CN107844988A - A kind of intelligent marketing system excavated based on big data with geographical position matching - Google Patents
A kind of intelligent marketing system excavated based on big data with geographical position matching Download PDFInfo
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- CN107844988A CN107844988A CN201710834675.XA CN201710834675A CN107844988A CN 107844988 A CN107844988 A CN 107844988A CN 201710834675 A CN201710834675 A CN 201710834675A CN 107844988 A CN107844988 A CN 107844988A
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- 238000010801 machine learning Methods 0.000 claims abstract description 9
- 230000001960 triggered effect Effects 0.000 claims abstract description 7
- 238000007418 data mining Methods 0.000 claims abstract description 6
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 5
- 238000000034 method Methods 0.000 claims description 5
- 238000013499 data model Methods 0.000 claims description 3
- 238000003066 decision tree Methods 0.000 claims description 3
- 238000007637 random forest analysis Methods 0.000 claims description 3
- 238000012706 support-vector machine Methods 0.000 claims description 3
- 238000005457 optimization Methods 0.000 abstract description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 abstract description 2
- 230000000694 effects Effects 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000009412 basement excavation Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
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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
- G06Q30/0261—Targeted advertisements based on user location
Abstract
The present invention relates to a kind of intelligent marketing system excavated based on big data and matched with geographical position, the all types of user data being collected into are analyzed by a variety of machine learning algorithms, user preference label is obtained, personalized marketing task is then formulated according to preference label and triggered at user preference time point；Marketing feedback subsystem is also provided with, using marketing effectiveness and user feedback as new data source, and input data mining model, optimization is iterated to model.The present invention can provide a kind of precision marketing, for the accurate water conservancy diversion of Xian Xia shops, the resource utilization that improves Xian Xia shops, lifting Consumer's Experience excavated based on big data and the intelligent marketing system of geographical position matching.
Description
Technical field
The present invention relates to big data technical field, more particularly to a kind of intelligence excavated based on big data with geographical position matching
Can marketing system.
Background technology
Marketed on traditional line, more based on short, multimedia message mass-sending, research differentiation is not carried out to user, because its is extensive
Marketing mode, relatively low marketing precision and lack real-time, so that marketing conversion ratio is low, effect is poor, is also easy to cause pair
The harassing and wrecking of user, cause customer complaint or loss.
As the people in the business activities in front Xiamen shop, attracted mainly by the natural flow of the people of shops position and advertising campaign
Stream, shops operation personnel lack effective drainage means.In the user in shop is entered, because no data analysis supports, it is impossible to
Quick identification user's request, does for the user for having demand and targetedly markets, cause substantial amounts of ineffective access flow, and enter shop
The resident rate of user is low, it is impossible to brings the lifting of actual volume.
With the development of big data application technology, by being excavated to user data, the demand of user is entered on line
Row precisely analysis, by location matches, guiding target user goes to neighbouring Xian Xia shops to experience, and can not only improve user's body
Test, improve marketing precision, lifting service level, can also improve the business efficiency of Xian Xia shops.
Marketed on line based on mass-sending, blindly the nature stream of people and advertising campaign, prior art are leaned on by push, Xian Xia shops for advertisement
Scheme has the disadvantage that:Being marketed on line, conversion ratio is low, easily user is caused to harass;Xian Xia shops is unable to Rapid matching user
Demand, poor user experience.
The content of the invention
A kind of precision marketing is provided the invention aims to overcome the deficiencies in the prior art, precisely led for Xian Xia shops
Stream, the resource utilization for improving Xian Xia shops, the intelligence based on big data excavation and geographical position matching of lifting Consumer's Experience
Marketing system.
To reach above-mentioned purpose, present invention employs following technical scheme.
A kind of intelligent marketing system excavated based on big data with geographical position matching, including big data modeling subsystem,
User matches subsystem, position marketing subsystem and marketing feedback subsystem, and the big data models subsystem by using machine
Device learning art excavates to the user data of collection, exports the preference label of each user；The user matches subsystem
The user data and preference label collected in subsystem are modeled according to the big data, with reference to marketing scale, Marking Budget, manpower
With place resource, matching marketing crowd, marketing task and marketing channel are generated, and set the triggered time；Position marketing
System carries out scene marketing by the real-time position information based on Xian Xia shops and user；The marketing feedback subsystem passes through
Marketing effectiveness and user feedback data are collected, as a part for user data, exports and models subsystem to the big data, make
For the data source of data mining, renewal iteration is optimized to big data modeling subsystem.
The user data collected in the big data modeling subsystem includes following at least one：ID, consumer record,
Shipping and receiving address, resident position, internet records and search record.
The machine learning techniques used in the big data modeling subsystem are supervision type or non-supervisory type machine learning skill
Art, its algorithm include following at least one：Logistics recurrence, SVMs, decision tree and random forest.
The user preference label exported in the big data modeling subsystem includes following at least one：Brang Preference, disappear
Take preference, channel preference, time preference and be lost in probability.
The marketing scale that the user is matched in subsystem is positively related with Marking Budget, manpower and place resource；Institute
It is the preference label that the user that subsystem exports is modeled according to the big data to state the marketing crowd that user is matched in subsystem, is selected
The marketing crowd matched with marketing task selected out；The marketing task that the user matches in subsystem is the channel according to user
Preference, most suitable marketing channel, including following at least one are matched for marketing crowd：Short message, phone and client push；Institute
It is time preference's label that user in subsystem is modeled according to the big data to state the triggered time that user is matched in subsystem,
Push marketing advertisement is carried out in the range of time preference.
The position marketing subsystem, is specifically included, step 1：Read by operator base station or cell-phone customer terminal
Gps satellite location information, obtain the real-time position information of user；Step 2：Establish Xian Xia shops location information data storehouse；Step
Three：Distance threshold is set, when the distance around targeted customer appears in shops is in threshold range, marketing message is sent, accuses
Know product information and shops position, invite user to carry out On-site Experience.
Due to the utilization of above-mentioned technical proposal, the advantageous effects that technical scheme is brought have：This technology side
Case obtains the preference mark of different user by the data mining mode of a variety of algorithms of different to collecting a variety of user data, analysis
Label, personalized marketing task is then formulated according to above-mentioned data and preference label and triggered at user preference time point, tool
Precision marketing is realized, is matched by geographical position, is the accurate water conservancy diversion of Xian Xia shops, improves the level of resources utilization of Xian Xia shops
With the advantageous effects of Consumer's Experience；The technical program is also provided with marketing feedback subsystem, by by marketing effectiveness and
User feedback is iterated optimization to model, has marketing effectiveness anti-in real time as new data source, input data mining model
Feedback, feedback data collect fast, data using advantageous effects that are abundant, accelerating model optimization renewal speed.
Brief description of the drawings
Accompanying drawing 1 is overall structure diagram of the invention.
Accompanying drawing 2 is schematic flow sheet of the invention.
In figure：1. big data models subsystem；2. user matches subsystem；The subsystem 3. position is marketed；4. marketing feedback
Subsystem.
Embodiment
Below in conjunction with the accompanying drawings and specific embodiment the present invention is described in further detail.
As shown in Figures 1 and 2, a kind of intelligent marketing system excavated based on big data with geographical position matching, including it is big
Data modeling subsystem 1, user match subsystem 2, position marketing subsystem 3 and marketing feedback subsystem 4, the big data and built
Mold system 1 is excavated by using machine learning techniques to the user data of collection, exports the preference label of each user；
The user matches subsystem 2 and the user data and preference label collected in subsystem 1 is modeled according to the big data, with reference to battalion
Pin gauge mould, Marking Budget, manpower and place resource, matching marketing crowd, generation marketing task and marketing channel, and set triggering
Time；The position marketing subsystem 3 carries out scene marketing by the real-time position information based on Xian Xia shops and user；Institute
Marketing feedback subsystem 4 is stated by collecting marketing effectiveness and user feedback data, as a part for user data, is exported to institute
Big data modeling subsystem 1 is stated, as the data source of data mining, renewal is optimized to big data modeling subsystem 1
Iteration.
The user data collected in the big data modeling subsystem 1 includes following at least one：ID, consumption note
Record, shipping and receiving address, resident position, internet records and search record.
The machine learning techniques used in the big data modeling subsystem 1 are supervision type or non-supervisory type machine learning skill
Art, its algorithm include following at least one：Logistics recurrence, SVMs, decision tree and random forest.
The user preference label exported in the big data modeling subsystem 1 includes following at least one：Brang Preference, disappear
Take preference, channel preference, time preference and be lost in probability.
The marketing scale that the user is matched in subsystem 2 is positively related with Marking Budget, manpower and place resource.
The marketing crowd that the user matches in subsystem 2 is the user that subsystem output is modeled according to the big data
Preference label, the marketing crowd matched with marketing task selected.
The marketing task that the user matches in subsystem 2 is the channel preference according to user, for marketing crowd matching most
Suitable marketing channel, including following at least one：Short message, phone and client push.
The triggered time that the user matches in subsystem 2 is the time that user in subsystem is modeled according to the big data
Preference label, the push marketing advertisement in the range of time preference.
The position marketing subsystem 3, is specifically included, step 1：Read by operator base station or cell-phone customer terminal
Gps satellite location information, obtain the real-time position information of user；Step 2：Establish Xian Xia shops location information data storehouse；Step
Rapid three：Distance threshold is set, when the distance around targeted customer appears in shops is in threshold range, sends marketing message,
Product information and shops position are informed, invites user to carry out On-site Experience.
It the above is only the concrete application example of the present invention, protection scope of the present invention be not limited in any way.All uses
Equivalent transformation or equivalent replacement and the technical scheme formed, all fall within rights protection scope of the present invention.
Claims (6)
- A kind of 1. intelligent marketing system excavated based on big data with geographical position matching, it is characterised in that：Built including big data Mold system, user match subsystem, position marketing subsystem and marketing feedback subsystem, and the big data modeling subsystem leads to Cross and the user data of collection is excavated using machine learning techniques, export the preference label of each user；The user Sub-combination models the user data and preference label collected in subsystem according to the big data, with reference to marketing scale, marketing Budget, manpower and place resource, matching marketing crowd, generation marketing task and marketing channel, and set the triggered time；Institute's rheme Marketing subsystem is put by the real-time position information based on Xian Xia shops and user, carries out scene marketing；Marketing feedback System, as a part for user data, is exported and modeled to the big data by collecting marketing effectiveness and user feedback data Subsystem, as the data source of data mining, renewal iteration is optimized to big data modeling subsystem.
- 2. it is according to claim 1 it is a kind of based on big data excavate and geographical position matching intelligent marketing system, its It is characterised by：The user data collected in the big data modeling subsystem includes following at least one：ID, consumption note Record, shipping and receiving address, resident position, internet records and search record.
- 3. a kind of intelligent marketing system excavated based on big data with geographical position matching according to claim 1, it is special Sign is：The machine learning techniques used in the big data modeling subsystem are supervision type or non-supervisory type machine learning skill Art, its algorithm include following at least one：Logistics recurrence, SVMs, decision tree and random forest.
- 4. a kind of intelligent marketing system excavated based on big data with geographical position matching according to claim 1, it is special Sign is：The user preference label exported in the big data modeling subsystem includes following at least one：Brang Preference, consumption Preference, channel preference, time preference and loss probability.
- 5. a kind of intelligent marketing system excavated based on big data with geographical position matching according to claim 1, it is special Sign is：The marketing scale that the user is matched in subsystem is positively related with Marking Budget, manpower and place resource；It is described The marketing crowd that user matches in subsystem is the preference label that the user that subsystem exports is modeled according to the big data, is selected The marketing crowd matched with marketing task gone out；The marketing task that the user matches in subsystem is inclined according to the channel of user It is good, match most suitable marketing channel, including following at least one for marketing crowd：Short message, phone and client push；It is described User match subsystem in triggered time be according to the big data model subsystem in user time preference's label, when Between push marketing advertisement is carried out in the range of preference.
- 6. a kind of intelligent marketing system excavated based on big data with geographical position matching according to claim 1, it is special Sign is：The position marketing subsystem, specifically includes step 1：Read by operator base station or cell-phone customer terminal Gps satellite location information, obtain the real-time position information of user；Step 2：Establish Xian Xia shops location information data storehouse；Step Three：Distance threshold is set, when the distance around targeted customer appears in shops is in threshold range, marketing message is sent, accuses Know product information and shops position, invite user to carry out On-site Experience.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109003143A (en) * | 2018-08-03 | 2018-12-14 | 阿里巴巴集团控股有限公司 | Recommend using deeply study the method and device of marketing |
| CN109376186A (en) * | 2018-10-30 | 2019-02-22 | 成都油管家科技有限公司 | A kind of excavating analysis system and method for gas station's management data |
| CN110009416A (en) * | 2019-04-02 | 2019-07-12 | 安徽筋斗云机器人科技股份有限公司 | A kind of system based on big data cleaning and AI precision marketing |
| CN110264252A (en) * | 2019-06-01 | 2019-09-20 | 浙江华坤道威数据科技有限公司 | A kind of advertisement fixed point jettison system based on LBS positioning |
| CN111105849A (en) * | 2019-12-31 | 2020-05-05 | 杭州健海科技有限公司 | Channel collaborative satisfaction investigation method and system based on big data |
| CN111738761A (en) * | 2020-06-19 | 2020-10-02 | 中国工商银行股份有限公司 | Marketing information processing method and device |
| CN112232876A (en) * | 2018-07-18 | 2021-01-15 | 口口相传(北京)网络技术有限公司 | Accurate marketing method and device based on user scene attribute information |
| CN113283930A (en) * | 2021-05-12 | 2021-08-20 | 建信金融科技有限责任公司 | Marketing activity operation method and device |
| CN113377802A (en) * | 2021-06-07 | 2021-09-10 | 广发银行股份有限公司 | Scheduling pushing method, system, equipment and storage medium |
| CN116188066A (en) * | 2023-03-10 | 2023-05-30 | 广州南方学院 | Intelligent distribution method and system for store clients based on geographic position |
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Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112232876A (en) * | 2018-07-18 | 2021-01-15 | 口口相传(北京)网络技术有限公司 | Accurate marketing method and device based on user scene attribute information |
| CN112232876B (en) * | 2018-07-18 | 2024-03-22 | 口口相传(北京)网络技术有限公司 | Accurate marketing method and device based on user scene attribute information |
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| CN109003143A (en) * | 2018-08-03 | 2018-12-14 | 阿里巴巴集团控股有限公司 | Recommend using deeply study the method and device of marketing |
| CN109376186A (en) * | 2018-10-30 | 2019-02-22 | 成都油管家科技有限公司 | A kind of excavating analysis system and method for gas station's management data |
| CN110009416A (en) * | 2019-04-02 | 2019-07-12 | 安徽筋斗云机器人科技股份有限公司 | A kind of system based on big data cleaning and AI precision marketing |
| CN110264252A (en) * | 2019-06-01 | 2019-09-20 | 浙江华坤道威数据科技有限公司 | A kind of advertisement fixed point jettison system based on LBS positioning |
| CN111105849A (en) * | 2019-12-31 | 2020-05-05 | 杭州健海科技有限公司 | Channel collaborative satisfaction investigation method and system based on big data |
| CN111105849B (en) * | 2019-12-31 | 2022-03-11 | 杭州健海科技有限公司 | Channel collaborative satisfaction investigation method and system based on big data |
| CN111738761A (en) * | 2020-06-19 | 2020-10-02 | 中国工商银行股份有限公司 | Marketing information processing method and device |
| CN113283930A (en) * | 2021-05-12 | 2021-08-20 | 建信金融科技有限责任公司 | Marketing activity operation method and device |
| CN113377802A (en) * | 2021-06-07 | 2021-09-10 | 广发银行股份有限公司 | Scheduling pushing method, system, equipment and storage medium |
| CN116188066A (en) * | 2023-03-10 | 2023-05-30 | 广州南方学院 | Intelligent distribution method and system for store clients based on geographic position |
| CN116188066B (en) * | 2023-03-10 | 2023-08-15 | 广州南方学院 | Intelligent distribution method and system for store clients based on geographic position |
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Application publication date: 20180327 |