-03-17 | Promotion scheme recommendation method and device and computer readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110288787.6A CN113159828A (en) | 2021-03-17 | 2021-03-17 | Promotion scheme recommendation method and device and computer readable storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113159828A true CN113159828A (en) | 2021-07-23 |
Family
ID=76887701
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110288787.6A Pending CN113159828A (en) | 2021-03-17 | 2021-03-17 | Promotion scheme recommendation method and device and computer readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113159828A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115170253A (en) * | 2022-09-07 | 2022-10-11 | 国连科技(浙江)有限公司 | Method and device for pushing commodity information in sales promotion activities |
| CN117556131A (en) * | 2023-10-30 | 2024-02-13 | 广州圈量网络信息科技有限公司 | User tag triggering method, device, equipment and medium based on multiple materials |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108229997A (en) * | 2016-12-21 | 2018-06-29 | 天脉聚源（北京）科技有限公司 | A kind of method and system of internet shopping promotion |
| CN109214866A (en) * | 2018-08-31 | 2019-01-15 | 深圳春沐源控股有限公司 | The preferential promotion management method and device of commodity, computer equipment, storage medium |
| CN111652648A (en) * | 2020-06-03 | 2020-09-11 | 陈包容 | Method for intelligently generating personalized combined promotion scheme and system with same |
-
2021
- 2021-03-17 CN CN202110288787.6A patent/CN113159828A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108229997A (en) * | 2016-12-21 | 2018-06-29 | 天脉聚源（北京）科技有限公司 | A kind of method and system of internet shopping promotion |
| CN109214866A (en) * | 2018-08-31 | 2019-01-15 | 深圳春沐源控股有限公司 | The preferential promotion management method and device of commodity, computer equipment, storage medium |
| CN111652648A (en) * | 2020-06-03 | 2020-09-11 | 陈包容 | Method for intelligently generating personalized combined promotion scheme and system with same |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115170253A (en) * | 2022-09-07 | 2022-10-11 | 国连科技(浙江)有限公司 | Method and device for pushing commodity information in sales promotion activities |
| CN117556131A (en) * | 2023-10-30 | 2024-02-13 | 广州圈量网络信息科技有限公司 | User tag triggering method, device, equipment and medium based on multiple materials |
| CN117556131B (en) * | 2023-10-30 | 2024-04-19 | 广州圈量网络信息科技有限公司 | User tag triggering method, device, equipment and medium based on multiple materials |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20200195737A1 (en) | Clickstream analysis methods and systems related to determining actionable insights relating to a path to purchase | |
| CN110222272A (en) | A kind of potential customers excavate and recommended method | |
| CA2700030C (en) | Touchpoint customization system | |
| Bounsaythip et al. | Overview of data mining for customer behavior modeling | |
| US8341102B2 (en) | User state presumption system, user state presumption method, and recording media storing user state presumption program | |
| CN107590675B (en) | User shopping behavior identification method based on big data, storage device and mobile terminal | |
| CN102629360B (en) | A kind of effective dynamic commodity recommend method and commercial product recommending system | |
| US8799814B1 (en) | Automated targeting of content components | |
| US20130124361A1 (en) | Consumer, retailer and supplier computing systems and methods | |
| US20090112648A1 (en) | Online sales and marketing integration | |
| CN112435067A (en) | Intelligent advertisement putting method and system for cross-e-commerce platform and social platform | |
| US20140279016A1 (en) | Behavioral tracking system and method in support of high-engagement communications | |
| CN104361506A (en) | Intelligent commodity recommending method and system based on user answer-and-question mode | |
| CN102360386A (en) | Intelligent shopping guide system and method of electronic commerce website | |
| CN110147821A (en) | Targeted user population determines method, apparatus, computer equipment and storage medium | |
| CN113159828A (en) | Promotion scheme recommendation method and device and computer readable storage medium | |
| CN111737338A (en) | Big data portrait-based closed-loop marketing data analysis method | |
| CN111428131A (en) | Information pushing method, device and system | |
| CN111311332A (en) | User data processing method and device | |
| CN110751537A (en) | Online and offline intelligent marketing method and device | |
| Denga et al. | Digital Marketing and the Sustainable Performance of Small and Medium Enterprises | |
| CN111680213B (en) | Information recommendation method, data processing method and device | |
| Soni | Role of Temporal, Demographic, and Behavioral Factors in Customer Conversion Through Dynamic Creative Optimization in the Consumer-Packaged Goods Setting | |
| US20140289054A1 (en) | Behavioral tracking system and method in support of high-engagement communications | |
| CN111127074A (en) | Data recommendation method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |