KR-102965192-B1 - E-commerce discount solution and statistical analysis method

Abstract

A method for e-commerce discounting and statistical analysis is disclosed, which is performed by an online service system comprising one or more servers. The method includes the steps of providing a video advertisement to a user during the process of using discount benefits and points to apply at least one of the use of points held by the logged-in user and a payment discount coupon for the payment amount prior to product payment, and applying a discount to the payment amount to the user who has watched the video advertisement.

Inventors

• 김학선

Dates

Publication Date

20260513

Application Date

20230119

Claims (3)

1. In a method for e-commerce discounting and statistical analysis performed by an online service system including one or more servers, A step of providing a video advertisement to a user during the process of using points and discount benefits to apply at least one of the use of points held by the logged-in user for the payment amount and a payment discount coupon before product payment; A step of conducting an evaluation survey on the video advertisement after the video advertisement ends; A step of applying a discount on the payment amount to users who watched a video advertisement; and The step of calculating part ratings responded to by users for each survey part of the video advertisement, calculating a final rating by combining all part ratings while reflecting part-specific weights, and providing the calculated part ratings and the final rating to the relevant parties of the video advertisement; The discount application step is performed after the user's response to the survey is completed, and An e-commerce discount and statistical analysis method in which each survey part consists of survey items regarding the role of a specific production element among multiple production elements for the production of video advertisements.
2. delete
3. delete

Description

E-commerce discount solution and statistical analysis method The present invention relates to e-commerce, and in particular to an e-commerce discount solution and a statistical analysis method. E-commerce platforms, which enable the trading of various tangible and intangible goods online, see active advertising driven by the nature of these platforms, which are accessed by a large number of users. Initially, the approach involved displaying the same advertisement on webpages to expose it to a mass audience regardless of gender or age; however, this has gradually evolved into a method that displays personalized advertisements tailored to each user based not only on gender and age but also on their search history. Nevertheless, since the primary purpose of platform usage is product search and purchase, most users ignore advertisements displayed in specific areas of the webpage, and a significant number of users feel aversion to the mere exposure of advertisements. Consequently, advertising inevitably targets only a select group of interested users, which limits the effectiveness of the advertisements. All e-commerce product purchases follow a fixed process consisting of ① product search and purchase decision, ② login, ③ use of points and discounts, ④ payment via payment method, and ⑤ product delivery. In this context, current platform advertising focuses on the ① product search and purchase decision stage; advertisements are positioned within shopping platform categories or the main interface and are delivered to an unspecified audience in the form of CPC (Cost Per Click) or CPM (Click Per Mile) without reflecting personal information, making it difficult for advertisers to expect credible results. Furthermore, although AI is used to collect buyer behavior data based on search history and apply it to platform advertising to compensate for this, this method merely improves sales efficiency during the product search and purchase decision stages, meaning advertisers cannot receive actual data feedback regarding advertising effectiveness. The purpose of advertising is to increase sales efficiency by inducing purchases and identifying buyer tendencies. However, existing platform advertising focuses only on inducing purchases, and there is a problem in that it is difficult to develop information on purchasing tendencies through product sales because it is linked to payment information from credit card companies and PG (Payment Gateway) companies, and requires the buyer's consent to provide personal information. FIG. 1 is an overall system block diagram according to one embodiment. Figure 2 is an example of a screen in the point and discount benefit process. FIG. 3 is a flowchart of an e-commerce discount solution and statistical analysis method according to one embodiment. Figure 4 is an example diagram related to an evaluation survey for video advertisements. Figure 5 shows an example of a survey on video advertisements. Figure 6 is an example of the application of the rating protocol. The foregoing and additional aspects of the present invention will become more apparent through preferred embodiments described with reference to the accompanying drawings. Hereinafter, the present invention will be described in detail through these embodiments so that a person skilled in the art can easily understand and reproduce it. FIG. 1 is an overall system block diagram according to one embodiment. A user terminal (100) is a communication and computing device used by a user, and may be a desktop or laptop, as well as a mobile terminal such as a smartphone or tablet PC. The user can use such a user terminal (100) to connect online to an online service system (200) and use the e-commerce platform service provided by the system. That is, the user can search for tangible and intangible goods registered on the e-commerce platform, select a product they wish to purchase, and make a payment to acquire the product. The online service system (200) is a server system configured to include one or more servers, and may include an e-commerce server (210) and a discount solution support server (220), and the discount solution support server (220) may be linked via API with the e-commerce server (210). This online service system (200) can stream video advertisements (product video advertisements) and survey questions stored in the DB server of the discount solution support server (220) to a user who intends to purchase a product before the user makes a payment for the product, and can grant a certain discount benefit to the user as a reward for watching the advertisement and responding to the survey. Furthermore, the discount solution support server (220) is linked via API with the e-commerce server (210) to perform tasks such as selecting and streaming video advertisements and survey DBs, statistically applying survey response data based on e-commerce platform member information, and personalized product recommendations, as well as storing