CN113421027A - Method for grading customer consumption behaviors based on data operation - Google Patents
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Abstract
The invention discloses a method for grading customer consumption behaviors based on data operation, which comprises the following steps: an ElasticSearch search engine is set up, and user attribute information and behavior information are synchronized; step two: establishing a rating model, and sequentially acquiring the information of each client by the server according to each rating item; step three: synchronizing the calculation result to an elastic search; step four: and displaying a proportion pie chart, a thermodynamic diagram and a single-dimensional interval coordinate diagram of the rating statistical result on the client. The invention belongs to the technical field of consumption rating, and particularly provides a method for rating customer consumption behaviors based on data operation, which has high flexibility and visual rating results and supports real-time display and derivation of the rating and scoring results of customers.
Description
Technical Field
The invention belongs to the technical field of consumption rating, and particularly relates to a method for rating customer consumption behaviors based on data operation.
Background
In the prior art, a common back-end development language such as PHP, JAVA, and the like is used to divide clues into two dimensions of explicit information and implicit information, set scores for various clues, score each item of information of a client according to a preset score, and finally give a score condition and a rating result of each client.
The disadvantages of the existing methods for rating consumer behavior are as follows:
1) the grading items do not support self-definition, the grading interval is fixed, an operator needs to manually calculate and input the score, and the flexibility is lacked;
2) the rating result adopts a list form, and the expression form is single and is not visual;
3) the subsequent tracking of the rated customers needs manual operation, and the operation is complicated and the intellectualization is not good enough;
4) the rating model is not repeatable and the customer information is not updated in time.
Disclosure of Invention
Aiming at the situation, in order to overcome the defects of the prior art, the invention provides a PHP (graphical user protocol) language-based method for rating the consumption behaviors of the customers based on data operation, which is based on a PHP language, carries out real-time calculation on the attribute information and the behavior information of each customer stored in MYSQL (MySQL) according to a rating model set by an operator, synchronizes the rating results to ElasticSearch in real time, outputs a rating thermodynamic diagram, a pie chart and a single-dimensional coordinate diagram at the customer end by using HTML (hypertext markup language), and supports real-time display and derivation of the rating and scoring results of the customers.
The technical scheme adopted by the invention is as follows: the invention relates to a method for grading customer consumption behaviors based on data operation, which comprises the following steps of:
the method comprises the following steps: an ElasticSearch search engine is set up, and user attribute information and behavior information are synchronized;
step two: according to the attribute information and the behavior information of the user, a rating model is established through the client, and the server side sequentially acquires the information of each client according to each rating item and adds or subtracts the score for the clients meeting the conditions;
step three: synchronizing the calculation result to an elastic search;
step four: and displaying a proportion pie chart, a thermodynamic diagram and a single-dimensional interval coordinate diagram of the rating statistical result on the client to rate the customer consumption behavior.
And further, in each report, through a label grouping system preset in the client, the server sets labels for users in the rating interval in real time and enters the groups, and the marketing automation center in Smarket is seamlessly connected.
Furthermore, the client side also comprises a data detail system, the data detail system is used for rapidly displaying the customer details and the scoring results of each rating interval, and supporting result export, and meanwhile, a high-level filter is arranged in the client side, so that various filtering conditions are defined by users, and the intention customers are more accurately filtered.
By adopting the structure, the method for grading the customer consumption behaviors based on the data operation has the following beneficial effects:
1. the scoring items and the scoring intervals can be customized, the scores are in a percentage form, the interval setting and the scoring setting support dragging, the operation is sensitive, and the scores are automatically calculated;
2. the rating report comprises a ratio pie chart, a thermodynamic diagram and a single-dimensional interval coordinate diagram, and is rich and various in expression form and very visual;
3. the method supports the checking of the user details of each rating interval, realizes the labeling and grouping of rating users by one key, and realizes the follow-up user tracking automation;
4. the rating model can be repeated and copied, the rating result is dynamically updated, and the data is more accurate;
5. data results are synchronized to the ElasticSearch, and tens of millions of data volume calculation and query are supported.
Drawings
FIG. 1 is a flow chart of rating model setup and rating calculation for a method for rating customer consumption behavior based on data operation according to the present invention.
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
Detailed Description
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 only a part of the embodiments of the present invention, and not all of the embodiments; 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.
As shown in FIG. 1, the invention relates to a method for rating customer consumption behavior based on data operation, which comprises the following steps:
the method comprises the following steps: an ElasticSearch search engine is set up, and user attribute information and behavior information are synchronized;
step two: according to the attribute information and the behavior information of the user, a rating model is established through the client, and the server side sequentially acquires the information of each client according to each rating item and adds or subtracts the score for the clients meeting the conditions;
step three: synchronizing the calculation result to an elastic search;
step four: and displaying a proportion pie chart, a thermodynamic diagram and a single-dimensional interval coordinate diagram of the rating statistical result on the client to rate the customer consumption behavior.
And fourthly, clicking 'tag marking' and 'grouping' operations in each report form through a tag grouping system preset in the client, enabling the server to set tags for users in the rating interval in real time and enter the grouping, and seamlessly connecting the marketing automation middlings in Smarket.
The client side also comprises a data detail system, and the data detail system is used for quickly displaying the customer details and the grading result of each grading interval and supporting result export, and meanwhile, a high-level filter is arranged in the client side, so that various filtering conditions are defined by users, and the intention customers are more accurately filtered.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
The present invention and its embodiments have been described above, and the description is not intended to be limiting, and the drawings are only one embodiment of the present invention, and the actual structure is not limited thereto. In summary, those skilled in the art should appreciate that they can readily use the disclosed conception and specific embodiments as a basis for designing or modifying other structures for carrying out the same purposes of the present invention without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (3)
1. A method for rating customer consumption behavior based on data operations, comprising the steps of:
the method comprises the following steps: an ElasticSearch search engine is set up, and user attribute information and behavior information are synchronized;
step two: according to the attribute information and the behavior information of the user, a rating model is established through the client, and the server side sequentially acquires the information of each client according to each rating item and adds or subtracts the score for the clients meeting the conditions;
step three: synchronizing the calculation result to an elastic search;
step four: and displaying a proportion pie chart, a thermodynamic diagram and a single-dimensional interval coordinate diagram of the rating statistical result on the client to rate the customer consumption behavior.
2. The method of claim 1, wherein the method comprises: and fourthly, in each report, through a label grouping system preset in the client, the server sets labels for users in the rating interval in real time and enters the groups, and the marketing automation center in Smarket is seamlessly connected.
3. The method of claim 1, wherein the method comprises: the client side also comprises a data detail system which is used for rapidly displaying the customer details and the scoring results of each rating interval, supporting result export, and meanwhile, a high-level filter is arranged in the client side, so that various filtering conditions are defined by users, and the intention customers are filtered more accurately.
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Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
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US20180308158A1 (en) * | 2016-04-19 | 2018-10-25 | Dalian University Of Technology | An optimal credit rating division method based on maximizing credit similarity |
CN109003127A (en) * | 2018-07-06 | 2018-12-14 | 国网福建省电力有限公司 | A kind of credit rating method based on Electricity customers data |
CN112767177A (en) * | 2020-12-30 | 2021-05-07 | 中国人寿保险股份有限公司上海数据中心 | Insurance customer information management system for customer grading based on random forest |
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- 2021-07-21 CN CN202110823133.9A patent/CN113421027A/en active Pending
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20180308158A1 (en) * | 2016-04-19 | 2018-10-25 | Dalian University Of Technology | An optimal credit rating division method based on maximizing credit similarity |
CN109003127A (en) * | 2018-07-06 | 2018-12-14 | 国网福建省电力有限公司 | A kind of credit rating method based on Electricity customers data |
CN112767177A (en) * | 2020-12-30 | 2021-05-07 | 中国人寿保险股份有限公司上海数据中心 | Insurance customer information management system for customer grading based on random forest |
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