• Title/Summary/Keyword: Keyword Marketing

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Associated Keyword Recommendation System for Keyword-based Blog Marketing (키워드 기반 블로그 마케팅을 위한 연관 키워드 추천 시스템)

  • Choi, Sung-Ja;Son, Min-Young;Kim, Young-Hak
    • KIISE Transactions on Computing Practices
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    • v.22 no.5
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    • pp.246-251
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    • 2016
  • Recently, the influence of SNS and online media is rapidly growing with a consequent increase in the interest of marketing using these tools. Blog marketing can increase the ripple effect and information delivery in marketing at low cost by prioritizing keyword search results of influential portal sites. However, because of the tough competition to gain top ranking of search results of specific keywords, long-term and proactive efforts are needed. Therefore, we propose a new method that recommends associated keyword groups with the possibility of higher exposure of the blog. The proposed method first collects the documents of blog including search results of target keyword, and extracts and filters keyword with higher association considering the frequency and location information of the word. Next, each associated keyword is compared to target keyword, and then associated keyword group with the possibility of higher exposure is recommended considering the information such as their association, search amount of associated keyword per month, the number of blogs including in search result, and average writhing date of blogs. The experiment result shows that the proposed method recommends keyword group with higher association.

Analytical Study on Classification and Service Quality Improvement for Keyword & Blog Advertising Marketing Services (검색 광고 마케팅 서비스 유형 분석과 서비스 품질 개선방안)

  • Choi, Yoon-Ho;Lee, Jae-Won
    • The Journal of the Korea Contents Association
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    • v.15 no.11
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    • pp.456-466
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    • 2015
  • This study is focusing to the keyword and blog advertising marketing services that are implementing a viral marketing utilizing keyword searches of the search portal and advertiser's blogs with convergent way. Through a case study for the company operating the service to pinpoint consumers to the advertisers site by indirect exposure via keyword advertising blog at the top of the search results, we analyzed the primitive service operation model on transactional relationship between the business players. We have a research purpose to generate improvement alternatives for the company's keyword advertising marketing services and operation solution using the survey study on the service quality perception and the perceptional gap between user groups. As results of study, we founded 4 types of the service solution and 4 models of service operating architecture on the transactional relations, and we recommended some improvements on the service and solution operation based on the SERVQUAL questionnaire analysis of the difference between the ads sponsor group and ads agency group.

To Bid or Not to Bid? - Keyword Selection in Paid Search Advertising

  • Ma, Yingying;Sun, Luping
    • Asia Marketing Journal
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    • v.16 no.3
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    • pp.23-33
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    • 2014
  • The selection of keywords for bidding is a critical component of paid search advertising. When the number of possible keywords is enormous, it becomes difficult to choose the best keywords for advertising and then subsequently to assess their effect. To this end, we propose an ultrahigh dimensional keyword selection approach that not only reduces the dimension for selections, but also generates the top listed keywords for profits. An empirical analysis using a unique panel dataset from a large online clothes retailer that advertises on the largest search engine in China (i.e., Baidu) is presented to illustrate the usefulness of our approach.

A Study on the Library Marketing Research Trends through Keyword Network Analysis: Comparative Analysis of Korea and Other Countries (키워드 네트워크 분석을 통한 도서관마케팅 연구 경향 분석 - 우리나라와 국외연구의 비교분석 -)

  • Lee, Seongsin
    • Journal of the Korean Society for Library and Information Science
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    • v.50 no.3
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    • pp.383-402
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    • 2016
  • The purpose of this study is to study library marketing research trends in Korea and other countries through the analysis of author keyword network of peer-reviewed journal articles. The author keyword was collected from four major LIS journals in Korea and Scopus academic database for other countries'. The data was analyzed using NetMiner4 software. The results of the study were as follows: 1) In Korea, lots of library marketing studies focused on public libraries. However, there was a range of library marketing researches focused on academic libraries in other countries, 2) In Korea, there was not a variety of subjects of library marketing studies and the studies were mainly led by a few scholars, 3) In other countries, many scholars paid attention to digital library marketing through social media and/or web, and 4) there little library marketing studies focused on school libraries both in Korea and other countries.

Design and Implementation of Potential Advertisement Keyword Extraction System Using SNS (SNS를 이용한 잠재적 광고 키워드 추출 시스템 설계 및 구현)

  • Seo, Hyun-Gon;Park, Hee-Wan
    • Journal of the Korea Convergence Society
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    • v.9 no.7
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    • pp.17-24
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    • 2018
  • One of the major issues in big data processing is extracting keywords from internet and using them to process the necessary information. Most of the proposed keyword extraction algorithms extract keywords using search function of a large portal site. In addition, these methods extract keywords based on already posted or created documents or fixed contents. In this paper, we propose a KAES(Keyword Advertisement Extraction System) system that helps the potential shopping keyword marketing to extract issue keywords and related keywords based on dynamic instant messages such as various issues, interests, comments posted on SNS. The KAES system makes a list of specific accounts to extract keywords and related keywords that have most frequency in the SNS.

Research Trends in Journal of Fashion Business -A Social Network Analysis of Keywords in Fashion Marketing and Design Area- (키워드 네트워크 분석을 통한 「패션비즈니스」 연구 동향 -패션마케팅 및 디자인 분야를 중심으로-)

  • Lee, MiYoung;Lee, Jungmin
    • Journal of Fashion Business
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    • v.23 no.3
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    • pp.51-66
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    • 2019
  • The aim of this study is to identify research trends of "Journal of Fashion Business" by analyzing the keyword network of the paper published between 2006 and 2017. The papers selected for analysis in the study were 287 fashion design articles and 281 fashion marketing articles published between February 2006 and December 2017 and titles, volumes, publishing years, authors, keywords, and abstracts of each paper were collected for data analysis. The research was carried out through selection, collection of article data, keyword extraction and coding, keywords refinement, formation of network matrix, and analysis and visualization process. First, based on the title of the paper used in the analysis, the fashion design/aesthetics, marketing/social psychology, clothing materials, clothing composition, and other fields were classified. Research analysis used the Netminer 4 (Ver.4.3.2) program. Results indicated showed that the intellectual structure of the "Fashion Business" research paper showed key word changes over time, and the degree centrality and between centrality of the keywords.

A Study on analyzing brand character of myth material, relevant keyword and relevance with big data of portal site and SNS (포털사이트, SNS의 빅데이터를 이용한 신화소재의 브랜드 캐릭터와 연관어, 연관도 분석)

  • Oh, Sejong;Doo, Illchul
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.11 no.1
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    • pp.157-169
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    • 2015
  • In digital marketing, means of public relations and marketing of enterprises are changing into marketing techniques of predictive analytics. A significant study can be carried out by an analysis of 'the patterns of customers' uses' using big data on major portal sites and SNSs and their correlation with related keywords. This study analyzes the origins of mythological characters in major brands such as Nike, Hermes, Versace, Canon and Starbucks. Also, it extracts related keywords and relevance using big data on portal sites and SNS and their correlation. Nike marketing that reminds people of 'the goddess of victory, Nike' formed a good combination of the brand with relevance. Most of them are based on Greek mythology and have rich materials for storytelling and artistic values in common. Hopefully, this case analysis of foreign brands would become a starting point of discovering the materials of the domestic mythological characters.

A Study on the Meaning and Strategy of Keyword Advertising Marketing

  • Park, Nam Goo
    • Journal of Distribution Science
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    • v.8 no.3
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    • pp.49-56
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    • 2010
  • At the initial stage of Internet advertising, banner advertising came into fashion. As the Internet developed into a central part of daily lives and the competition in the on-line advertising market was getting fierce, there was not enough space for banner advertising, which rushed to portal sites only. All these factors was responsible for an upsurge in advertising prices. Consequently, the high-cost and low-efficiency problems with banner advertising were raised, which led to an emergence of keyword advertising as a new type of Internet advertising to replace its predecessor. In the beginning of 2000s, when Internet advertising came to be activated, display advertisement including banner advertising dominated the Net. However, display advertising showed signs of gradual decline, and registered minus growth in the year 2009, whereas keyword advertising showed rapid growth and started to outdo display advertising as of the year 2005. Keyword advertising refers to the advertising technique that exposes relevant advertisements on the top of research sites when one searches for a keyword. Instead of exposing advertisements to unspecified individuals like banner advertising, keyword advertising, or targeted advertising technique, shows advertisements only when customers search for a desired keyword so that only highly prospective customers are given a chance to see them. In this context, it is also referred to as search advertising. It is regarded as more aggressive advertising with a high hit rate than previous advertising in that, instead of the seller discovering customers and running an advertisement for them like TV, radios or banner advertising, it exposes advertisements to visiting customers. Keyword advertising makes it possible for a company to seek publicity on line simply by making use of a single word and to achieve a maximum of efficiency at a minimum cost. The strong point of keyword advertising is that customers are allowed to directly contact the products in question through its more efficient advertising when compared to the advertisements of mass media such as TV and radio, etc. The weak point of keyword advertising is that a company should have its advertisement registered on each and every portal site and finds it hard to exercise substantial supervision over its advertisement, there being a possibility of its advertising expenses exceeding its profits. Keyword advertising severs as the most appropriate methods of advertising for the sales and publicity of small and medium enterprises which are in need of a maximum of advertising effect at a low advertising cost. At present, keyword advertising is divided into CPC advertising and CPM advertising. The former is known as the most efficient technique, which is also referred to as advertising based on the meter rate system; A company is supposed to pay for the number of clicks on a searched keyword which users have searched. This is representatively adopted by Overture, Google's Adwords, Naver's Clickchoice, and Daum's Clicks, etc. CPM advertising is dependent upon the flat rate payment system, making a company pay for its advertisement on the basis of the number of exposure, not on the basis of the number of clicks. This method fixes a price for advertisement on the basis of 1,000-time exposure, and is mainly adopted by Naver's Timechoice, Daum's Speciallink, and Nate's Speedup, etc, At present, the CPC method is most frequently adopted. The weak point of the CPC method is that advertising cost can rise through constant clicks from the same IP. If a company makes good use of strategies for maximizing the strong points of keyword advertising and complementing its weak points, it is highly likely to turn its visitors into prospective customers. Accordingly, an advertiser should make an analysis of customers' behavior and approach them in a variety of ways, trying hard to find out what they want. With this in mind, her or she has to put multiple keywords into use when running for ads. When he or she first runs an ad, he or she should first give priority to which keyword to select. The advertiser should consider how many individuals using a search engine will click the keyword in question and how much money he or she has to pay for the advertisement. As the popular keywords that the users of search engines are frequently using are expensive in terms of a unit cost per click, the advertisers without much money for advertising at the initial phrase should pay attention to detailed keywords suitable to their budget. Detailed keywords are also referred to as peripheral keywords or extension keywords, which can be called a combination of major keywords. Most keywords are in the form of texts. The biggest strong point of text-based advertising is that it looks like search results, causing little antipathy to it. But it fails to attract much attention because of the fact that most keyword advertising is in the form of texts. Image-embedded advertising is easy to notice due to images, but it is exposed on the lower part of a web page and regarded as an advertisement, which leads to a low click through rate. However, its strong point is that its prices are lower than those of text-based advertising. If a company owns a logo or a product that is easy enough for people to recognize, the company is well advised to make good use of image-embedded advertising so as to attract Internet users' attention. Advertisers should make an analysis of their logos and examine customers' responses based on the events of sites in question and the composition of products as a vehicle for monitoring their behavior in detail. Besides, keyword advertising allows them to analyze the advertising effects of exposed keywords through the analysis of logos. The logo analysis refers to a close analysis of the current situation of a site by making an analysis of information about visitors on the basis of the analysis of the number of visitors and page view, and that of cookie values. It is in the log files generated through each Web server that a user's IP, used pages, the time when he or she uses it, and cookie values are stored. The log files contain a huge amount of data. As it is almost impossible to make a direct analysis of these log files, one is supposed to make an analysis of them by using solutions for a log analysis. The generic information that can be extracted from tools for each logo analysis includes the number of viewing the total pages, the number of average page view per day, the number of basic page view, the number of page view per visit, the total number of hits, the number of average hits per day, the number of hits per visit, the number of visits, the number of average visits per day, the net number of visitors, average visitors per day, one-time visitors, visitors who have come more than twice, and average using hours, etc. These sites are deemed to be useful for utilizing data for the analysis of the situation and current status of rival companies as well as benchmarking. As keyword advertising exposes advertisements exclusively on search-result pages, competition among advertisers attempting to preoccupy popular keywords is very fierce. Some portal sites keep on giving priority to the existing advertisers, whereas others provide chances to purchase keywords in question to all the advertisers after the advertising contract is over. If an advertiser tries to rely on keywords sensitive to seasons and timeliness in case of sites providing priority to the established advertisers, he or she may as well make a purchase of a vacant place for advertising lest he or she should miss appropriate timing for advertising. However, Naver doesn't provide priority to the existing advertisers as far as all the keyword advertisements are concerned. In this case, one can preoccupy keywords if he or she enters into a contract after confirming the contract period for advertising. This study is designed to take a look at marketing for keyword advertising and to present effective strategies for keyword advertising marketing. At present, the Korean CPC advertising market is virtually monopolized by Overture. Its strong points are that Overture is based on the CPC charging model and that advertisements are registered on the top of the most representative portal sites in Korea. These advantages serve as the most appropriate medium for small and medium enterprises to use. However, the CPC method of Overture has its weak points, too. That is, the CPC method is not the only perfect advertising model among the search advertisements in the on-line market. So it is absolutely necessary that small and medium enterprises including independent shopping malls should complement the weaknesses of the CPC method and make good use of strategies for maximizing its strengths so as to increase their sales and to create a point of contact with customers.

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A Methodology for Extracting Shopping-Related Keywords by Analyzing Internet Navigation Patterns (인터넷 검색기록 분석을 통한 쇼핑의도 포함 키워드 자동 추출 기법)

  • Kim, Mingyu;Kim, Namgyu;Jung, Inhwan
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.123-136
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    • 2014
  • Recently, online shopping has further developed as the use of the Internet and a variety of smart mobile devices becomes more prevalent. The increase in the scale of such shopping has led to the creation of many Internet shopping malls. Consequently, there is a tendency for increasingly fierce competition among online retailers, and as a result, many Internet shopping malls are making significant attempts to attract online users to their sites. One such attempt is keyword marketing, whereby a retail site pays a fee to expose its link to potential customers when they insert a specific keyword on an Internet portal site. The price related to each keyword is generally estimated by the keyword's frequency of appearance. However, it is widely accepted that the price of keywords cannot be based solely on their frequency because many keywords may appear frequently but have little relationship to shopping. This implies that it is unreasonable for an online shopping mall to spend a great deal on some keywords simply because people frequently use them. Therefore, from the perspective of shopping malls, a specialized process is required to extract meaningful keywords. Further, the demand for automating this extraction process is increasing because of the drive to improve online sales performance. In this study, we propose a methodology that can automatically extract only shopping-related keywords from the entire set of search keywords used on portal sites. We define a shopping-related keyword as a keyword that is used directly before shopping behaviors. In other words, only search keywords that direct the search results page to shopping-related pages are extracted from among the entire set of search keywords. A comparison is then made between the extracted keywords' rankings and the rankings of the entire set of search keywords. Two types of data are used in our study's experiment: web browsing history from July 1, 2012 to June 30, 2013, and site information. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The original sample dataset contains 150 million transaction logs. First, portal sites are selected, and search keywords in those sites are extracted. Search keywords can be easily extracted by simple parsing. The extracted keywords are ranked according to their frequency. The experiment uses approximately 3.9 million search results from Korea's largest search portal site. As a result, a total of 344,822 search keywords were extracted. Next, by using web browsing history and site information, the shopping-related keywords were taken from the entire set of search keywords. As a result, we obtained 4,709 shopping-related keywords. For performance evaluation, we compared the hit ratios of all the search keywords with the shopping-related keywords. To achieve this, we extracted 80,298 search keywords from several Internet shopping malls and then chose the top 1,000 keywords as a set of true shopping keywords. We measured precision, recall, and F-scores of the entire amount of keywords and the shopping-related keywords. The F-Score was formulated by calculating the harmonic mean of precision and recall. The precision, recall, and F-score of shopping-related keywords derived by the proposed methodology were revealed to be higher than those of the entire number of keywords. This study proposes a scheme that is able to obtain shopping-related keywords in a relatively simple manner. We could easily extract shopping-related keywords simply by examining transactions whose next visit is a shopping mall. The resultant shopping-related keyword set is expected to be a useful asset for many shopping malls that participate in keyword marketing. Moreover, the proposed methodology can be easily applied to the construction of special area-related keywords as well as shopping-related ones.

A Study on the Change of Tourism Marketing Trends through Big Data

  • Se-won Jeon;Gi-Hwan Ryu
    • International journal of advanced smart convergence
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    • v.13 no.2
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    • pp.166-171
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    • 2024
  • Recently, there has been an increasing trend in the role of social media in tourism marketing. We analyze changes in tourism marketing trends using tourism marketing keywords through social media networks. The aim is to understand marketing trends based on the analyzed data and effectively create, maintain, and manage customers, as well as efficiently supply tourism products. Data was collected using web data from platforms such as Naver, Google, and Daum through TexTom. The data collection period was set for one year, from December 1, 2022, to December 1, 2023. The collected data, after undergoing refinement, was analyzed as keyword networks based on frequency analysis results. Network visualization and CONCOR analysis were conducted using the Ucinet program. The top words in frequency were 'tourists,' 'promotion,' 'travel,' and 'research.' Clusters were categorized into four: tourism field, tourism products, marketing, and motivation for visits. Through this, it was confirmed that tourism marketing is being conducted in various tourism sectors such as MICE, medical tourism, and conventions. Utilizing digital marketing via online platforms, tourism products are promoted to tourists, and unique tourism products are developed to increase city branding and tourism demand through integrated tourism content. We identify trends in tourism marketing, providing tourists with a positive image and contributing to the activation of local tourism.