KR20200113370A - How to Implement a Sales Forecasting System on the Broadcast of YouTube Creators for Sale of Goods - Google Patents
How to Implement a Sales Forecasting System on the Broadcast of YouTube Creators for Sale of Goods Download PDFInfo
- Publication number
- KR20200113370A KR20200113370A KR1020190033418A KR20190033418A KR20200113370A KR 20200113370 A KR20200113370 A KR 20200113370A KR 1020190033418 A KR1020190033418 A KR 1020190033418A KR 20190033418 A KR20190033418 A KR 20190033418A KR 20200113370 A KR20200113370 A KR 20200113370A
- Authority
- KR
- South Korea
- Prior art keywords
- creator
- broadcast
- youtube
- creators
- sales
- Prior art date
Links
Images
Classifications
-
- 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
-
- 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
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- 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
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
-
- 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
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Development Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Accounting & Taxation (AREA)
- Human Resources & Organizations (AREA)
- Finance (AREA)
- Marketing (AREA)
- Game Theory and Decision Science (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Educational Administration (AREA)
- Data Mining & Analysis (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
Description
본 발명은 최근 이슈화되고 있는 유튜브 방송을 이용한 상품 판매에 대해서 효율적으로 유튜브 크리에이터를 이용하기 위한 방법으로써, 판매자는 상품 판매를 의뢰하기 전에 해당 유튜브의 방송 데이타를 토대로 상품 판매를 예측할 수 있다면 매우 효율적으로 유튜브 크리에이터와의 협의가 가능하고 홍보 및 광고 예산 관리에 있어 매우 편리할 것이다. 따라서 본 발명은 판매자가 상품 판매를 위해 유튜브 크리에이터를 홍보 방송에 이용할 경우 사전에 시스템을 토대로 매칭된 유튜브의 성향 및 조회수 등 방송데이타를 토대로 사전에 판매수량 및 금액을 예측할 수 있는 시스템에 관한 것이다.The present invention is a method for efficiently using YouTube creators for product sales using YouTube broadcasting, which has become an issue recently. If a seller can predict product sales based on the broadcasting data of the relevant YouTube before requesting product sales, it is very efficient. It will be possible to consult with YouTube creators, and it will be very convenient for promotion and advertising budget management. Accordingly, the present invention relates to a system capable of predicting sales quantity and amount in advance based on broadcast data such as propensity and views of YouTube matched based on the system in advance when a seller uses a YouTube creator for promotional broadcasting for product sales.
전세계적으로 멀티미디어채널 네트워트(MCN)산업은 매우 폭발적으로 성장하는 산업이다. 이전에 포털사이트에서 사용자가 모였다면 점차 멀티미디어로 사용자는 빠르게 이동하고 있다. 즉 우리나라도 점차 멀티미디어로 트래픽이 빠르게 전환하고 있으며 현재 네이버에서의 사용자의 체류시간보다 유튜브에서의 체류시간이 더 많은 것이 현실이다. 따라서 유튜브로 광고상품이 빠르게 이동하고 있으며 멀티미디어 특성상 체험 및 리뷰등의 컨텐츠는 매우 큰 인기를 얻고 있는 상황이다. Globally, the multimedia channel network (MCN) industry is a very explosive growth industry. If users gathered at the portal site before, users are gradually moving rapidly to multimedia. In other words, Korea is also gradually converting traffic to multimedia rapidly, and the reality is that the time spent on YouTube is more than the current time spent on Naver. Therefore, advertising products are moving rapidly to YouTube, and contents such as experiences and reviews are gaining great popularity due to the nature of multimedia.
크리에이터를 이용한 상품 홍보 및 리뷰는 점차 광고 상품으로 자리매김하고 있으며, 크리에이터의 인기도와 비레하여 광고 가격이 산정되고 있다. 하지만 객관적이고 체계적인 플랫폼이 보편화되어 있지 않고 무엇보다도 예측 시스템이 없어 자칫 판매자는 시행착오를 겪을 수 밖에 없는 것이 현실이다. 따라서 이러한 크레에이터 방송 진행 전에 판매 예측이 가능하다면 판매자는 비용을 효율적으로 절감시킬 수 있을 것이다. Product promotion and reviews using creators are gradually becoming an advertising product, and advertising prices are calculated in proportion to the popularity of creators. However, since objective and systematic platforms are not common and most of all, there is no prediction system, the reality is that sellers are forced to undergo trial and error. Therefore, if sales forecasting is possible before such a crater broadcast, sellers will be able to efficiently reduce costs.
현재의 서비스중인 시스템의 경우 멀티미디어 조회수에 근거하여 광고 가격을 책정하고 있으나 이는 컨텐츠에 따라 조회수 차이가 10배이상 발생하는 컨텐츠 특성상 광고데이타로 사용하기엔 다소 부족한 것이 현실이다. In the case of the current service system, the advertisement price is set based on the number of multimedia views, but this is a reality that it is somewhat insufficient to be used as advertisement data due to the nature of the content that the number of views occurs more than 10 times depending on the content.
따라서 예측시스템이 멀티미디어 광고에 적용될 수 있다면 판매자 및 광고주는 매우 효율적으로 광고 운영이 가능할 뿐 아니라 예산의 효율적 운영도 가능하여 서비스 만족도가 매우 높아 질 것이다.Therefore, if the prediction system can be applied to multimedia advertisements, sellers and advertisers can operate advertisements very efficiently, as well as efficiently operate budgets, and service satisfaction will be very high.
상기와 같이 크리에이터의 영상물을 통해 상품홍보 및 리뷰를 통해 홍보 영상을 게재할 경우 크리에이터의 컨텐츠 성향에 따른 조회수를 예측할 수 있어야 한다. 즉 크리에이터의 컨텐츠가 광고하고자 하는 상품 카테고리군과 일치하는 컨텐츠일 경우 평균 조회수를 접목할 수 있지만 상품카테고리와 매칭되지 않을 경우 변수가 발생할 수 있기 때문이다. 이는 크리에이터를 시청하는 구독자의 성향과 일치하는데, 크리에이터 컨턴츠의 상품과 광고하고자하는 상품의 카테고리가 일치하지 않을 경우 조회수가 현저희 줄어들 가능성이 있기 때문에 이를 반영하여 조회수를 예측해야 정확한 판매 예측도 가능하다. As described above, when a promotional video is posted through product promotion and review through the creator's video material, it is necessary to predict the number of views according to the content disposition of the creator. That is, if the creator's content matches the product category group to be advertised, the average number of views can be combined, but if it does not match the product category, a variable may occur. This coincides with the propensity of the subscribers to watch the creator.If the product of the creator content and the category of the product to be advertised do not match, the number of views may be significantly reduced. Therefore, it is necessary to predict the number of views to accurately predict sales. .
따라서 크리에이터와 방송 컨텐츠의 평균 조회수 데이타와 일치하기 위한 사전 작업이 이루어져야만이 예측 데이타의 신뢰성을 확보할 수 있을 것이다. 또한 이 과제를 해결해야만 광고 데이타로서 유의미한 방송 데이타가 산출 될 것으로 판단된다. 그러므로 크리에이터의 평균 조회수가 예측 조회수가 될 수 있도록 사전에 필요한 작업을 하는 것이 무엇보다도 필요하다. Therefore, the reliability of this predicted data can be secured only when a preliminary work is performed to match the average number of views of the creator and broadcast content. Also, it is judged that only when this problem is solved, broadcast data that is meaningful as advertisement data will be produced. Therefore, above all, it is necessary to do the necessary work in advance so that the average number of views of the creator becomes the predicted number of views.
이를 위해서는 조회수 예측 데이타를 산출하기 위한 사전 개발이 필요한데 이를 위해서는 별도의 시스템적 개발을 통해 구현해야 한다.For this, it is necessary to develop in advance to calculate the number of views predicted data, and for this, it must be implemented through a separate systemic development.
상기의 목적을 달성하기 위해 본 발명은 아래의 구성을 갖는다. 크리에이터의 예상 조회수 산출을 위해서는 우선 크리에이터의 방송 컨텐츠 내용을 토대로 상품 카테고리화 작업을 해야 한다. 크리에이터가 사이트에 가입할 때 자신의 방송 컨텐츠를 토대로 쇼핑몰에서 운영하는 상품 카테고리화하여 분류하는 작업을 해야 하며, 크리에이터가 입력한 상품 카테고리의 적절성을 판단하여 조정 및 승인 과정을 거쳐 카테고리화가 완료된다. 이렇게 크리에이터의 방송 컨텐츠를 상품의 카테고리로 분류하게 될 경우 크리에이터의 구독자수와 평균 조회수를 토대로 예상 조회수의 산출이 가능해진다. In order to achieve the above object, the present invention has the following configuration. In order to calculate the creator's expected number of views, it is first necessary to categorize the product based on the content of the creator's broadcast content. When a creator subscribes to the site, it is necessary to categorize and categorize products operated by the shopping mall based on their broadcast content, and the categorization is completed through an adjustment and approval process by judging the appropriateness of the product category entered by the creator. In this way, when the broadcast content of the creator is classified into a product category, the expected number of views can be calculated based on the number of subscribers and the average number of views of the creator.
이렇게 산출된 평균 조회수를 토대로 판매 예측을 산출해야 하는데 통상 판매 예측은 이전의 유사 크리에이터들의 평균 판매 전환율을 토대로 가중치를 두게되며, 해당 크리에이터의 전환율 데이타가 존재할 경우 가중치를 더 두어 전환율을 산출하게 된다. 이렇게 전환율이 산출되면, 상품의 판매가격을 입력할 경우 판매수량 및 예상 매출까지 산출이 가능하게 된다.. The sales forecast should be calculated based on the average number of views calculated in this way. In general, the sales forecast is weighted based on the average sales conversion rate of previous similar creators, and if there is conversion rate data of the corresponding creator, a weight is added to calculate the conversion rate. When the conversion rate is calculated in this way, it is possible to calculate the sales quantity and expected sales by entering the selling price of the product.
데이타는 누적된 데이타를 토대로 지속적으로 갱신되어야 하는데, 여기서 갱신되어야 할 데이타는 크리에이터의 구독자 수 및 예상 조호수 그리고 평균 전환율및 크리에이터의 전환율이 월단위로 변경되어 데이타 산출의 변수로 적용해야 한다. 이렇게 적용된 함수를 토대로 예측 데이타를 산출하게 된다면 신뢰성 있는 광고 데이타로 사용이 가능해진다. The data must be continuously updated based on the accumulated data, and the data to be updated here should be applied as a variable of data calculation as the number of subscribers of the creator, the number of expected groups, the average conversion rate, and the conversion rate of the creator are changed monthly. If prediction data is calculated based on the applied function, it can be used as reliable advertisement data.
이상에서와 같이 본 발명은 크리에이터의 방송 컨텐츠를 토대로 예상 조회수 및 전환율을 토대로 판매 예측이 가능한 시스템을 개발하고자 함이다. 따라서 해당 함수가 적용된 시스템을 이용할 경우 판매자 입장에서는 예산에 맞는 효율적인 광고 운영이 가능해지고, 아울러 크리에이터 입장에서는 합리적인 방송 댓가 산정이 가능해짐으로써 구성원 모두가 만족할 수 있는 시스템이 될 수 있다. 아울러 효율적인 광고 운영이라는 측면에서 판매자의 광고 운영을 함에 있어 별도의 시행착오를 겪지 않고 비용절감이 가능해짐으로서 수익 개선 효과를 볼 수 있다. 따라서 본 시스템이 개발될 경우 광고 구성원 모두가 만족할 수 있는 수익배분이 가능해진다. As described above, the present invention is to develop a system capable of predicting sales based on expected views and conversion rates based on the broadcast content of the creator. Therefore, if the system to which the function is applied is used, it is possible for the seller to efficiently operate advertisements that fit the budget, and for the creator to calculate a reasonable broadcast price, it can be a system that all members can be satisfied with. In addition, in terms of efficient advertisement operation, it is possible to improve profits by reducing costs without experiencing separate trial and error in the seller's advertisement operation. Therefore, when this system is developed, it becomes possible to distribute profits that all members of the advertisement can satisfy.
도 1은 본 발명에 의한 예측시스템 구성도1 is a configuration diagram of a prediction system according to the present invention
상기와 같은 본 발명의 실시예를 첨부된 도면을 참조하여 상세히 설명한다.An embodiment of the present invention as described above will be described in detail with reference to the accompanying drawings.
도 1은 본 발명에 의한 예측 시스템 구성도이다.1 is a block diagram of a prediction system according to the present invention.
도면을 참조하면 본 발명에 의한 예측시스템은 01 크리에이터가 회원 가입시 정보 입력란에 자신의 방송 컨텐츠를 상품카테고리 범주를 선택하여 입력한다. 입력된 정보는 02 데이타베이스에 저장이 되며 저장된 데이타를 관리자가 호출하여 적정 여부를 판단하게 된다. 관리자가 적정하다고 승인을 하게 되면 03 카테고리 데이타베이스에 갱신되어 저장이 되며, 저장된 카테고리 데이타베이스는 상품과 매칭되는 표준데이타가 된다. 04 상품을 매칭해야 하는 상황이 발생하게 되면 판매자는 자신의 상품과 맞는 크리에이터를 선택할 수 있으며, 선택된 크리에이터를 토대로 상품과 매칭이 완료되면 05 예측데이타가 산출되게 된다. 예측 데이타는 조회수, 평균 전환율, 예상 판매수량, 예상 매출까지 산출이 가능한다. 예측 데이타를 토대로 판매자는 Referring to the drawings, in the prediction system according to the present invention, 01 creator selects a product category category and inputs his or her broadcast content in an information input field when a creator registers as a member. The entered information is stored in the 02 database, and the administrator calls the stored data to determine whether it is appropriate. If the manager approves that it is appropriate, it is updated and stored in the 03 category database, and the stored category database becomes standard data matching products. 04 When there is a situation where a product needs to be matched, the seller can select a creator that matches his product, and when matching with the product is completed based on the selected creator, 05 prediction data is calculated. Forecast data can be calculated from hits, average conversion rate, expected sales volume, and expected sales. Based on the forecast data, the seller
01 크리에이터
02 데이타베이스
03 카테고리 데이타베이스
04 상품
05 예측데이타01 Creator
02 database
03 Category Database
04 products
05 Forecast data
Claims (1)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| KR1020190033418A KR20200113370A (en) | 2019-03-25 | 2019-03-25 | How to Implement a Sales Forecasting System on the Broadcast of YouTube Creators for Sale of Goods |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| KR1020190033418A KR20200113370A (en) | 2019-03-25 | 2019-03-25 | How to Implement a Sales Forecasting System on the Broadcast of YouTube Creators for Sale of Goods |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| KR20200113370A true KR20200113370A (en) | 2020-10-07 |
Family
ID=72884047
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| KR1020190033418A KR20200113370A (en) | 2019-03-25 | 2019-03-25 | How to Implement a Sales Forecasting System on the Broadcast of YouTube Creators for Sale of Goods |
Country Status (1)
| Country | Link |
|---|---|
| KR (1) | KR20200113370A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20220116784A (en) | 2021-02-15 | 2022-08-23 | 경남정보대학교 산학협력단 | Merchandise sales method for micro enterprise owners and local creator |
| KR20240002089A (en) | 2022-06-28 | 2024-01-04 | 아도바 주식회사 | Method, apparatus and system of providing contents service in multi-channel network |
-
2019
- 2019-03-25 KR KR1020190033418A patent/KR20200113370A/en not_active Application Discontinuation
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20220116784A (en) | 2021-02-15 | 2022-08-23 | 경남정보대학교 산학협력단 | Merchandise sales method for micro enterprise owners and local creator |
| KR20240002089A (en) | 2022-06-28 | 2024-01-04 | 아도바 주식회사 | Method, apparatus and system of providing contents service in multi-channel network |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20200195540A1 (en) | Method and system for scoring quality of traffic to network sites | |
| KR101790312B1 (en) | Apparatus and Method for matching management | |
| US20200286121A1 (en) | Network based system and method for managing and implementing online commerce | |
| US8108253B2 (en) | Identifying advertising specialist | |
| US8788345B2 (en) | Method and apparatus for advertising bidding | |
| JP2008529190A (en) | Advertisement management method, shadow campaign system, and advertisement management system | |
| US20140330638A1 (en) | System and method for management of marketing allocations using a return on investment metric | |
| US20120158461A1 (en) | Content management and advertisement management | |
| US20090171763A1 (en) | System and method for online advertising driven by predicting user interest | |
| US8645199B1 (en) | Using application characteristics for ad pricing | |
| CN110348894B (en) | Method and device for displaying resource advertisement and electronic equipment | |
| US20120271709A1 (en) | Integrated and comprehensive advertising campaign visualization | |
| US20140058826A1 (en) | Composite publisher audience profiles in comprehensive advertising campaign management and optimization | |
| US20140156383A1 (en) | Ad-words optimization based on performance across multiple channels | |
| US20150310481A1 (en) | System and method for management of marketing campaigns | |
| US11769171B1 (en) | Predicting advertisement impact for audience selection | |
| US20220122118A1 (en) | Planning device and computer program | |
| US11216840B2 (en) | Systems and methods for optimization of data element utilization according to multi-touch attribution | |
| US20080294519A1 (en) | Method and system for integrating advertising with content | |
| CN112819528A (en) | Crowd pack online method and device and electronic equipment | |
| KR20200113370A (en) | How to Implement a Sales Forecasting System on the Broadcast of YouTube Creators for Sale of Goods | |
| US11756070B1 (en) | Predicting advertisement impact for campaign selection | |
| US10410237B1 (en) | Inventory management integrating subscriber and targeting data | |
| KR101343085B1 (en) | Level advertising exposure advertising medium and billing system | |
| JP2018129048A (en) | Target selection method and system thereof, advertisement content provision method to target and system thereof, and content provision method to target |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| E902 | Notification of reason for refusal | ||
| E601 | Decision to refuse application | ||
| E601 | Decision to refuse application |