The metrics of measuring the effectiveness of web ads

• Main Authors: Tien Chi-Fang, 田季芳
• Other Authors: 陳亭羽
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/67177216676876806072

碩士 === 長庚大學 === 企業管理研究所 === 92 === With the rapid growing number of internet users, the market of internet has become flourishing. Web advertisements become another focus for advertisers, therefore, the issue of how to measure web advertisements’ effectiveness has become more and more important. Although there are many advertisement measurement indexes nowadays, the validity was queried. Besides, there is no specific rule for advertisers. Base on the reasons mention above, this research attempt to discuss the indexes through expert interviews and develop an evaluation model which can be applied in Taiwan. After literature review, we find that advertising-effects model which includes interactive factors can completely describe users’ browsing behavior. Therefore, we quote media model of ARF to be our framework, and try to find out some useful metrics for each stage. In order to be more objective, we use different dimensions to analyze our study. In first stage, we use questionnaires to find out the most important index characters in practice, then apply rank reciprocal weight, rank sum weight, and linear assignment methods to analyze it. The result shows that relevance, clear, and sensitivity are the most important characters in practice. Hence, the follow-up evaluation will base on it. In second stage, we interview key users of Web index. After integrated different opinions, we get the following conclusions: 1. Superior-index characters have different weight. The view of advertiser, ad-agent, and portal site are very similar in this point. Relevance, clear, and sensitivity are the most important characters. It deserves to be mentioned that consistency is most important for portal site, there is no difference in other opinions. 2. Web media suitable for interactive advertising-effects model. This is the biggest difference between models nowadays and those in the past. 3. Different metrics suitable for different stages among hierarchy models. This research provides complete measurements for each stage. 4. New metrics follow users’ need. Besides existing metrics, there are also some new metrics for using which bring up by experts, such as average impression, impression rate, advertisement duration time, ARO, effectiveness, e-coupon using rate, etc.