CN110472843A - A kind of commercial brand health indicator balancing method and system based on big data - Google Patents
A kind of commercial brand health indicator balancing method and system based on big data Download PDFInfo
- Publication number
- CN110472843A CN110472843A CN201910691915.4A CN201910691915A CN110472843A CN 110472843 A CN110472843 A CN 110472843A CN 201910691915 A CN201910691915 A CN 201910691915A CN 110472843 A CN110472843 A CN 110472843A
- Authority
- CN
- China
- Prior art keywords
- product
- information
- health indicator
- data
- collection terminal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000036541 health Effects 0.000 title claims abstract description 116
- 238000000034 method Methods 0.000 title claims abstract description 69
- 230000008569 process Effects 0.000 claims abstract description 39
- 230000004807 localization Effects 0.000 claims abstract description 38
- 238000012545 processing Methods 0.000 claims description 55
- 230000000694 effects Effects 0.000 claims description 17
- 238000009826 distribution Methods 0.000 claims description 14
- 238000005259 measurement Methods 0.000 claims description 12
- 230000004069 differentiation Effects 0.000 claims description 10
- 238000005457 optimization Methods 0.000 claims description 9
- 238000013528 artificial neural network Methods 0.000 claims description 6
- 238000013480 data collection Methods 0.000 claims description 6
- 235000013399 edible fruits Nutrition 0.000 claims description 4
- 239000000725 suspension Substances 0.000 claims description 2
- 238000005303 weighing Methods 0.000 claims 1
- 238000011161 development Methods 0.000 description 8
- 239000011159 matrix material Substances 0.000 description 7
- 238000007405 data analysis Methods 0.000 description 6
- PCHJSUWPFVWCPO-UHFFFAOYSA-N gold Chemical compound [Au] PCHJSUWPFVWCPO-UHFFFAOYSA-N 0.000 description 5
- 239000010931 gold Substances 0.000 description 5
- 229910052737 gold Inorganic materials 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 4
- 239000000203 mixture Substances 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 238000009472 formulation Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 230000002860 competitive effect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 241001672694 Citrus reticulata Species 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000019771 cognition Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 230000004907 flux Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- 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
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0202—Market predictions or forecasting for commercial activities
Abstract
The present invention provides a kind of commercial brand health indicator balancing method based on big data, the commercial brand health indicator balancing method based on big data includes the following steps: step (1), if passing through collection terminal under collection terminal on main line and/or line, several different types of feedback data information about a certain product are obtained, and several different types of feedback data information are carried out to mark localization process；Step (2), according to this to mark localization process as a result, determining the linked character data between several different types of feedback data information and the product；Step (3) determines that the corresponding health indicator of the product measures curve model, and obtain the corresponding health indicator variation tendency information of the product with this according to the linked character data.
Description
Technical field
The present invention relates to the technical field of big data analysis, in particular to a kind of commercial brand health based on big data refers to
Mark balancing method and system.
Background technique
Under the epoch of digital economy, market environment and customer demand all change constantly, in order to realize certainly
Body commercial brand occupies vantage point in market competition, and enterprise needs according to market environment, customer demand and itself brand feelings
The difference factor such as condition carries out the in due course adjustment of business strategy.Currently, most of enterprise is all of equal value simply by giving a discount or making a price reduction
Lattice competitive way improves the occupation rate of market of itself brand, but the mode of this Price-dependent war can only obtain in a short time
The value of itself brand cannot but be effectively improved in the long run by obtaining some effects, and also result in the bad of commercial brand
Change.As it can be seen that a kind of side that can effectively carry out accurately and quickly measurement and positioning to itself commercial brand is badly in need of at present in enterprise
Method and system.
Summary of the invention
In view of the defects existing in the prior art, the present invention provides a kind of commercial brand health indicator measurement based on big data
Method and system, should commercial brand health indicator balancing method and system based on big data by line and/or under line into
The acquisition of row commercial brand related data obtains, and carries out corresponding big data analysis processing to the initial data collected,
It is obtained in time with this and needs the analysis of equal different aspects about market environment and client as a result, being directed to be more advantageous to enterprise
The market of the commercial brand of the formulation and adjustment and raising enterprise of market environment and customer demand the progress business strategy of variation
Competitiveness.Wherein, it is somebody's turn to do the commercial brand health indicator balancing method based on big data and includes the following steps: step (1), if by
Collection terminal under collection terminal and/or line, obtains several different types of feedback data information about a certain product, and right on main line
Several different types of feedback data information are carried out to mark localization process；Step (2), according to the knot to mark localization process
Fruit determines the linked character data between several different types of feedback data information and the product；Step (3), according to this
Linked character data determine that the corresponding health indicator of the product measures curve model, and obtain the corresponding health of the product with this
Index variation tendency information, the commercial brand health indicator balancing method are obtained by big data analysis about itself brand development
Golden curve model, and the healthy measurement index of itself brand is obtained according to the golden curve model, the health measurement index
It can intuitively reflect the state of development of brand, so that enterprise can carry out the quotient of adaptability according to the health measurement index
Industry decision.
The present invention provides a kind of commercial brand health indicator balancing method based on big data, which is characterized in that the base
Include the following steps: in the commercial brand health indicator balancing method of big data
Step (1), if obtaining several differences about a certain product by collection terminal under collection terminal on main line and/or line
The feedback data information of type, and several different types of feedback data information are carried out to mark localization process；
Step (2), according to described pair mark localization process as a result, determining several different types of feedback data information
Linked character data between the product；
Step (3) determines that the corresponding health indicator of the product measures curve model according to the linked character data,
And the corresponding health indicator variation tendency information of the product is obtained with this；
Further, in the step (1), if being obtained by collection terminal under collection terminal on main line and/or line about a certain
Several different types of feedback data information of product, and several different types of feedback data information are carried out to calibration
Position processing specifically includes,
Step (101), obtains the attribute information of the product, and if adopting according on the determining main line of the attribute information
Collect the data acquisition scheme of collection terminal under end and/or line, while also judging that the data acquisition scheme and the product are current
Whether matching between distribution state；
Step (102), if according to the data acquisition scheme and the matching judgment as a result, being acquired on the main line
Each of collection terminal sends acquisition indication signal under end and/or line, if under collection terminal on the control main line and/or line
Each of collection terminal executes the feedback data information collection operation of adaptability；
Step (103) carries out suitable modules differentiation to several different types of feedback data information collected
Processing, and distinguish handling according to the suitable modules as a result, executing described pair of mark localization process；
Further, in the step (101), the attribute information of the product is obtained, and true according to the attribute information
If on the main line under collection terminal and/or line collection terminal data acquisition scheme, while also judging the data acquisition scheme
It is specifically included whether matching between the distribution state current with the product,
Step (1011) obtains price, purposes, sales volume and the shelf life of the product as the attribute information, and
The attribute information and default expected product marketing model are compared into processing, with this obtain the product and expected product it
Between different information；
Step (1012) acquires on the main line according to the different information between the product and expected product if determining
Under end and/or line in the layout areas range of collection terminal, data collection type, data acquisition target and data acquiring frequency extremely
Few one, so as to form the data acquisition scheme；
Step (1013) obtains the current sales volume of the product, consumption sum and at least one of feedback is made after sale
For the current distribution state of the product, and the data acquisition scheme distribution state current with the product is matched
Processing；
Alternatively,
In the step (102), according to the data acquisition module and the matching judgment as a result, to described several
Each of collection terminal sends acquisition indication signal under collection terminal and/or line on line, if to control collection terminal on the main line
And/or the feedback data information collection operation that each of collection terminal executes adaptability under line specifically includes,
Step (1021), judges whether the data acquisition scheme matches with the current distribution state of the product, if two
Person matches, if then each of collection terminal sends the first acquisition indication signal under collection terminal and/or line on Xiang Suoshu main line,
If the two mismatches, if each of collection terminal sends the second acquisition instruction under collection terminal and/or line on Xiang Suoshu main line
Signal；
Step (1022), if each of collection terminal is adopted according to described first under collection terminal and/or line on the main line
Collect the feedback data information collection operation that indication signal executes preset mode；
Step (1023), if each of collection terminal is adopted according to described second under collection terminal and/or line on the main line
Collect indication signal pause or the/current feedback data information collection of termination operates；
Alternatively,
In the step (103), several different types of feedback data information collected are carried out applicable
Module differentiation processing, and specifically including as a result, executing described pair of mark localization process for processing is distinguished according to the suitable modules,
Step (1031) carries out about consumer layer several different types of feedback data information collected
Face, medium propagation level, line are put up at an inn the block region of roofing, product itself level, brand effect level and industry category level
Divide processing；
Several different types of feedback data information are distinguished processing knot according to the module of its own by step (1032)
Fruit executes default level metrics-thresholds comparison accordingly, realizes described pair of mark localization process with this, to obtain corresponding feedback
Data information is to mark positioning result；
Further, in the step (2), according to described pair mark localization process as a result, determining several inhomogeneities
Linked character data between the feedback data information and the product of type specifically include,
Step (201), according to described pair mark localization process as a result, consumer layer where determining the feedback data information
Face, medium propagation level, line put up at an inn roofing, product itself level, brand effect level or industry category level mutually it
Between associated path information；
Step (202) determines the feedback data according to the corresponding associated path information of the feedback data information
The corresponding product of information is put up at an inn roofing, the product itself in the consumer level, the medium propagation level, the line
The close angle value of association of level, the brand effect level and the industry category level；
Step (203), using the associated path information and the close angle value of association as the linked character data, and
The linked character data are carried out with the mark processing of corresponding product information；
Further, in the step (3), according to the linked character data, determine that the corresponding health of the product refers to
Mark measures curve model, and obtains the corresponding health indicator variation tendency information of the product with this and specifically include,
The linked character data are measured the defeated of neural network by step (301)
Enter source data, determines that the health indicator measures curve model with this；
Step (302) is measured curve model to the health indicator and move about the timeliness of the linked character data
The optimization processing that curve model is measured to the health indicator is realized in state adjustment with this；
Step (303) is measured curve model based on the health indicator Jing Guo the optimization processing, is calculated described in obtaining
The corresponding health indicator variation tendency information of product.
The present invention also provides a kind of, and the commercial brand health indicator based on big data measures system, it is characterised in that:
If if the commercial brand health indicator based on big data measures system including under acquisition module, main line on main line
Acquisition module, to calibration position processing module, linked character data determining module and health indicator determining module；Wherein,
If if if on the main line under acquisition module and/or the main line acquisition module for obtaining about a certain product
Do different types of feedback data information；
Described pair of calibration position processing module is used to carry out several different types of feedback data information to calibration position
Processing；
The linked character data determining module be used for according to described pair mark localization process as a result, determine it is described it is several not
Linked character data between the feedback data information and the product of same type；
The health indicator determining module is used to determine that the corresponding health of the product refers to according to the linked character data
Mark measures curve model, and obtains the corresponding health indicator variation tendency information of the product with this；
Further, if if each of acquisition module includes data under acquisition module or the main line on the main line
Acquisition mode determines that submodule and suitable modules distinguish processing submodule；Wherein,
If the acquisition mode determine submodule for according to the attribute information of product determine on the main line collection terminal and/
Or under line collection terminal data acquisition scheme；
The suitable modules are distinguished processing submodule and are used for several different types of feedback data collected
Information carries out suitable modules differentiation processing；
Described pair of calibration position processing module is also used to distinguish marking as a result, executing described pair for processing according to the suitable modules
Localization process；
Further, if if each of acquisition module further includes producing under acquisition module or the main line on the main line
Product attribute acquisition submodule and different information acquisition submodule；Wherein,
The product attribute acquisition submodule is used to obtain price, purposes, sales volume and the shelf life conduct of the product
The attribute information；
The different information acquisition submodule is used to carry out the attribute information and default expected product marketing model pair
Than processing, the different information between the product and expected product is obtained with this；
The acquisition mode determines that submodule is also used to determine according to the different information between the product and expected product
If on the main line under collection terminal and/or line collection terminal layout areas range, data collection type, data acquisition target sum number
According at least one of frequency acquisition, so as to form the data acquisition scheme；
Further, the linked character data determining module includes associated path acquisition of information submodule and be associated with degree closely
It is worth acquisition submodule；Wherein,
The associated path acquisition of information submodule be used for according to described pair mark localization process as a result, determining the feedback
Consumer level where data information, medium propagation level, line put up at an inn roofing, product itself level, brand effect level or
The mutual associated path information of person's industry category level；
The close angle value acquisition submodule of association is used for according to the corresponding associated path of the feedback data information
Information determines the corresponding product of the feedback data information under the consumer level, the medium propagation level, the line
Shop level, the product itself level, the close angle value of association of the brand effect level and the industry category level；
The linked character data determining module is also used to make the associated path information and the close angle value of association
For the linked character data, and the mark for carrying out corresponding product information to the linked character data is handled；
Further, the health indicator determining module includes that health indicator measurement curve model determines that submodule and health refer to
Mark variation tendency computational submodule；Wherein,
The health indicator measures curve model and determines submodule for using the linked character data as default business
Brand health indicator measures the input source data of neural network, determines that the health indicator measures curve model with this；
The health indicator variation tendency computational submodule is used to measure by the health indicator Jing Guo optimization processing
Curve model calculates and obtains the corresponding health indicator variation tendency information of the product.
Compared with the prior art, should pass through on line in the commercial brand health indicator balancing method and system of big data
And/or the acquisition acquisition of commercial brand related data is carried out under line, and corresponding big number is carried out to the initial data collected
It is handled according to analysis, is obtained in time with this and need the analysis of equal different aspects about market environment and client as a result, to more have
Conducive to enterprise for the formulation and adjustment of market environment and customer demand the progress business strategy of variation and the quotient for improving enterprise
The market competitiveness of industry brand.Wherein, the commercial brand health indicator balancing method based on big data is somebody's turn to do to include the following steps: to walk
Suddenly (1), if obtaining several different types of feedbacks about a certain product by collection terminal under collection terminal on main line and/or line
Data information, and several different types of feedback data information are carried out to mark localization process；Step (2), according to this to mark
Localization process as a result, determining the linked character data between several different types of feedback data information and the product；Step
Suddenly (3) determine that the corresponding health indicator of the product measures curve model, and obtain the production with this according to the linked character data
The corresponding health indicator variation tendency information of product, the commercial brand health indicator balancing method by big data analysis obtain about
The golden curve model of itself brand development, and the healthy measurement index of itself brand is obtained according to the golden curve model, it should
Healthy measurement index can intuitively reflect the state of development of brand so that enterprise can according to the health measurement index into
The business decision of row adaptability.
Other features and advantages of the present invention will be illustrated in the following description, also, partly becomes from specification
It obtains it is clear that understand through the implementation of the invention.The objectives and other advantages of the invention can be by written explanation
Specifically noted structure is achieved and obtained in book, claims and attached drawing.
Below by drawings and examples, technical scheme of the present invention will be described in further detail.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
It obtains other drawings based on these drawings.
Fig. 1 is a kind of process signal of commercial brand health indicator balancing method based on big data provided by the invention
Figure.
Fig. 2 is the structural representation that a kind of commercial brand health indicator based on big data provided by the invention measures system
Figure.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
It refering to fig. 1, is a kind of commercial brand health indicator balancing method based on big data provided in an embodiment of the present invention
Flow diagram.The commercial brand health indicator balancing method based on big data includes the following steps:
Step (1), if obtaining several differences about a certain product by collection terminal under collection terminal on main line and/or line
The feedback data information of type, and several different types of feedback data information are carried out to mark localization process.
Preferably, in the step (1), if being obtained by collection terminal under collection terminal on main line and/or line about a certain production
Several different types of feedback data information of product, and several different types of feedback data information are carried out at calibration position
Reason specifically includes,
Step (101), obtains the attribute information of the product, and if being somebody's turn to do collection terminal on main line according to the attribute information is determining
And/or under line collection terminal data acquisition scheme, while also judging the data acquisition scheme and the current distribution state of the product
Between whether match；
Step (102), if according to the data acquisition scheme and the matching judgment as a result, on the main line collection terminal and/
Or each of collection terminal sends acquisition indication signal under line, if with collection terminal under collection terminal on the control main line and/or line
Each of execute adaptability feedback data information collection operation；
Step (103) carries out at suitable modules differentiation several different types of feedback data information collected
Reason, and distinguish handling according to the suitable modules as a result, executing this to mark localization process.
Preferably, in the step (101), the attribute information of the product is obtained, and if being somebody's turn to do according to the attribute information is determining
On main line under collection terminal and/or line collection terminal data acquisition scheme, while also judging that the data acquisition scheme is worked as with the product
It is specifically included whether matching between preceding distribution state,
Step (1011) obtains price, purposes, sales volume and the shelf life of the product as the attribute information, and should
Attribute information and default expected product marketing model compare processing, obtain the difference between the product and expected product with this
Information；
Step (1012), according to the different information between the product and expected product, if determine should on main line collection terminal and/
Or under line in the layout areas range of collection terminal, data collection type, data acquisition target and data acquiring frequency at least one
Person, so as to form the data acquisition scheme；
Step (1013) obtains the current sales volume of the product, consumption sum and at least one of feedback conduct after sale
The current distribution state of the product, and the current distribution state of the data acquisition scheme and the product is subjected to matching treatment.
Preferably, in the step (102), according to the data acquisition module with the matching judgment as a result, several to this
Each of collection terminal sends acquisition indication signal under collection terminal and/or line on line, if with control should on main line collection terminal and/
Or the feedback data information collection operation that each of collection terminal executes adaptability under line specifically includes,
Step (1021), judges whether the data acquisition scheme matches with the current distribution state of the product, if the two phase
Matching, if then each of collection terminal sends the first acquisition indication signal under collection terminal and/or line on the main line, if the two
It mismatches, if then each of collection terminal sends the second acquisition indication signal under collection terminal and/or line on the main line；
Step (1022), if should each of collection terminal refers to according to first acquisition under collection terminal and/or line on main line
Show that signal executes the feedback data information collection operation of preset mode；
Step (1023), if should each of collection terminal refers to according to second acquisition under collection terminal and/or line on main line
Show that signal suspension or the/current feedback data information collection of termination operate.
Preferably, in the step (103), several different types of feedback data information collected are fitted
It is handled with module differentiation, and distinguishes specifically including as a result, executing this to mark localization process for processing according to the suitable modules,
Step (1031) carries out about consumer layer several different types of feedback data information collected
Face, medium propagation level, line are put up at an inn the block region of roofing, product itself level, brand effect level and industry category level
Divide processing；
Several different types of feedback data information are distinguished processing knot according to the module of its own by step (1032)
Fruit executes default level metrics-thresholds comparison accordingly, realizes this to mark localization process, to obtain corresponding feedback coefficient with this
It is believed that breath is to mark positioning result.
Step (2), according to this to mark localization process as a result, determine several different types of feedback data information with should
Linked character data between product.
Preferably, in the step (2), according to this to mark localization process as a result, determining that this is several different types of anti-
Linked character data between feedback data information and the product specifically include,
Step (201), according to this to mark localization process as a result, consumer level where determining feedback data information,
Put up at an inn roofing, product itself level, brand effect level or industry category level of medium propagation level, line is mutual
Associated path information；
Step (202) determines the feedback data information pair according to the corresponding associated path information of the feedback data information
The product answered is put up at an inn roofing, the product itself level, brand effect in the consumer level, the medium propagation level, the line
Answer the close angle value of association of level and the sector category level；
Step (203) is associated with close angle value using the associated path information with this as the linked character data, and to the pass
Join the mark processing that characteristic carries out corresponding product information.
Step (3) determines that the corresponding health indicator of the product measures curve model according to the linked character data, and with
This obtains the corresponding health indicator variation tendency information of the product.
Preferably, in the step (3), according to the linked character data, determine that the corresponding health indicator of the product is measured
Curve model, and the corresponding health indicator variation tendency information of the product is obtained with this and is specifically included,
Step (301) measures the input of neural network using the linked character data as default commercial brand health indicator
Source data determines that the health indicator measures curve model with this；
Step (302) is measured curve model to the health indicator and adjust about the timeliness dynamic of the linked character data
It is whole, the optimization processing that curve model is measured to the health indicator is realized with this；
Step (303) measures curve model based on the health indicator Jing Guo the optimization processing, calculates and obtain the product pair
The health indicator variation tendency information answered.
Referring to Fig.2, for a kind of commercial brand health indicator measurement system based on big data provided in an embodiment of the present invention
Structural schematic diagram.If the commercial brand health indicator based on big data measure system include acquisition module on main line, it is several
Acquisition module under line, to calibration position processing module, linked character data determining module and health indicator determining module.Wherein,
If if on the main line acquisition module and/or should under main line acquisition module be used to obtain about a certain product it is several not
The feedback data information of same type；
This is used to carry out several different types of feedback data information to mark localization process to calibration position processing module；
The linked character data determining module is used for according to this to mark localization process as a result, determining several different types
Feedback data information and the product between linked character data；
The health indicator determining module is used to determine that the corresponding health indicator of the product is measured according to the linked character data
Curve model, and the corresponding health indicator variation tendency information of the product is obtained with this.
It preferably, if if should acquisition module or should each of acquisition module include that data acquire under main line on main line
Mode determines that submodule and suitable modules distinguish processing submodule；
Preferably, if the acquisition mode determines that submodule is somebody's turn to do collection terminal on main line for determining according to the attribute information of product
And/or under line collection terminal data acquisition scheme；
Preferably, which distinguishes processing submodule and is used for several different types of feedback coefficients collected
It is believed that breath carries out suitable modules differentiation processing；
Preferably, this to calibration position processing module be also used to be distinguished according to the suitable modules processing as a result, to execute this right
Mark localization process；
It preferably, if if should acquisition module or should each of acquisition module further include product category under main line on main line
Property acquisition submodule and different information acquisition submodule；
Preferably, price, purposes, sales volume and the shelf life which is used to obtain the product are made
For the attribute information；
Preferably, which is used to carry out the attribute information and default expected product marketing model
Comparison processing, obtains the different information between the product and expected product with this；
Preferably, which determines that submodule is also used to according to the different information between the product and expected product,
If determine the layout areas range of collection terminal under collection terminal on the main line and/or line, data collection type, data acquisition target and
At least one of data acquiring frequency, so as to form the data acquisition scheme；
Preferably, which includes associated path acquisition of information submodule and be associated with close angle value
Acquisition submodule；
Preferably, which is used for according to this to mark localization process as a result, determining that this is anti-
Consumer level where feedback data information, medium propagation level, line put up at an inn roofing, product itself level, brand effect level
Or the associated path information that industry category level is mutual；
Preferably, the close angle value acquisition submodule of the association is used for according to the corresponding associated path of the feedback data information
Information determines that the corresponding product of feedback data information is put up at an inn laying in the consumer level, the medium propagation level, the line
Face, the product itself level, the close angle value of association of the brand effect level and the sector category level；
Preferably, which is also used to for the associated path information being associated with close angle value with this and makees
For the linked character data, and the mark for carrying out corresponding product information to the linked character data is handled；
Preferably, which includes that health indicator measurement curve model determines submodule and health indicator
Variation tendency computational submodule；
Preferably, which measures curve model and determines that submodule is used for using the linked character data as default quotient
Industry brand health indicator measures the input source data of neural network, determines that the health indicator measures curve model with this；
Preferably, which is used to weigh by the health indicator Jing Guo optimization processing
Curve model is measured, calculates and obtains the corresponding health indicator variation tendency information of the product.
In practical applications, it is somebody's turn to do commercial brand health indicator balancing method and system based on big data, from category, product
Board, product, shop, medium, consumer this six big module are studied, and " picture " goes out the health of category industry development " gold is bent
Line " then carries out obtaining pair of brand side's corresponding index and " golden curve " to mark according to the category industry that brand side is in
Than understanding problem and shortcoming of our the brand side on related section, being analyzed further according to the problem of fining, propose plan
Slightly property suggestion carries out Developing Tactics further according to the current own situation in brand side, finds the solution that can be landed.For example, needle
The old and new visitor of healthy brand, which is constituted, from the point of view of purchase crowd, in industry flows in and out in a steady upward " gold song
Line " becomes a mandarin artificial situation to the old and new's passenger flow of mark brand side itself, it can be seen that in the operation of the old and new visitor, brand side whether be
" health "；In addition, the consumer of brand can be done base categories according to the behavior of " people " " field " " goods ", wherein being divided into brand
Cognition crowd A (Aware), interest crowd I (Interest) are bought P (Purchase), loyal L (Loyal), are directed to disappear at present
This six big respective parser matrix of module of Fei Zhe, medium, shop, product, brand and category relates separately to different factors.
It specifically, may include that AIPL framework, attribute structure, circulation link and the old and new care for for the parser matrix for consumer
The difference factor such as visitor may include the selection of gold medium, gold media mix and gold for the parser matrix for medium
The difference factor such as TA concentration, may include Flux efficiency for the parser matrix for shop, and action number accounting, investment produce
Out than factors different with shop type etc., it may include value and quantity for the parser matrix for product, purchase efficiency again
With product orientation with the different factors such as combine, may include brand value, brand competition for the parser matrix for brand
The difference factor such as power and brand promotion channel may include that industry and brand, category are purchased for the parser matrix for category
Buy the different factors such as opportunity and category competitive opportunity.
The commercial brand health indicator balancing method market department and electricity suitable for brand synchronous with system in big data
Quotient department, and can help into the high-rise N planning and current year planning for confirming itself brand by these indexs of brand side
Integrated planning and assessment to brand " product " " effect " help marketing and the topic of operation level of the brand side gradually from thousand layers, into
One step rises to strategic subject under discussion, and the operation of brand is risen to brand consumption person's assets, product from the pure flow operation of electric business
Come in board overall value and brand business scale, expands to full channel service from online service, further rely on new technology, it is perfect
The digitlization ecosystem of brand, additionally it is possible to be required, be provided according to difference of the different category different brands for brand development
Methodology itself can be assessed, and can measure, sustainable operation.
From above-described embodiment as can be seen that the commercial brand health indicator balancing method and system based on big data pass through
The acquisition for carrying out commercial brand related data on line and/or under line obtains, and carries out to the initial data collected corresponding
Big data analysis processing, obtained in time with this about market environment and client need equal different aspects analysis as a result, from
And enterprise is more advantageous to for the formulation and adjustment of market environment and customer demand the progress business strategy of variation and improves enterprise
The market competitiveness of the commercial brand of industry；The commercial brand health indicator balancing method and system are also obtained by big data analysis
About the golden curve model of itself brand development, and is measured and referred to according to the health that the golden curve model obtains itself brand
Mark, which can intuitively reflect the state of development of brand, so that enterprise can measure according to the health
The business decision of index progress adaptability.
Obviously, various changes and modifications can be made to the invention without departing from essence of the invention by those skilled in the art
Mind and range.In this way, if these modifications and changes of the present invention belongs to the range of the claims in the present invention and its equivalent technologies
Within, then the present invention is also intended to include these modifications and variations.
Claims (10)
1. a kind of commercial brand health indicator balancing method based on big data, which is characterized in that the quotient based on big data
Industry brand health indicator balancing method includes the following steps:
Step (1), if obtaining several different types about a certain product by collection terminal under collection terminal on main line and/or line
Feedback data information, and to several different types of feedback data information carry out to mark localization process；
Step (2), according to described pair mark localization process as a result, determining several different types of feedback data information and institute
State the linked character data between product；
Step (3) determines that the corresponding health indicator of the product measures curve model according to the linked character data, and with
This obtains the corresponding health indicator variation tendency information of the product.
2. the commercial brand health indicator balancing method based on big data as described in claim 1, it is characterised in that:
In the step (1), if being obtained by collection terminal under collection terminal on main line and/or line about the several of a certain product
Different types of feedback data information, and several different types of feedback data information are carried out specific to mark localization process
Including,
Step (101), obtains the attribute information of the product, and if determining collection terminal on the main line according to the attribute information
And/or under line collection terminal data acquisition scheme, while also judging the data acquisition scheme and the current sale of the product
Whether matching between state；
Step (102), if according to the data acquisition scheme and the matching judgment as a result, on the main line collection terminal
And/or each of collection terminal sends acquisition indication signal under line, if being adopted under collection terminal and/or line on the main line with controlling
Collect the feedback data information collection operation that each of end executes adaptability；
Step (103) carries out suitable modules differentiation processing to several different types of feedback data information collected,
And distinguish handling according to the suitable modules as a result, executing described pair of mark localization process.
3. the commercial brand health indicator balancing method based on big data as claimed in claim 2, it is characterised in that:
In the step (101), the attribute information of the product is obtained, and if determining the main line according to the attribute information
The data acquisition scheme of collection terminal under upper collection terminal and/or line, while also judging that the data acquisition scheme is worked as with the product
It is specifically included whether matching between preceding distribution state,
Step (1011) obtains price, purposes, sales volume and the shelf life of the product as the attribute information, and by institute
It states attribute information and default expected product marketing model compares processing, obtained between the product and expected product with this
Different information；
Step (1012), according to the different information between the product and expected product, if determine on the main line collection terminal and/
Or under line in the layout areas range of collection terminal, data collection type, data acquisition target and data acquiring frequency at least one
Person, so as to form the data acquisition scheme；
Step (1013) obtains the current sales volume of the product, consumption sum and at least one of feedback after sale as institute
The current distribution state of product is stated, and the data acquisition scheme and the current distribution state of the product are carried out at matching
Reason；
Alternatively,
In the step (102), if according to the data acquisition module and the matching judgment as a result, on the main line
Each of collection terminal sends acquisition indication signal under collection terminal and/or line, if with control on the main line collection terminal and/or
The feedback data information collection operation that each of collection terminal executes adaptability under line specifically includes,
Step (1021), judges whether the data acquisition scheme matches with the current distribution state of the product, if the two phase
Matching, if then each of collection terminal sends the first acquisition indication signal under collection terminal and/or line on Xiang Suoshu main line, if two
Person mismatches, if then each of collection terminal sends the second acquisition indication signal under collection terminal and/or line on Xiang Suoshu main line；
Step (1022), if each of collection terminal refers to according to first acquisition under collection terminal and/or line on the main line
Show that signal executes the feedback data information collection operation of preset mode；
Step (1023), if each of collection terminal refers to according to second acquisition under collection terminal and/or line on the main line
Show that signal suspension or the/current feedback data information collection of termination operate；
Alternatively,
In the step (103), suitable modules are carried out to several different types of feedback data information collected
Differentiation processing, and specifically including as a result, executing described pair of mark localization process for processing is distinguished according to the suitable modules,
Step (1031), to several different types of feedback data information collected carry out about consumer level,
Medium propagation level, line put up at an inn roofing, product itself level, brand effect level and industry category level module differentiation at
Reason；
Several different types of feedback data information are distinguished processing result according to the module of its own by step (1032),
Default level metrics-thresholds comparison accordingly is executed, described pair of mark localization process is realized with this, to obtain corresponding feedback coefficient
It is believed that breath is to mark positioning result.
4. the commercial brand health indicator balancing method based on big data as described in claim 1, it is characterised in that:
In the step (2), according to described pair mark localization process as a result, determining several different types of feedback data
Linked character data between information and the product specifically include, step (201), and the knot of localization process is marked according to described pair
Fruit, consumer level where determining the feedback data information, medium propagation level, line put up at an inn roofing, product itself level,
Brand effect level or the mutual associated path information of industry category level；
Step (202) determines the feedback data information according to the corresponding associated path information of the feedback data information
Corresponding product is put up at an inn roofing, the product own layer in the consumer level, the medium propagation level, the line
The close angle value of association in face, the brand effect level and the industry category level；
Step (203), using the associated path information and the close angle value of association as the linked character data, and to institute
State the mark processing that linked character data carry out corresponding product information.
5. the commercial brand health indicator balancing method based on big data as described in claim 1, it is characterised in that:
In the step (3), according to the linked character data, determine that the corresponding health indicator of the product measures curvilinear mold
Type, and the corresponding health indicator variation tendency information of the product is obtained with this and is specifically included,
Step (301) measures the input source of neural network using the linked character data as default commercial brand health indicator
Data determine that the health indicator measures curve model with this；
Step (302) is measured curve model to the health indicator and adjust about the timeliness dynamic of the linked character data
It is whole, the optimization processing that curve model is measured to the health indicator is realized with this；
Step (303) measures curve model based on the health indicator Jing Guo the optimization processing, calculates and obtain the product
Corresponding health indicator variation tendency information.
6. a kind of commercial brand health indicator based on big data measures system, it is characterised in that:
If if it includes acquiring under acquisition module, main line on main line that the commercial brand health indicator based on big data, which measures system,
Module, to calibration position processing module, linked character data determining module and health indicator determining module；Wherein,
If if on the main line under acquisition module and/or the main line acquisition module be used to obtain about a certain product it is several not
The feedback data information of same type；
Described pair of calibration position processing module is used to carry out several different types of feedback data information to mark localization process；
The linked character data determining module be used for according to described pair mark localization process as a result, determining several inhomogeneities
Linked character data between the feedback data information and the product of type；
The health indicator determining module is used to determine the corresponding health indicator weighing apparatus of the product according to the linked character data
Curve model is measured, and the corresponding health indicator variation tendency information of the product is obtained with this.
7. the commercial brand health indicator based on big data measures system as claimed in claim 6, it is characterised in that:
If if each of acquisition module includes that data acquisition scheme is true under acquisition module or the main line on the main line
Stator modules and suitable modules distinguish processing submodule；Wherein, the acquisition mode determines submodule for the category according to product
If property information determines the data acquisition scheme of collection terminal under collection terminal on the main line and/or line；
The suitable modules are distinguished processing submodule and are used for several different types of feedback data information collected
Carry out suitable modules differentiation processing；
Described pair of calibration position processing module is also used to distinguish handling according to the suitable modules as a result, executing described pair of calibration position
Processing.
8. the commercial brand health indicator based on big data measures system as claimed in claim 7, it is characterised in that:
If if each of acquisition module further includes that product attribute obtains under acquisition module or the main line on the main line
Submodule and different information acquisition submodule；Wherein,
Described in price, purposes, sales volume and the shelf life that the product attribute acquisition submodule is used to obtain the product are used as
Attribute information；
The different information acquisition submodule is used to the attribute information and default expected product marketing model comparing place
Reason, obtains the different information between the product and expected product with this；
The acquisition mode determines that submodule is also used to according to the different information between the product and expected product, determine described in
If layout areas range, data collection type, data acquisition target and the data of collection terminal are adopted under collection terminal and/or line on main line
Collect at least one of frequency, so as to form the data acquisition scheme.
9. the commercial brand health indicator based on big data measures system as claimed in claim 6, it is characterised in that:
The linked character data determining module includes associated path acquisition of information submodule and be associated with close angle value and obtain submodule
Block；Wherein,
The associated path acquisition of information submodule be used for according to described pair mark localization process as a result, determining the feedback data
Consumer level where information, medium propagation level, line put up at an inn roofing, product itself level, brand effect level or row
The mutual associated path information of industry category level；
The close angle value acquisition submodule of association is used for according to the corresponding associated path information of the feedback data information,
Determine the corresponding product of feedback data information shop under the consumer level, the medium propagation level, the line
Level, the product itself level, the close angle value of association of the brand effect level and the industry category level；
The linked character data determining module is also used to using the associated path information and the close angle value of association as institute
Linked character data are stated, and the mark for carrying out corresponding product information to the linked character data is handled.
10. the commercial brand health indicator based on big data measures system as claimed in claim 6, it is characterised in that:
The health indicator determining module includes that health indicator measurement curve model determines submodule and health indicator variation tendency
Computational submodule；Wherein,
The health indicator measures curve model and determines submodule for using the linked character data as default commercial brand
Health indicator measures the input source data of neural network, determines that the health indicator measures curve model with this；
The health indicator variation tendency computational submodule is used to measure curve by the health indicator Jing Guo optimization processing
Model calculates and obtains the corresponding health indicator variation tendency information of the product.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910691915.4A CN110472843A (en) | 2019-07-30 | 2019-07-30 | A kind of commercial brand health indicator balancing method and system based on big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910691915.4A CN110472843A (en) | 2019-07-30 | 2019-07-30 | A kind of commercial brand health indicator balancing method and system based on big data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110472843A true CN110472843A (en) | 2019-11-19 |
Family
ID=68509105
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910691915.4A Pending CN110472843A (en) | 2019-07-30 | 2019-07-30 | A kind of commercial brand health indicator balancing method and system based on big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110472843A (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090259518A1 (en) * | 2008-04-14 | 2009-10-15 | Tra, Inc. | Analyzing return on investment of advertising campaigns using cross-correlation of multiple data sources |
| US20110178839A1 (en) * | 2010-01-20 | 2011-07-21 | Adra Hosni I | Method and system for evaluating a consumer product based on web-searchable criteria |
| CN104978665A (en) * | 2015-06-16 | 2015-10-14 | 北京畅游天下网络技术有限公司 | Brand evaluation method and brand evaluation device |
-
2019
- 2019-07-30 CN CN201910691915.4A patent/CN110472843A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090259518A1 (en) * | 2008-04-14 | 2009-10-15 | Tra, Inc. | Analyzing return on investment of advertising campaigns using cross-correlation of multiple data sources |
| US20110178839A1 (en) * | 2010-01-20 | 2011-07-21 | Adra Hosni I | Method and system for evaluating a consumer product based on web-searchable criteria |
| CN104978665A (en) * | 2015-06-16 | 2015-10-14 | 北京畅游天下网络技术有限公司 | Brand evaluation method and brand evaluation device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Ha et al. | Channel structures of online retail platforms | |
| Ren et al. | Modeling customer bounded rationality in operations management: A review and research opportunities | |
| Broda et al. | Identifying the relationship between trade and exchange rate volatility | |
| Drysdale et al. | Trade intensities and the analysis of bilateral trade flows in a many-country world: A survey | |
| Caswell et al. | Unifying two frameworks for analyzing quality and quality assurance for food products | |
| JP6231204B2 (en) | Generating similarity between items | |
| Narasimhan et al. | A dynamic model of product quality and pricing decisions on sales response | |
| CN102707024B (en) | Construction method of tilapia fillet quality evaluation model based on proteins and enzymes in muscle | |
| CN107240005A (en) | The commending system and method for air ticket addition product | |
| CN107665448A (en) | For determining the method, apparatus and storage medium of consumption contributed value | |
| CN109902441A (en) | A kind of vehicle performance index weights distribution system and method based on KANO modular concept | |
| Ingene et al. | Manufacturer-optimal wholesale pricing when retailers compete | |
| Claudia | A Decomposed Model of Consumers' Intention to Continue Buying Online. | |
| Mojduszka et al. | Consumer choice of food products and the implications for price competition and government policy | |
| Jain et al. | Supply chains and antitrust governance | |
| Júnior et al. | Study to evaluate the performance development of Brazilian franchise segments | |
| CN110472843A (en) | A kind of commercial brand health indicator balancing method and system based on big data | |
| Japee et al. | Automated method for tracking individual red blood cells within capillaries to compute velocity and oxygen saturation | |
| Goddard et al. | Optimal producer investment in generic advertising: The case of fluid milk in Ontario and Quebec | |
| Chyc et al. | Optimal investment in generic advertising and research: The case of the Canadian supply‐managed egg market | |
| Wallace et al. | A Better CPI | |
| Kovo et al. | Inferring Market Definitions and Competition Groups from Empirically-Estimated Demand Systems: A Practitioner’s Guide | |
| An et al. | Procurement in welfare programs: Evidence and implications from WIC infant formula contracts | |
| Kartika et al. | Influence of Brand Image and Service Quality toward Purchase Decisions through Tokopedia | |
| CN110009041A (en) | A kind of personalized recommendation algorithm based on sewage disposal device and process evaluation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20191119 |