CN108376339A - Advertising specialty recommends method and device - Google Patents
Advertising specialty recommends method and device Download PDFInfo
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- CN108376339A CN108376339A CN201711477925.5A CN201711477925A CN108376339A CN 108376339 A CN108376339 A CN 108376339A CN 201711477925 A CN201711477925 A CN 201711477925A CN 108376339 A CN108376339 A CN 108376339A
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- 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
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- 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
- G06Q30/0207—Discounts or incentives, e.g. coupons or rebates
Abstract
The invention discloses a kind of advertising specialties to recommend method, the method includes：The attributive character information of advertising specialty is matched with the initial attribute characteristic information of user, obtains the advertising specialty to be recommended to match with the user；The advertising specialty to be recommended is recommended into user；User is received in the advertising specialty to be recommended to the selection confirmation message of advertising specialty, obtains actual recommendation advertising specialty.Using the above method, solves existing advertising specialty and recommend method not high in the presence of recommendation precision, the low problem of ad conversion rates.
Description
This application claims being submitted within 11st in September in 2017, Patent Office of the People's Republic of China, application No. is 201710812053.7, invention names
This is hereby incorporated by reference in the referred to as priority of the Chinese patent application of " advertising specialty recommendation method and device ", entire contents
In application.
Technical field
This application involves computer realms, and in particular to a kind of advertising specialty recommendation method and device.
Background technology
Currently, many enterprises or businessman be to improve the popularity of product, often through the mode pair for providing advertising specialty
Its product makees advertisement.There is provided advertising specialty one of conventional method be at random in the street pedestrian provide advertising specialty or
These advertising specialties are sent by mailing.
Existing advertising specialty recommends method not carry out any screening to user, often randomly chooses user and carries out advertisement
The granting of gift, there is no being orientated to advertising specialty real feelings in view of user, user cannot be liked according to oneself to select
The advertising specialty of oneself interested advertising specialty, recommendation inevitably generates harassing and wrecking to user, and usual user can abandon these immediately
Advertising specialty.
Recommend precision not high in conclusion existing advertising specialty recommends method to exist, the low problem of ad conversion rates.
Invention content
The application provides a kind of advertising specialty recommendation method, recommends method accurate in the presence of recommending to solve existing advertising specialty
Spend not high, the low problem of ad conversion rates.
The advertising specialty recommends method, including：
The attributive character information of advertising specialty is matched with the initial attribute characteristic information of user, is obtained and the use
The advertising specialty to be recommended that family matches；
The advertising specialty to be recommended is recommended into user；
User is received in the advertising specialty to be recommended to the selection confirmation message of advertising specialty, it is wide to obtain actual recommendation
Accuse gift.
Optionally, before the described the step of advertising specialty to be recommended is recommended user, including：
Postsearch screening is carried out to the advertising specialty to be recommended according to the user information of real-time collecting.
Optionally, the user information of the real-time collecting includes at least one below：
User is to the feedback information of offering question, the buying behavior information of user, the network behavior information of user, user
Self-description information, other people description informations to user.
Optionally, the user includes to the feedback information of offering question：
The problem of more than one is arranged, feedback the problem of according to user to having proposed, is dynamically arranged next ask
Topic.
Optionally, the setting more than one the problem of, feedback the problem of according to user to having proposed dynamically is set
Next problem is set, including：
The problem of more than one is set, and positive feedback and negative-feedback Liang Ge feedback informations branch are arranged to each problem,
If user is positive feedback to the feedback information of current problem, next problem is set as the problem corresponding to positive feedback；If with
Family is negative-feedback to the feedback information of current problem, then next problem is set as the problem corresponding to negative-feedback.
Optionally, the step of carrying out postsearch screening to the advertising specialty to be recommended according to the user information of real-time collecting
Later, including：
The initial attribute characteristic information of the user is adjusted into Mobile state according to the user information of real-time collecting.
Optionally, the attributive character information by advertising specialty is matched with the initial attribute characteristic information of user,
Including：
Each key word information in the initial attribute characteristic information of user is ranked up one pass of generation according to weight
Keyword sequence；
It closes first key word information in the sequence is corresponding with the attributive character information of each advertising specialty
Keyword information is matched, and the current matching advertising specialty that can obtain matching keywords is selected；
Each current matching advertising specialty that next key word information in the sequence is selected with previous step again
Attributive character information in corresponding key word information matched, select matched advertising specialty；
It repeats the above steps, until the last one key word information matching in the keyword sequence terminates；
If by the keyword sequence next key word information and the category of matched advertising specialty selected
Property characteristic information in corresponding key word information can not obtain matching keywords when being matched, i.e., cannot select and more match again
Advertising specialty, then terminate matching process；
Using the matched advertising specialty finally selected as the advertising specialty to be recommended to match with user.
Optionally, the attributive character information of the advertising specialty, including：
The granting region of the advertising specialty, use environment, the advertisement position size for including, the advertisement position position for including, packet
The advertisement position background color contained and/or suitable crowd.
Optionally, the advertising specialty includes：Gift and/or gift token in kind.
Optionally, the initial attribute characteristic information of the user, including：
Age of user, gender, region, educational background, the level of consumption, advertising specialty type interested.
Optionally, the attributive character information by advertising specialty is matched with the initial attribute characteristic information of user,
Including：
By having the website platform of DSP analysis ability to the attributive character information of advertising specialty and the initial attribute of user
Characteristic information is analyzed, and the attributive character information of advertising specialty is matched with the initial attribute characteristic information of user.
The application also provides a kind of advertising specialty recommendation apparatus, and described device includes：
Matching characteristic information unit is used for the initial attribute characteristic information of the attributive character information of advertising specialty and user
It is matched, obtains the advertising specialty to be recommended to match with the user；
Recommend gift unit, for the advertising specialty to be recommended to be recommended user；
Target gift unit is obtained, receives user in the advertising specialty to be recommended to the selection confirmation letter of advertising specialty
Breath, obtains actual recommendation advertising specialty.
Optionally, described device includes：
Postsearch screening unit is used for before recommending gift cell operation, according to the user information of real-time collecting to described
Advertising specialty to be recommended carries out postsearch screening.
Optionally, the user information of the real-time collecting includes at least one below：
User is to the feedback information of offering question, the buying behavior information of user, the network behavior information of user, user
Self-description information, other people description informations to user.
Optionally, the user includes to the feedback information of offering question：
The problem of more than one is arranged, feedback the problem of according to user to having proposed, is dynamically arranged next ask
Topic.
Optionally, the setting more than one the problem of, feedback the problem of according to user to having proposed dynamically is set
Next problem is set, including：
The problem of more than one is set, and positive feedback and negative-feedback Liang Ge feedback informations branch are arranged to each problem,
If user is positive feedback to the feedback information of current problem, next problem is set as the problem corresponding to positive feedback；If with
Family is negative-feedback to the feedback information of current problem, then next problem is set as the problem corresponding to negative-feedback.
Optionally, the step of carrying out postsearch screening to the advertising specialty to be recommended according to the user information of real-time collecting
Later, including：
The initial attribute characteristic information of the user is adjusted into Mobile state according to the user information of real-time collecting.
Optionally, the attributive character information by advertising specialty is matched with the initial attribute characteristic information of user,
Including：
Each key word information in the initial attribute characteristic information of user is ranked up one pass of generation according to weight
Keyword sequence；
It closes first key word information in the sequence is corresponding with the attributive character information of each advertising specialty
Keyword information is matched, and the current matching advertising specialty that can obtain matching keywords is selected；
Each current matching advertising specialty that next key word information in the sequence is selected with previous step again
Attributive character information in corresponding key word information matched, select matched advertising specialty；
It repeats the above steps, until the last one key word information matching in the keyword sequence terminates；
If by the keyword sequence next key word information and the category of matched advertising specialty selected
Property characteristic information in corresponding key word information can not obtain matching keywords when being matched, i.e., cannot select and more match again
Advertising specialty, then terminate matching process；
Using the matched advertising specialty finally selected as the advertising specialty to be recommended to match with user.
Optionally, the attributive character information of the advertising specialty, including：
The granting region of the advertising specialty, use environment, the advertisement position size for including, the advertisement position position for including, packet
The advertisement position background color contained and/or suitable crowd.
Optionally, the advertising specialty includes：Gift and/or gift token in kind.
Optionally, the initial attribute characteristic information of the user, including：
Age of user, gender, region, educational background, the level of consumption, advertising specialty type interested.
Optionally, the attributive character information by advertising specialty is matched with the initial attribute characteristic information of user,
Including：
By having the website platform of DSP analysis ability to the attributive character information of advertising specialty and the initial attribute of user
Characteristic information is analyzed, and the attributive character information of advertising specialty is matched with the initial attribute characteristic information of user.
Compared with prior art, the present invention has the following advantages：
The application provides a kind of advertising specialty recommendation method, the method includes：The attributive character of advertising specialty is believed
Breath is matched with the initial attribute characteristic information of user, obtains the advertising specialty to be recommended to match with the user；By institute
It states advertising specialty to be recommended and recommends user；User is received to confirm the selection of advertising specialty in the advertising specialty to be recommended
Information obtains actual recommendation advertising specialty.
Advertising specialty provided by the present application recommends method, first by by the attributive character information of advertising specialty and user
Initial attribute characteristic information is matched, and the advertising specialty to be recommended to match with the user is filtered out；Then by user couple
The advertising specialty to be recommended to match is screened to obtain actual recommendation advertising specialty.Filtering of the present invention Jing Guo two links,
Realize that the height of advertising specialty is precisely recommended, while target recommended advertisements gift is the advertising specialty that user likes, and directly affects use
Frequency and period of the family using advertising specialty, improve advertising specialty arrival rate and displaying frequency, can realize that brand quickly exports
With marketing rapid conversion, ad conversion rates are significantly improved.
Description of the drawings
Fig. 1 is the flow chart that a kind of advertising specialty that the application first embodiment provides recommends method.
Fig. 2 is a kind of schematic diagram for advertising specialty recommendation apparatus that the application first embodiment provides.
Specific implementation mode
Many details are elaborated in the following description in order to fully understand the present invention.But the present invention can be with
Much implement different from other manner described here, those skilled in the art can be without prejudice to intension of the present invention the case where
Under do similar popularization, therefore the present invention is not limited to the specific embodiments disclosed below.
The application first embodiment provides a kind of advertising specialty recommendation method.Referring to FIG. 1, it illustrates according to this Shen
A kind of advertising specialty that embodiment please provides recommends the flow chart of method.It is described in detail below in conjunction with Fig. 1.The embodiment
It is that the advertising specialty provided from the visual angle of advertising specialty publication channel recommends method.The advertising specialty publication channel refers to B2C
Website (Jingdone district, Amazon etc.) or information network platform (such as today's tops etc.).
The attributive character information of advertising specialty is matched with the initial attribute characteristic information of user, is obtained by step S101
Take the advertising specialty to be recommended to match with the user.
This step is real by matching the attributive character information of advertising specialty with the initial attribute characteristic information of user
Advertising specialty is showed to match with the first time of user, the advertising specialty to be recommended to match with user is filtered out by matching.
The advertising specialty, refers to the gift for providing gift advertisement position, and an advertising specialty can usually provide at least
One advertisement position, can provide two or more advertisement positions under normal circumstances, so that corporate boss shares advertising expenditure.The advertisement
Gift includes：Gift and/or gift token in kind.The small article in kind for being usually suitable carrying or posting, such as paper handkerchief, makeup
Product.Usual paper towel box is the cuboid with 6 faces, that is, there are multiple advertisement positions, one kind can be printed on each advertisement position and waited for
The information of releasing advertisements.Compared with advertisement on line, making advertisement on advertising specialty has apparent advantage, since advertisement goes out on line
The existing time is extremely short, and consumer cannot be made to form memory, and can continually see paper handkerchief using the consumer of gift paper towel box
Advertising information on box can bring profoundly impression to it, promote the desire that consumer buys audience in advertisement to be released
It hopes, and then makes the profit of corporate boss's acquisition bigger.
The attributive character information of the advertising specialty, including：The granting region of the advertising specialty, includes at use environment
Advertisement position size, include advertisement position position, include advertisement position background color and/or suitable crowd.The attribute of advertising specialty is believed
Breath can be showed by the form of label.
The initial attribute characteristic information of the user, refer to recommended advertisements gift gift publication channel storage about user
Initial attribute characteristic information, including：Age of user, gender, region, educational background, the level of consumption, advertising specialty type interested.
The initial attribute characteristic information of user can be showed by the form of label.
The advertising specialty to be recommended to match with the user refers to and is gone out by matching the preliminary screening from advertising specialty
Be used for advertising specialty recommended to the user.In order to realize more accurately advertising specialty dispatching, waited for what the user matched
Recommended advertisements gift also needs to the postsearch screening by user.
The attributive character information by advertising specialty is matched with the initial attribute characteristic information of user, including：
By having the website platform of DSP analysis ability to the attributive character information of advertising specialty and the initial attribute of user
Characteristic information is analyzed, and the attributive character information of advertising specialty is matched with the initial attribute characteristic information of user.
Wherein, DSP (Demand-SidePlatform) is exactly party in request's platform.The DSP of one real meaning, it is necessary to core there are two gathering around
Heart feature, first, possessing the infrastructure and ability of powerful RTB (Real-Time Bidding), second is that possessing advanced use
Family orients (AudienceTargeting) technology.DSP (party in request's platform) services for advertiser, and advertisement can be arranged in advertiser
Target audience, launch region, advertisement bid etc..
The attributive character information by advertising specialty is matched with the initial attribute characteristic information of user, including：
Each key word information in the initial attribute characteristic information of user is ranked up one pass of generation according to weight
Keyword sequence；
It closes first key word information in the sequence is corresponding with the attributive character information of each advertising specialty
Keyword information is matched, and the current matching advertising specialty that can obtain matching keywords is selected；
Each current matching advertising specialty that next key word information in the sequence is selected with previous step again
Attributive character information in corresponding key word information matched, select matched advertising specialty；
It repeats the above steps, until the last one key word information matching in the keyword sequence terminates；
If by the keyword sequence next key word information and the category of matched advertising specialty selected
Property characteristic information in corresponding key word information can not obtain matching keywords when being matched, i.e., cannot select and more match again
Advertising specialty, then terminate matching process；
Using the matched advertising specialty finally selected as the advertising specialty to be recommended to match with user.
The advertising specialty to be recommended is recommended user by step S102.
After advertising specialty publication channel selects the advertising specialty to be recommended to match with the user, need to wait for described
Recommended advertisements gift recommends user, is screened again by user.
The user refers to the user for accessing advertising specialty publication channel client, and user issues canal if necessary to advertising specialty
The advertising specialty that road is recommended, it usually needs registered and provided the initial attribute characteristic information of user.
The advertising specialty to be recommended is recommended into user, can by the picture presentation of advertising specialty to be recommended to user,
The name list of advertising specialty to be recommended can also be showed user, be selected for user.
Preferably, in order to improve the precision of advertising specialty dispatching, the advertising specialty to be recommended is recommended described
Before the step of user, postsearch screening is carried out to the advertising specialty to be recommended according to the user information of real-time collecting.Carry out two
Secondary screening includes not only that part advertising specialty to be recommended is selected from all advertising specialties to be recommended, further includes increasing new wait for
Recommended advertisements gift.Because may find that certain advertising specialties to be recommended are not suitable for user according to the user information of real-time collecting
At this moment new demand needs to delete some advertising specialties to be recommended；, whereas if the user information according to real-time collecting may
It was found that user has advertising specialty new demand, then need to increase new advertising specialty to be recommended, for example, from the buying behavior of user
It finds that user is buying some articless for babies in information, then can increase the conduct of the advertising specialties such as baby moistening frost, baby wipes box and wait for
Recommended advertisements gift.The user information of the real-time collecting includes at least one below：Feedback letter of the user to offering question
Breath, the buying behavior information of user, the network behavior information of user, the self-description information of user, other people descriptions to user
Information.
The user includes to the feedback information of offering question：The problem of more than one is set, according to user to having carried
Next problem is dynamically arranged in the feedback for the problem of going out.
The setting more than one the problem of, feedback the problem of according to user to having proposed dynamically is arranged next
A problem, including：
The problem of more than one is set, and positive feedback and negative-feedback Liang Ge feedback informations branch are arranged to each problem,
If user is positive feedback to the feedback information of current problem, next problem is set as the problem corresponding to positive feedback；If with
Family is negative-feedback to the feedback information of current problem, then next problem is set as the problem corresponding to negative-feedback.
For example, if user is women, if provided with first for " you want to get free cosmeticsIf " with
"Yes" is answered at family, then next problem could be provided as that " you like the cosmetics of which brand", if user answers "No",
Then next problem could be provided as that " you want to get free paper handkerchief", " you like the cosmetics of which brand" it is just
Corresponding problem is fed back, " you want to get free paper handkerchief" it is problem corresponding to negative-feedback.
After the step of carrying out postsearch screening to the advertising specialty to be recommended according to the user information of real-time collecting, extensively
Accuse gift publication channel can according to the user information of real-time collecting to the initial attribute characteristic information of the user into Mobile state
Adjustment.For example, if finding the existing level of consumption of user and initial attribute characteristic information according to the user information of real-time collecting
The middle level of consumption is inconsistent, then the level of consumption in user property characteristic information is dynamically changed to the existing level of consumption,
Assuming that the level of consumption is low and middle-end in a certain user's initial attribute characteristic information, the existing level of consumption is high-end, then uses this
Level of consumption dynamic in the attributive character information of family is adjusted to high-end, to recommend when next recommended advertisements gift and user
Matched advertising specialty to be recommended.
Step S103 receives user in the advertising specialty to be recommended to the selection confirmation message of advertising specialty, obtains
Actual recommendation advertising specialty.
Advertising specialty publication channel after advertising specialty to be recommended is recommended user, by user according to the hobby of oneself from
The advertising specialty that oneself hobby is selected in advertising specialty to be recommended, is further screened by user.Pass through user couple
Advertising specialty carries out selection confirmation, and it is the advertising specialty that user likes to realize actual recommendation advertising specialty, is on the one hand avoided
Make that advertising specialty is idle can not to generate value since user obtains the advertising specialty not liked, influences ad conversion rates；Separately
The advertising specialty that one side user likes oneself does not have conflict psychology, uses probability higher, ad conversion rates higher.
So far, the embodiment of method is recommended to be described in detail advertising specialty provided in this embodiment.This implementation
Example, the attributive character information of advertising specialty is matched, realize advertisement gift with the initial attribute characteristic information of user first
The first time of product screens；Then postsearch screening is carried out to the advertising specialty to be recommended according to the user information of real-time collecting；Most
The advertising specialty for selecting from advertising specialty to be recommended oneself hobby according to the hobby of oneself by user afterwards, to advertising specialty into
Third time of having gone is screened.By screening process three times, make to realize advertising specialty and the accurate matching of user, actual recommendation advertisement
Gift is the advertising specialty that user likes, and user uses probability higher, ad conversion rates higher to these advertising specialties.
Recommend method corresponding with the advertising specialty of above-mentioned offer, present invention also provides a kind of advertising specialties to recommend to fill
It sets.Since the embodiment of described device is substantially similar to the embodiment of method, so describe fairly simple, related place referring to
The part of embodiment of the method illustrates.Device embodiment described below is only schematical.The advertising specialty is recommended
Device embodiment is as follows：
Referring to FIG. 2, it illustrates a kind of advertising specialty recommendation apparatus provided according to the second embodiment of the application
Schematic diagram.
Described device, including：Matching characteristic information unit 201 recommends gift unit 202, obtains target gift unit
203。
Matching characteristic information unit 201 is used for the initial attribute feature of the attributive character information of advertising specialty and user
Information is matched, and the advertising specialty to be recommended to match with the user is obtained；
Recommend gift unit 202, for the advertising specialty to be recommended to be recommended user；
Target gift unit 203 is obtained, it is true to the selection of advertising specialty in the advertising specialty to be recommended to receive user
Recognize information, obtains actual recommendation advertising specialty.
Optionally, described device includes：
Postsearch screening unit is used for before recommending gift cell operation, according to the user information of real-time collecting to described
Advertising specialty to be recommended carries out postsearch screening.
Optionally, the user information of the real-time collecting includes at least one below：
User is to the feedback information of offering question, the buying behavior information of user, the network behavior information of user, user
Self-description information, other people description informations to user.
Optionally, the user includes to the feedback information of offering question：
The problem of more than one is arranged, feedback the problem of according to user to having proposed, is dynamically arranged next ask
Topic.
Optionally, the setting more than one the problem of, feedback the problem of according to user to having proposed dynamically is set
Next problem is set, including：
The problem of more than one is set, and positive feedback and negative-feedback Liang Ge feedback informations branch are arranged to each problem,
If user is positive feedback to the feedback information of current problem, next problem is set as the problem corresponding to positive feedback；If with
Family is negative-feedback to the feedback information of current problem, then next problem is set as the problem corresponding to negative-feedback.
Optionally, the step of carrying out postsearch screening to the advertising specialty to be recommended according to the user information of real-time collecting
Later, including：
The initial attribute characteristic information of the user is adjusted into Mobile state according to the user information of real-time collecting.
Optionally, the attributive character information by advertising specialty is matched with the initial attribute characteristic information of user,
Including：
Each key word information in the initial attribute characteristic information of user is ranked up one pass of generation according to weight
Keyword sequence；
It closes first key word information in the sequence is corresponding with the attributive character information of each advertising specialty
Keyword information is matched, and the current matching advertising specialty that can obtain matching keywords is selected；
Each current matching advertising specialty that next key word information in the sequence is selected with previous step again
Attributive character information in corresponding key word information matched, select matched advertising specialty；
It repeats the above steps, until the last one key word information matching in the keyword sequence terminates；
If by the keyword sequence next key word information and the category of matched advertising specialty selected
Property characteristic information in corresponding key word information can not obtain matching keywords when being matched, i.e., cannot select and more match again
Advertising specialty, then terminate matching process；
Using the matched advertising specialty finally selected as the advertising specialty to be recommended to match with user.
Optionally, the attributive character information of the advertising specialty, including：
The granting region of the advertising specialty, use environment, the advertisement position size for including, the advertisement position position for including, packet
The advertisement position background color contained and/or suitable crowd.
Optionally, the advertising specialty includes：Gift and/or gift token in kind.
Optionally, the initial attribute characteristic information of the user, including：
Age of user, gender, region, educational background, the level of consumption, advertising specialty type interested.
Optionally, the attributive character information by advertising specialty is matched with the initial attribute characteristic information of user,
Including：
By having the website platform of DSP analysis ability to the attributive character information of advertising specialty and the initial attribute of user
Characteristic information is analyzed, and the attributive character information of advertising specialty is matched with the initial attribute characteristic information of user.
Although the present invention is disclosed as above with preferred embodiment, it is not for limiting the present invention, any this field skill
Art personnel without departing from the spirit and scope of the present invention, can make possible variation and modification, therefore the guarantor of the present invention
Shield range should be subject to the range that the claims in the present invention are defined.
Claims (22)
1. a kind of advertising specialty recommends method, which is characterized in that including：
The attributive character information of advertising specialty is matched with the initial attribute characteristic information of user, is obtained and user's phase
Matched advertising specialty to be recommended；
The advertising specialty to be recommended is recommended into user；
User is received in the advertising specialty to be recommended to the selection confirmation message of advertising specialty, obtains actual recommendation advertisement gift
Product.
2. advertising specialty according to claim 1 recommends method, which is characterized in that described by the advertisement gift to be recommended
Before product recommend the step of user, including：
Postsearch screening is carried out to the advertising specialty to be recommended according to the user information of real-time collecting.
3. advertising specialty according to claim 2 recommends method, which is characterized in that the user information packet of the real-time collecting
Include at least one below：
User to the feedback information of offering question, the buying behavior information of user, the network behavior information of user, user self
Description information, other people description informations to user.
4. advertising specialty according to claim 3 recommends method, which is characterized in that feedback of the user to offering question
Information includes：
The problem of more than one is arranged, feedback the problem of according to user to having proposed, is dynamically arranged next problem.
5. advertising specialty according to claim 4 recommends method, which is characterized in that described the problem of more than one is set,
Next problem is dynamically arranged in the feedback of the problem of according to user to having proposed, including：
The problem of more than one is set, and positive feedback and negative-feedback Liang Ge feedback informations branch are arranged to each problem, if with
Family is positive feedback to the feedback information of current problem, then next problem is set as the problem corresponding to positive feedback；If user couple
The feedback information of current problem is negative-feedback, then next problem is set as the problem corresponding to negative-feedback.
6. recommending method according to claim 3 to 5 any one of them advertising specialty, which is characterized in that according to real-time collecting
User information the step of postsearch screening is carried out to the advertising specialty to be recommended after, including：
The initial attribute characteristic information of the user is adjusted into Mobile state according to the user information of real-time collecting.
7. advertising specialty according to claim 1 recommends method, which is characterized in that the attributive character by advertising specialty
Information is matched with the initial attribute characteristic information of user, including：
Each key word information in the initial attribute characteristic information of user is ranked up according to weight and generates a keyword
Sequence；
By first key word information in the sequence and corresponding keyword in the attributive character information of each advertising specialty
Information is matched, and the current matching advertising specialty that can obtain matching keywords is selected；
The category for each current matching advertising specialty that next key word information in the sequence is selected with previous step again
Property characteristic information in corresponding key word information matched, select matched advertising specialty；
It repeats the above steps, until the last one key word information matching in the keyword sequence terminates；
If the attribute of next key word information and the matched advertising specialty selected in the keyword sequence is special
Matching keywords can not be obtained when corresponding key word information is matched in reference breath, i.e., cannot be selected again more matched wide
Gift is accused, then terminates matching process；
Using the matched advertising specialty finally selected as the advertising specialty to be recommended to match with user.
8. advertising specialty according to claim 1 recommends method, which is characterized in that the attributive character of the advertising specialty is believed
Breath, including：
The granting region of the advertising specialty, the advertisement position size for including, the advertisement position position for including, includes at use environment
Advertisement position background color and/or suitable crowd.
9. advertising specialty according to claim 1 recommends method, which is characterized in that the advertising specialty includes：Gift in kind
Product and/or gift token.
10. advertising specialty according to claim 1 recommends method, which is characterized in that the initial attribute feature of the user
Information, including：
Age of user, gender, region, educational background, the level of consumption, advertising specialty type interested.
11. advertising specialty according to claim 1 recommends method, which is characterized in that the attribute by advertising specialty is special
Reference breath is matched with the initial attribute characteristic information of user, including：
By having the website platform of DSP analysis ability to the attributive character information of advertising specialty and the initial attribute feature of user
Information is analyzed, and the attributive character information of advertising specialty is matched with the initial attribute characteristic information of user.
12. a kind of advertising specialty recommendation apparatus, which is characterized in that including：
Matching characteristic information unit, for carrying out the initial attribute characteristic information of the attributive character information of advertising specialty and user
Matching obtains the advertising specialty to be recommended to match with the user；
Recommend gift unit, for the advertising specialty to be recommended to be recommended user；
Target gift unit is obtained, receives user in the advertising specialty to be recommended to the selection confirmation message of advertising specialty,
Obtain actual recommendation advertising specialty.
13. advertising specialty recommendation apparatus according to claim 11, which is characterized in that described device includes：
Postsearch screening unit, for before recommending gift cell operation, waiting pushing away to described according to the user information of real-time collecting
It recommends advertising specialty and carries out postsearch screening.
14. advertising specialty recommendation apparatus according to claim 13, which is characterized in that the user information of the real-time collecting
Including at least one below：
User to the feedback information of offering question, the buying behavior information of user, the network behavior information of user, user self
Description information, other people description informations to user.
15. advertising specialty recommendation apparatus according to claim 14, which is characterized in that the user is to the anti-of offering question
Feedforward information includes：
The problem of more than one is arranged, feedback the problem of according to user to having proposed, is dynamically arranged next problem.
16. advertising specialty recommendation apparatus according to claim 15, which is characterized in that the setting is more than one to ask
Topic, feedback the problem of according to user to having proposed, is dynamically arranged next problem, including：
The problem of more than one is set, and positive feedback and negative-feedback Liang Ge feedback informations branch are arranged to each problem, if with
Family is positive feedback to the feedback information of current problem, then next problem is set as the problem corresponding to positive feedback；If user couple
The feedback information of current problem is negative-feedback, then next problem is set as the problem corresponding to negative-feedback.
17. according to claim 14 to 16 any one of them advertising specialty recommendation apparatus, which is characterized in that according to receipts in real time
After the step of user information of collection carries out postsearch screening to the advertising specialty to be recommended, including：
The initial attribute characteristic information of the user is adjusted into Mobile state according to the user information of real-time collecting.
18. advertising specialty recommendation apparatus according to claim 12, which is characterized in that the attribute by advertising specialty is special
Reference breath is matched with the initial attribute characteristic information of user, including：
Each key word information in the initial attribute characteristic information of user is ranked up according to weight and generates a keyword
Sequence；
By first key word information in the sequence and corresponding keyword in the attributive character information of each advertising specialty
Information is matched, and the current matching advertising specialty that can obtain matching keywords is selected；
The category for each current matching advertising specialty that next key word information in the sequence is selected with previous step again
Property characteristic information in corresponding key word information matched, select matched advertising specialty；
It repeats the above steps, until the last one key word information matching in the keyword sequence terminates；
If the attribute of next key word information and the matched advertising specialty selected in the keyword sequence is special
Matching keywords can not be obtained when corresponding key word information is matched in reference breath, i.e., cannot be selected again more matched wide
Gift is accused, then terminates matching process；
Using the matched advertising specialty finally selected as the advertising specialty to be recommended to match with user.
19. advertising specialty recommendation apparatus according to claim 12, which is characterized in that the attributive character of the advertising specialty
Information, including：
The granting region of the advertising specialty, the advertisement position size for including, the advertisement position position for including, includes at use environment
Advertisement position background color and/or suitable crowd.
20. advertising specialty recommendation apparatus according to claim 12, which is characterized in that the advertising specialty includes：It is in kind
Gift and/or gift token.
21. advertising specialty recommendation apparatus according to claim 12, which is characterized in that the initial attribute feature of the user
Information, including：
Age of user, gender, region, educational background, the level of consumption, advertising specialty type interested.
22. advertising specialty recommendation apparatus according to claim 12, which is characterized in that the attribute by advertising specialty is special
Reference breath is matched with the initial attribute characteristic information of user, including：
By having the website platform of DSP analysis ability to the attributive character information of advertising specialty and the initial attribute feature of user
Information is analyzed, and the attributive character information of advertising specialty is matched with the initial attribute characteristic information of user.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2018/097424 WO2019047630A1 (en) | 2017-09-11 | 2018-07-27 | Marketing system, advertising gift recommendation method and sales sharing system |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201710812053 | 2017-09-11 | ||
| CN2017108120537 | 2017-09-11 |
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| CN108376339A true CN108376339A (en) | 2018-08-07 |
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| CN201711477925.5A Pending CN108376339A (en) | 2017-09-11 | 2017-12-29 | Advertising specialty recommends method and device |
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