CN113781173A - AI robot marketing method and system based on one-object-one-code and storable medium - Google Patents

AI robot marketing method and system based on one-object-one-code and storable medium Download PDF

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CN113781173A
CN113781173A CN202111070372.8A CN202111070372A CN113781173A CN 113781173 A CN113781173 A CN 113781173A CN 202111070372 A CN202111070372 A CN 202111070372A CN 113781173 A CN113781173 A CN 113781173A
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任威伦
金燕
孙顺博
赵辰
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Calculus Innovation Technology Beijing Co ltd
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Abstract

The invention discloses an AI robot marketing method, system and storage medium based on one object-one code, belonging to the technical field related to intelligent marketing, and comprising the following steps: collecting basic data and behavior data of a user; calculating basic data and behavior data of a user, and performing label matching on the user; dividing the user into groups according to the labels and the behavior data; determining a marketing mode according to the user tags, the user groups and the marketing rules; the method has the advantages that targeted fine marketing is realized through the user portrait, the label and the group which are mined by the big data in the private consumer member operation system; by adopting different marketing conversation schemes and care schemes of different consumers, the online and offline consumers can carry out commodity marketing and emotional care when communicating with the robot, so that the user experience is improved, the promotion effect is improved, and the robot recommends commodities more reasonably.

Description

AI robot marketing method and system based on one-object-one-code and storable medium
Technical Field
The invention relates to the technical field related to intelligent marketing, in particular to an AI robot marketing method and system based on one object and one code and a storage medium.
Background
The intelligent customer service is developed on the basis of large-scale knowledge processing, is applied to the industry, is a large-scale knowledge processing technology, a natural language understanding technology, a knowledge management technology, an automatic question-answering system, an inference technology and the like, has industrial universality, provides a fine-grained knowledge management technology for enterprises, and establishes a quick and effective technical means based on natural language for communication between the enterprises and mass users; meanwhile, statistical analysis information required by fine management can be provided for enterprises.
However, in the prior art, a relatively fixed knowledge base is generally adopted, the knowledge base is input in advance, a user submits a keyword and then feeds back the keyword, accurate marketing cannot be performed on the user, most of the keywords are passive questions and lack of active marketing, so that the common marketing robot is fixed in replying the questions, and the marketing effect is poor. Therefore, developing a marketing system capable of actively marketing is an urgent problem to be solved by those skilled in the art to improve marketing effect.
Disclosure of Invention
In view of the above, the present invention provides an AI robot marketing method, system and storage medium based on one object-one code, which overcome the drawbacks of the prior art.
In order to achieve the above purpose, the invention provides the following technical scheme:
an AI robot marketing method based on one object-one code comprises the following specific steps:
collecting data: collecting basic data and behavior data of a user;
matching the labels: calculating basic data and behavior data of a user, and performing label matching on the user;
grouping: dividing the user into groups according to the labels and the behavior data;
determining a marketing mode: and determining a marketing mode according to the user tags, the user groups and the marketing rules.
Optionally, the step of acquiring data is:
setting a behavior data acquisition step according to a goods sales flow;
the user participates in the behavior data acquisition step to generate behavior data;
acquiring basic data and behavior data of a user, and performing relevance storage, wherein the basic data is identity information of the user and the state of a user side.
Optionally, the behavior data acquiring step includes: generating a code source, printing a label, putting on the market and configuring activities;
wherein the content of the first and second substances,
generating a code source: generating two-dimensional codes in batches according to goods, and sending the two-dimensional codes to a factory;
printing a label: receiving the two-dimension code of the electronic version, and printing the two-dimension code on the corresponding goods;
putting on the market: putting the goods printed with the two-dimensional code on the market;
configuring activities: and carrying out equity configuration on goods released to the market.
Optionally, the tag matching method includes that original multi-dimensional data is adopted for behaviors of each user at regular time according to tag categories, data cleaning and missing value processing are performed, an ARMA algorithm is used for data dimension reduction, and classification calculation and tag updating are performed through K-means unsupervised clustering and a naive Bayesian algorithm.
Optionally, the tag types include a fact tag, a model tag, a prediction tag, an operation tag, and an e-commerce tag.
Optionally, the marketing mode includes two types, namely active touch and passive touch;
wherein:
the main movable contact is as follows: when the set external environment meets the active touch condition, the AI robot actively touches the consumer to give corresponding marketing scheme and/or care;
is moved to contact: when the consumer accords with the moved access condition during code scanning, the AI robot passively accesses the consumer to carry out a corresponding marketing scheme.
Optionally, the main moving contacting step is:
s41: the set external environment reaches the main contact condition;
s42: designing a marketing scheme through the acquired user portrait and the user group;
s43: establishing an interaction rule under the background-condition interaction function of the AI robot;
s44: the AI robot automatically executes the interaction rules set at S43, executes the marketing plan, and feeds back data to refine the user tags and portraits.
Optionally, the moved contacting step is:
s51: the user reaches the moved access condition when scanning the code;
s52: designing a marketing scheme according to the acquired user portrait and the user group;
s53: establishing an interaction rule under the background-code scanning interaction function of the AI robot;
s54: the AI robot automatically executes the interaction rules set at S53, executes the marketing plan, and feeds back data to refine the user tags and portraits.
An AI robot marketing system based on one object-one code comprises a data acquisition device, a data processing device and a data execution device;
a data acquisition device: collecting basic data and behavior data of a user;
a data processing device: calculating basic data and behavior data of a user and matching a user label; dividing the user into groups according to the labels and the behavior data; classifying the marketing modes according to the user tags, the user groups and the marketing rules;
the data execution device: and executing different marketing modes according to the triggering conditions.
A computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the steps in an AI robot marketing method based on an object-code.
According to the technical scheme, compared with the prior art, the invention discloses an AI robot marketing method, system and storage medium based on one object and one code, and aims to refine marketing by using user figures, labels and groups mined by big data in a private consumer member operation system; different marketing conversation schemes and care schemes are adopted for different consumers, and the online and offline consumers are subjected to commodity marketing and emotional care when communicating with the robot and are put down, so that the sales promotion effect is improved, and the robot recommends commodities more reasonably.
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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 embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a schematic flow chart of a tag acquisition method according to the present invention;
FIG. 3 is a flowchart of the active contact method of the present invention;
fig. 4 is a flowchart of the moved contact method of the present 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.
The embodiment of the invention discloses an AI robot marketing method, a system and a storage medium based on one object and one code.
An AI robot marketing method based on one-object-one code is shown in fig. 1, wherein a private consumer member operation system is used to acquire data to divide user tags and groups.
Private consumer member operation system: a private consumer member operation system developed by V points provides consumer members and products operated intelligently by relying on mass consumer data and AI processing capacity of the V points, integrates functions of user insights, labels and groups, intelligent operation, marketing touch points and the like, optimizes marketing strategies and schemes for clients in various industries through deep mining and analysis of big data, provides accurate marketing touch means, and achieves the purposes of reducing marketing cost and improving marketing effect. And the marketing efficiency and the intelligent marketing capability of the brand enterprises are driven to be upgraded.
The method for classifying the labels is shown in fig. 2 and includes two steps:
1. the data acquisition step comprises:
the member operation system of the private consumer completes the commercial behavior, and the code source generation, the label printing, the market release and the configuration correlation are carried out;
after a consumer purchases a product, scanning a two-dimension code of the activity on the product to participate in an object-code marketing activity;
after the code is scanned, the consumer can call the activity rule configured by the member operation system of the private area consumer;
the system acquires necessary data generated by a consumer in a code scanning process to give corresponding rights and interests, and the acquired data comprises the following data: openid, geographic location, code scanning batch, code scanning product, code scanning time, etc.
Wherein, the specific steps of one object and one code activity are as follows:
generating a code source: the two-dimensional codes are generated in batches and can be provided according to a factory requirement format so as to be printed;
printing a label: the factory receives the two-dimensional code of electronic version, uses professional machine, prints the two-dimensional code to relevant product, for example: printing the two-dimensional code on media bound with commodities, such as paper cards, bottle caps and the like;
putting on the market: after the two-dimensional code is printed, the commodities are produced, and can be put on the market and can be purchased by consumers;
configuring activities: and performing active configuration on the two-dimensional code put on the market, for example, configuring certain products, and when the user uses the WeChat code, issuing the rights and interests of a cash red packet, a point and a coupon to the user.
2. The specific steps for dividing the labels and the groups are as follows:
the user participates in an object-code scanning activity, generates user basic data and behavior data in the participation process, and associates the information of products purchased by the user, code scanning time, code scanning positions and the like.
Wherein, the user basic information: the user authorized woolen scale, gender, mobile phone number, authorized geographic position, warehousing time, WeChat openid and whether public numbers are concerned or not;
the user consumption information: code scanning date, code scanning time, code scanning commodity, code scanning right (cash red package and score), code scanning geographic position and code scanning times.
And operating through a one-object one-code user specific algorithm according to the collected information, and printing a fact label, a model label, a prediction label, an operation label and an electronic trademark label for the user, wherein the total number of the five types of labels is five.
The one-object one-code user specific algorithm is characterized in that according to formulated different label rules, original multi-dimensional data are adopted for behaviors of each user every day, after data cleaning and missing value processing, an ARMA algorithm is used for data dimension reduction, K-means unsupervised clustering is carried out, a naive Bayes algorithm is used for classification calculation, and labels are updated; the method comprises the following specific steps:
performing data dimensionality reduction by using an ARMA algorithm: according to the user basic data collected by the system, due to the fact that the dimensionality is large, dimensionality reduction processing is conducted, namely, the user basic information (the name, the gender, the mobile phone number, the authorized geographic position, the warehousing time, the WeChat openid and whether public numbers are concerned or not) and the user consumption information (code scanning date, code scanning time, code scanning commodities, code scanning rights (cash packages and points), code scanning geographic positions and code scanning times) are reduced to 2-5 dimensionalities in total, and after data are produced, unsupervised clustering is conducted through K-means.
K-means unsupervised clustering: the ARMA algorithm is used for carrying out data dimension reduction on data, manual interference is not carried out, the data are freely combined and clustered, and effective clustering data (for example, the data volume is typical and is defined according to working experience) are processed by a naive Bayes algorithm.
Naive Bayes algorithm: and receiving effective clustering data of the K-means unsupervised clustering, judging probability values of the data, accurately classifying the data, matching the data with the existing label rules, and automatically marking labels according to an algorithm after the data meet the rules.
The label rule is:
fact label: objective facts exist, and user labels such as gender, age, warehousing time, etc. cannot be changed basically.
Model labeling: according to the brand industry characteristics, after the brand industry characteristics are set in advance, the system automatically marks labels through the behavior analysis of the user, such as: XX product preferences, active users, etc.
And (3) predicting a label: according to the brand industry characteristics, after the user behavior and other data are analyzed integrally, the user is predicted, for example: and (4) predicting occupation.
Operation label: and judging the label of the operation effect on the basis of the RFM model by analyzing the user behavior.
Electric trademark label: and the user finishes corresponding behaviors at the e-commerce, and the label is attached after being analyzed by the large data center of the private-domain consumer member operation system.
The tags can be queried through the query levels and the tag types, the number of people who have the tags can be checked through the tags in the list, and the user can be selected to the corresponding user library after clicking the number of people.
User groups can be set according to user behaviors and label combinations, wherein label conditions comprise the five types of labels, and the group behaviors comprise: code scanning position, code scanning SKU, accumulated code scanning days, accumulated code scanning times, accumulated code scanning amount, first code scanning time, last code scanning time, attention operation time, mobile phone numbers, accumulated consumption amount, user value of the last year, code scanning days of the last year, code scanning times of the month, code scanning months continuously, code scanning times of the last 30 days, code scanning days of the last 30 days and code scanning times of the last day are 18 conditions. According to the combination of the user characteristics, the system can obtain the corresponding label after scanning every day.
Marketing mode setting:
based on AI robot interaction, carry out initiative marketing and weather/festival care to the consumer, include the following step: the method is related to a private consumer member operation system, user figures, groups and user labels after big data analysis are called, robot marketing and care rules are set for different group users, and the touch modes are active touch and passive touch.
Wherein, the user portrait covers the content and includes:
1) the crowd attributes are as follows: sex distribution;
2) user owned tag: a fact label, a model label, an operation label, a prediction label and an e-commerce label;
3) consumption position: a consumption geographic location;
4) code scanning condition: code scanning time distribution, code scanning times, code scanning days,
5) User value: and (5) a user code scanning trend.
The main moving contact is arranged in a mode that: according to the group to which the user belongs, the owned label and the robot execution time (specifically, the time, the hour, the minute and the second unit), the AI robot reaches the appointed time, and actively carries out marketing touch on the user with the set group and label rule.
The specific steps are shown in fig. 3:
s11 main contact modes of the AI robot main contact (condition interaction) comprise: short message reach, public number reach;
s12, setting accurate marketing schemes for different user groups through the user portrait and the user groups acquired in the private consumer member operation system;
s13: and under the background-condition interaction function of the AI robot, creating a corresponding interaction rule. The rules comprise the steps of specifying groups, labels, touch channels, setting relevant dialogs (the dialogs support dynamic parameters such as user names, total code scanning amount, total code scanning days, total code scanning times, continuous code scanning months, maximum code scanning SKU, geographic positions and other information), pictures, execution time of tasks, touch intervals and sequencing of condition interaction;
s14: the AI robot automatically executes the relevant rules set in S13, executes the marketing plan, supports multiple rounds of conversations with the consumer after reaching the touch, collects and feeds back effective information in the process of communicating with the user again to perfect the user label and portrait in the private consumer member operation system.
For example, if a consumer communicates with a common robot, the robot replies a rigid state, which is information recorded in a knowledge base in advance, and if a private consumer member operation system AI robot is used for interaction, the robot can firstly call a user portrait and an affiliated group of the consumer in a private consumer member operation system to know the consumer, and targeted communication and marketing can be performed, and besides passive communication and marketing, active contact can be performed. Can save labour cost, marketing expense, use the AI robot to economize under the condition of manpower, marketing effect can be better, and user experience is also better.
The set mode of the moved contact is as follows: and automatically carrying out the triggered marketing according to the group to which the user belongs, the SKU with the label, the code scanning and consumption of the one-object-one code, the number of interaction times of the one-object-one code and the number of interaction days. Namely, when a user scans a code in one object, the AI robot automatically contacts the information feedback and marketing information of the user, which are different according to different set conditions, and different marketing methods are adopted for different users consuming the code in one object.
The specific steps are shown in fig. 4:
s21, the main contact mode of the AI robot being contacted (code scanning interaction) is that after the consumer scans one object of the commodity for one code, the AI robot is contacted when the corresponding small program or H5 page is opened;
s22, setting accurate marketing schemes for different user groups through the user portrait and the user groups acquired in the private consumer member operation system;
s23: establishing a corresponding interaction rule under the background-code scanning interaction function of the AI robot; the rules comprise a designated group, a label, a touch type (according to interaction times and interaction days), a designated SKU (stock keeping unit), a touch channel, a set of related dialogs (dynamic parameters supported by the dialogs, such as user information, total code scanning amount, total code scanning days, total code scanning times, continuous code scanning months, maximum code scanning SKU (stock keeping unit), geographical positions and the like), pictures, execution time of tasks, touch intervals and sequencing of condition interaction;
s24: the AI robot automatically executes the relevant rule set at S23, performs the passive contact when the user meets the relevant contact type and other rules, and supports multiple rounds of conversations with the consumer after the contact, and can collect feedback to improve the user label and portrait in the "private consumer member operation system" again, in order to communicate with the user effectively.
For example, when the user scans the code and opens the applet or the H5 page, there are related marketing dialogs set according to the rule of the user code scanning interaction behavior, and targeted communication and marketing according to different dialogs and the user image of the consumer and the affiliated group.
An AI robot marketing system based on one object-one code comprises a data acquisition device, a data processing device and a data execution device;
a data acquisition device: collecting basic data and behavior data of a user;
a data processing device: calculating basic data and behavior data of a user and matching a user label; dividing the user into groups according to the labels and the behavior data; classifying the marketing modes according to the user tags, the user groups and the marketing rules;
the data execution device: and executing different marketing modes according to the triggering conditions.
A computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the steps in an AI robot marketing method based on an object-code.
Example 2:
1. an thing-code user participates in the marketing process, which specifically comprises the following steps:
1) the private consumer member operation system completes business behaviors, and relevant one-code activities are configured from code source generation, label printing, market release and configuration.
2) After a consumer purchases a product, the activity two-dimension code on the product is scanned to participate in an object-code marketing activity.
3) After the code is scanned, the consumer can call the activity rule configured by the member operation system of the private-area consumer.
4) The system acquires necessary data generated by a consumer in a code scanning process to give corresponding rights and interests, and the acquired data comprises the following data: openid, geographic location, code scanning batch, code scanning product and code scanning time.
5) And (4) marking a corresponding label for a user through label algorithms such as data cleaning, missing value processing and the like.
2. Active and passive contact to consumer
And dividing consumer groups through user tags and consumption behaviors.
And setting the rules of the main moving contact and the driven contact.
The robot automatically operates according to the rule, when the user performs code scanning interaction again and reaches the triggered touch rule (set user group, user label, touch type and consumer consumption SKU), the machine executes the touch rule and issues the rule according to the set words and rights.
For example:
the user is swept three bottles of beer, and then is moved to: fiercely friend, you have drunk 3 bottles of Qingdao beer today, surpassing the past. A lottery may be drawn by clicking on the link http:// vjifen. com.
The code scanning of the user is that the user is triggered to reach the following condition that the code scanning is carried out by a tag non-server at 10-12 o' clock in the evening: the wine taste is known deeply at night and the love is great!
The user has scanned 5 bottles & the label is not the waiter on the day, then is touched: you have drunk 5 bottles of Qingdao beer today, send you a driving ticket of a generation and hope to help you, please see in the personal center.
The main moving contact is to actively set an appointed group and an appointed label, set the dialect and the task time, and after reaching the set rule, the robot actively moves the contact and issues the call according to the set dialect and the right.
For example:
if the local temperature is rainy, the contact is activated: today [ geographical position ] has little rain, go out and carry rain gear, avoid drenching on the rain gear!
And festival and holiday day denier, the main and movable contacts are as follows: yuan Dan comes to visit relatives and friends, and you want to be happy and worried; get together to drink XXXX and wish you good to take everyday; the love returns to the beginning again, warmly wishes to remain in mind, wish you to be happy for a long time, and happy never break down! Coupon picking address:http://vjifen.com。
the AI robot automatic operation back is carried out accurate touch and is reached and can carry out many rounds of conversations to the user, through the accurate marketing means of AI robot, reaches and saves marketing cost, promotes marketing effect.
According to the method, active consumer care can be performed under the weather, festival and specific scenes of consumers according to set and learned rules through an AI robot active contact technology; based on an object-code, through an AI robot passive contact technology, when a consumer conducts an object-code scanning action, according to the code scanning interaction action of the consumer, a user portrait and an affiliated group, the communication and marketing are pertinently and accurately conducted.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. An AI robot marketing method based on one object-one code is characterized by comprising the following specific steps:
collecting data: collecting basic data and behavior data of a user;
matching the labels: calculating basic data and behavior data of a user, and performing label matching on the user;
grouping: dividing the user into groups according to the labels and the behavior data;
determining a marketing mode: and determining a marketing mode according to the user tags, the user groups and the marketing rules.
2. The AI robot marketing method based on an object-code according to claim 1, characterized in that the step of collecting data is:
setting a behavior data acquisition step according to a goods sales flow;
the user participates in the behavior data acquisition step to generate behavior data;
acquiring basic data and behavior data of a user, and performing relevance storage, wherein the basic data is identity information of the user and the state of a user side.
3. The AI robot marketing method based on an object-code according to claim 2, characterized in that the behavior data acquisition step is: generating a code source, printing a label, putting on the market and configuring activities; wherein the content of the first and second substances,
generating a code source: generating two-dimensional codes in batches according to goods, and sending the two-dimensional codes to a factory;
printing a label: receiving the two-dimension code of the electronic version, and printing the two-dimension code on the corresponding goods;
putting on the market: putting the goods printed with the two-dimensional code on the market;
configuring activities: and carrying out equity configuration on goods released to the market.
4. The AI robot marketing method based on one object and one code as claimed in claim 1, wherein the label matching method is to adopt original multidimensional data for each user's behavior at regular time according to label category, to perform data cleaning and missing value processing, to perform data dimension reduction using ARMA algorithm, to perform classification calculation and update labels by K-means unsupervised clustering and naive Bayesian algorithm.
5. The AI robot marketing method based on one object-one code according to claim 1, characterized in that the tag types include a fact tag, a model tag, a forecast tag, an operation tag, and an e-commerce tag.
6. The AI robot marketing method based on one object and one code as claimed in claim 1, wherein the marketing mode includes two types of active touch and passive touch;
wherein:
the main movable contact is as follows: when the set external environment meets the active contact condition, the AI robot actively contacts the consumer to push the goods information;
is moved to contact: when the consumer accords with the passive access condition during code scanning, the AI robot passively accesses the consumer and pushes the goods information.
7. The AI robot marketing method based on one object-code according to claim 6, characterized in that the active contacting steps are:
s41: the set external environment reaches the main contact condition;
s42: designing a marketing scheme through the acquired user portrait and the user group;
s43: establishing an interaction rule under the background-condition interaction function of the AI robot;
s44: the AI robot automatically executes the interaction rules set at S43, executes the marketing plan, and feeds back data to refine the user tags and portraits.
8. The AI robot marketing method based on an object-code according to claim 6, characterized in that the step of being moved is:
s51: the user reaches the moved access condition when scanning the code;
s52: designing a marketing scheme according to the acquired user portrait and the user group;
s53: establishing an interaction rule under the background-code scanning interaction function of the AI robot;
s54: the AI robot automatically executes the interaction rules set at S53, executes the marketing plan, and feeds back data to refine the user tags and portraits.
9. An AI robot marketing system based on an object code is characterized by comprising a data acquisition device, a data processing device and a data execution device;
a data acquisition device: collecting basic data and behavior data of a user;
a data processing device: calculating basic data and behavior data of a user and matching a user label; dividing the user into groups according to the labels and the behavior data; classifying the marketing modes according to the user tags, the user groups and the marketing rules;
the data execution device: and executing different marketing modes according to the triggering conditions.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of a method for AI robot marketing based on an object-code according to any one of claims 1 to 8.
CN202111070372.8A 2021-09-13 2021-09-13 AI robot marketing method and system based on one-object-one-code and storable medium Pending CN113781173A (en)

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