CN116258330A - Method for judging optimal activity scheme based on existing user structure - Google Patents

Method for judging optimal activity scheme based on existing user structure Download PDF

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CN116258330A
CN116258330A CN202310050615.4A CN202310050615A CN116258330A CN 116258330 A CN116258330 A CN 116258330A CN 202310050615 A CN202310050615 A CN 202310050615A CN 116258330 A CN116258330 A CN 116258330A
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scheme
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徐默
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QIMING INFORMATION TECHNOLOGY CO LTD
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QIMING INFORMATION TECHNOLOGY CO LTD
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Abstract

The invention discloses a method for judging an optimal activity scheme based on an existing user structure, which is characterized in that the existing user structure is based on the existing user information, the current user cluster situation is analyzed, the history activity effect is referred, the characteristics of the existing user structure are judged, the targeted activity design is carried out, the budget of the activity is combined, a more reasonable activity scheme is provided for a user, the amount of the investment of the activity cost is calculated, the user tag is combined with the activity scheme by the technical scheme provided by the invention, the user characteristics are effectively utilized to accurately obtain customers, the effective activity scheme formulation is completed, the problem that the prior art scheme depends on human judgment or is a more effective activity along history, so that the merchant activity item is single, the existing user group information cannot be effectively utilized, and the effective user activity amount can be formulated through the analysis of the existing user.

Description

Method for judging optimal activity scheme based on existing user structure
Technical Field
The invention relates to the technical field of scheme planning, in particular to a method for judging an optimal activity scheme based on an existing user structure.
Background
With the rapid development of the internet, online user operation has become a user group struggled by various merchants and platforms, and online user experience is also particularly important, so that the merchants can often surround hot topics when making user schemes, or perform activity planning and design by referring to other merchant activities, the problem that the merchants are blind is solved, and a desirable activity planning scheme is made by combining the self user group and target users and combining business development.
At present, the B-end merchant and group market activities are mostly surrounded by a plurality of directions of new drawing, repurching and retaining, each of the merchants is provided with similar or identical activity schemes, the strong relevance of the existing user structure, user relation, target user group and activity scheme is ignored in the activity planning process, so that the situation that the floor fall of the activity execution is large, the passenger acquisition cost is high, the market cost is high but the activity effect is low is caused, the real user requirements cannot be acquired by standing at the B-end thinking, and similar effects cannot be obtained in the same way.
Disclosure of Invention
In order to solve the problem that the scheme is formulated to be undesirable, the invention provides a method for judging the optimal activity scheme based on the existing user structure.
A method of determining an optimal activity scheme based on an existing user structure, comprising the steps of:
step S1: establishing a dynamic user structure label based on the existing user: re-analyzing the current user structure data based on the user portraits pre-constructed by the existing users before each activity setting;
step S2: determining the activity target and the activity budget cost amount in the present period: the user selects the activity target in the current period and inputs the budget cost amount of the activity;
step S3: analyzing whether the merchant targets are consistent with the existing user structure labels, and recommending an activity scheme: comprehensively analyzing the existing structure labels of the users, and outputting the problems existing in the existing user structures and the directions needing to be lifted.
Further, the step S1 of re-analyzing the current user structure data based on the user portrayal pre-constructed by the existing user further comprises the sub-steps of:
step S11: marking task information through the basic information of the user;
step S12: marking through the recent daily behaviors of the user, and establishing a label library similar to the business project;
step S13: through the user tag in the step S12, a word frequency-inverse text frequency TF-IDF algorithm is adopted to screen tags from the existing user information tags;
step S14: and (3) considering the definition range of the movable commodity by combining with the information of the existing mall, comprehensively analyzing the new stay rate, the loss rate and the purchasing rate of the shared commodity of the historical user, and defining the user structure by the age bracket of the existing user group and the purchasing power of the existing user.
Further, the step S11 of user basic information includes an age, a location, and a distance from the activity place; the distance between the movable place and the movable place can be judged through daily goods receiving addresses.
Further, the step S12 includes login frequency, common module, user search word, order product, re-purchase information, order information, liveness, sharing capability and purchasing power; at least one tag per user.
Further, the step S13 ensures that the existing users all have at least one user room, and the screening tag further includes: and screening out labels with the weight value of the user label before n bits, wherein n is a positive integer, and the label distribution corresponds to the marking of the user basic information in the first item, and taking the first three labels with higher corresponding weights as basic information to attach labels.
Further, the step S14 mall information includes: shopping mall purchase information, sales of goods and sales of single goods information.
Further, the step S2 of selecting the activity target by the user includes: pulling up, activating, re-purchasing and selling; the user may also input the cast-out status of the historical activity for the activity scheme to reference.
Further, the step S3 further includes: meanwhile, an activity scheme for solving the problem in a targeted way is output, and a plurality of recommended schemes are provided for the user to select in combination with a historical activity scheme of the user, and the recommended amount is recommended around the budget amount of the user.
The invention has the beneficial effects that: the invention provides a method for judging an optimal activity scheme based on the existing user structure, which is used for analyzing the current user cluster situation based on the existing user information, referring to the history activity effect, judging the characteristics of the existing user structure, carrying out targeted activity design, combining the budget of the activity, providing a more reasonable activity scheme for users, and putting in the amount of the activity cost.
Drawings
Fig. 1 is a diagram of a method architecture for determining an optimal activity scheme based on an existing user architecture in accordance with the present invention.
Detailed Description
For a clearer understanding of technical features, objects, and effects of the present invention, a specific embodiment of the present invention will be described with reference to the accompanying drawings.
The invention provides a method for judging an optimal activity scheme based on an existing user structure, which comprises the following steps:
step S1: establishing a dynamic user structure label based on the existing user: re-analyzing the current user structure data based on the user portraits pre-constructed by the existing users before each activity setting;
step S2: determining the activity target and the activity budget cost amount in the present period: the user selects the activity target in the current period and inputs the budget cost amount of the activity;
step S3: analyzing whether the merchant targets are consistent with the existing user structure labels, and recommending an activity scheme: comprehensively analyzing the existing structure labels of the users, and outputting the problems existing in the existing user structures and the directions needing to be lifted.
Step S1 re-analyzes the current user structure data based on the pre-constructed user representation of the existing user further comprises the sub-steps of:
step S11: marking task information through the basic information of the user;
step S12: marking through the recent daily behaviors of the user, and establishing a label library similar to the business project;
step S13: through the user tag in the step S12, a word frequency-inverse text frequency TF-IDF algorithm is adopted to screen tags from the existing user information tags;
step S14: and (3) considering the definition range of the movable commodity by combining with the information of the existing mall, comprehensively analyzing the new stay rate, the loss rate and the purchasing rate of the shared commodity of the historical user, and defining the user structure by the age bracket of the existing user group and the purchasing power of the existing user.
Step S11, the user basic information comprises age, position and distance from the activity place; the distance between the movable place and the movable place can be judged through daily goods receiving addresses.
Step S12, the daily behaviors of the user comprise login frequency, a common module, user search words, ordered products, re-purchase information, order information, liveness, sharing capability and purchasing power; at least one tag per user.
Step S13, ensuring that all existing users have at least one user label room, wherein the screening label further comprises: and screening out labels with the weight value of the user label before n bits, wherein n is a positive integer, and the label distribution corresponds to the marking of the user basic information in the first item, and taking the first three labels with higher corresponding weights as basic information to attach labels.
The step S14 mall information includes: shopping mall purchase information, sales of goods and sales of single goods information.
Step S2 the user selecting an activity target includes: pulling up, activating, re-purchasing and selling; the user may also input the cast-out status of the historical activity for the activity scheme to reference.
Step S3 further includes: meanwhile, an activity scheme for solving the problem in a targeted way is output, and a plurality of recommended schemes are provided for the user to select in combination with a historical activity scheme of the user, and the recommended amount is recommended around the budget amount of the user.
In this embodiment, a method architecture for determining an optimal activity scheme based on an existing user structure is shown in fig. 1, and a method for formulating an effective activity scheme based on an existing user structure analysis is divided into three main steps: and establishing a dynamic user structure label based on the existing user, selecting a current activity target and budgeting the activity cost amount, and analyzing whether a merchant target accords with the existing user structure to recommend an activity scheme.
1. Existing user structure analysis: re-analyzing the current user structure data before each activity setting, and based on the user portrait pre-constructed by the existing user, the first item is: marking task information through basic information of a user, such as age, position, distance between the user and an activity place (which can be judged through a daily receiving address) and the like; the second item: marking by using information such as login frequency, common modules, user search words, order products, re-purchase information, order information, liveness, sharing capability, purchasing power and the like of the user in the daily activities of nearly three months, and establishing a tag library which is similar to the operation project, wherein each user has at least one behavior tag; third item: through the user label of the second item, the condition that the existing member users all have at least one user label, the label with the weight value of the user label before n bits is obtained by screening out the label with the weight value of the user label more than or equal to 1 (positive integer) from the existing member user information labels by adopting a word frequency-inverse text frequency TF-IDF algorithm, the label distribution corresponds to the condition that the user basic information of the first item is marked, and the first three labels with higher corresponding weights are taken as basic information attached labels; fourth item: by combining the existing shopping mall purchase information and the sales volume information of the goods and the sales volume information of the single goods, the definition range of the movable goods can be considered; and the whole disc analysis history user draws new retention rate, loss rate, purchasing rate after sharing commodities, age groups of the existing user and purchasing power of the existing user, and defines a user structure.
2. The current activity goal selection and budget activity cost amount: the user selects the target of the activity in the current period, can select to pull new, activate, re-purchase and sell, can manually input the budget cost amount of the activity, and can manually input the project production condition of the historical activity for the reference of the activity scheme.
3. The method comprises the steps of comprehensively analyzing the existing structure of a user, outputting the problems and the direction to be lifted existing in the existing structure of the user, outputting the activity scheme for solving the problems in the same way as the output and the pertinence, providing three recommendation schemes for the user to select by combining the historical activity scheme of the user, and recommending the user with the budget amount of the user.
After the scheme is used for measuring and calculating, the scheme for planning the activities of the merchants can be more specifically solved, and the scheme for optimizing the activities of the users can be timely matched with the pain points existing in the users, so that better conversion and promotion of the user groups are realized.
The original artificial experience activity plan is converted into the activity plan aiming at the current operation situation demand through the data, so that the user demand can be better grasped, blind spots and pain spots of a merchant in the activity plan are solved, and the input of the merchant is more effectively produced.
The invention provides a method for judging an optimal activity scheme based on the existing user structure, which is used for analyzing the current user cluster situation based on the existing user information, referring to the history activity effect, judging the characteristics of the existing user structure, carrying out targeted activity design, combining the budget of the activity, providing a more reasonable activity scheme for users, and putting in the amount of the activity cost.
The foregoing has shown and described the basic principles and features of the invention and the advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims (8)

1. A method for determining an optimal activity scheme based on an existing user structure, comprising the steps of:
step S1: establishing a dynamic user structure label based on the existing user: re-analyzing the current user structure data based on the user portraits pre-constructed by the existing users before each activity setting;
step S2: determining the activity target and the activity budget cost amount in the present period: the user selects the activity target in the current period and inputs the budget cost amount of the activity;
step S3: analyzing whether the merchant targets are consistent with the existing user structure labels, and recommending an activity scheme: comprehensively analyzing the existing structure labels of the users, and outputting the problems existing in the existing user structures and the directions needing to be lifted.
2. The method of claim 1, wherein said step S1 of re-analyzing the current user structure data based on the user portraits pre-constructed by the existing user further comprises the sub-steps of:
step S11: marking task information through the basic information of the user;
step S12: marking through the recent daily behaviors of the user, and establishing a label library similar to the business project;
step S13: through the user tag in the step S12, a word frequency-inverse text frequency TF-IDF algorithm is adopted to screen tags from the existing user information tags;
step S14: and (3) considering the definition range of the movable commodity by combining with the information of the existing mall, comprehensively analyzing the new stay rate, the loss rate and the purchasing rate of the shared commodity of the historical user, and defining the user structure by the age bracket of the existing user group and the purchasing power of the existing user.
3. The method according to claim 2, wherein the user basic information in step S11 includes age, location, and distance from the place of activity; the distance between the movable place and the movable place can be judged through daily goods receiving addresses.
4. The method according to claim 2, wherein the step S12 of determining the optimal activity scheme based on the existing user structure includes login frequency, common module, user search word, order product, repurchase information, order information, liveness, sharing ability and purchasing power; at least one tag per user.
5. The method according to claim 2, wherein said step S13 guarantees that the existing users all have at least one user room, and said filtering tag further comprises: and screening out labels with the weight value of the user label before n bits, wherein n is a positive integer, and the label distribution corresponds to the marking of the user basic information in the first item, and taking the first three labels with higher corresponding weights as basic information to attach labels.
6. The method of claim 2, wherein the step S14 mall information includes: shopping mall purchase information, sales of goods and sales of single goods information.
7. The method of claim 1, wherein the step S2 of selecting the activity target by the user comprises: pulling up, activating, re-purchasing and selling; the user may also input the cast-out status of the historical activity for the activity scheme to reference.
8. The method of claim 1, wherein said step S3 further comprises: meanwhile, an activity scheme for solving the problem in a targeted way is output, and a plurality of recommended schemes are provided for the user to select in combination with a historical activity scheme of the user, and the recommended amount is recommended around the budget amount of the user.
CN202310050615.4A 2023-02-01 2023-02-01 Method for judging optimal activity scheme based on existing user structure Pending CN116258330A (en)

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