Click Through Rate

click through rate is the ratio of users who click on a spesifik link to the number of total users who view a page, email or advertisement. It is commonly used to measure the success of an online advertising campaign for a particular website as well as the effectiveness of email campaigns.

Click through rates for ad campaign vary tremendously. The very first online display ad shown for AT&T on website hotwired in 1994, had a 44% click through rate. Over time the over all rate users click on webpage banner ads has decreased.

The purpose of click-through rates is to measure the ratio of clicks to impressions of an online ad or email marketing campaign. Generally the higher the CTR the more effective the marketing campaign has been at bringing people to a website.[4] Most commercial websites are designed to elicit some sort of action, whether it be to buy a book, read a news article, watch a music video, or search for a flight. People rarely visit websites with the intention of viewing advertisements, in the same way that few people watch television to view the commercials.

Construction:

The click-through rate is the number of times a click is made on the advertisement divided by the total impressions (the number of times an advertisement was served):

Click-through rate = Click-throughs (#) / Impressions (#)

Online advertising CTR:

The click-through rate of an advertisement is defined as the number of clicks on an ad divided by the number of times the ad is shown (impressions), expressed as a percentage. For example, if a banner ad is delivered 100 times (100 impressions) and receives one click, then the click-through rate for the advertisement would be 1%.

CTR = CLICKS/IMPRESSIONSX100

Example:

Click = 4 | Impressions = 304 CTR = 4/304*100 = 1,316 CTR

Click-through rates for banner ads have decreased over time. When banner ads first started to appear, it was not uncommon to have rates above five percent. They have fallen since then, currently averaging closer to 0.2 or 0.3 percent.In most cases, a 2% click-through rate would be considered very successful, though the exact number is hotly debated and would vary depending on the situation. The average click-through rate of 3% in the 1990s declined to 2.4%–0.4% by 2002.[13] Since advertisers typically pay more for a high click-through rate, getting many click-throughs with few purchases is undesirable to advertisers.Similarly, by selecting an appropriate advertising site with high affinity (e.g., a movie magazine for a movie advertisement), the same banner can achieve a substantially higher CTR. Though personalized ads, unusual formats, and more obtrusive ads typically result in higher click-through rates than standard banner ads, overly intrusive ads are often avoided by viewers.

Modern online advertising has moved beyond just using banner ads. Popular search engines allow advertisers to display ads in with the search results triggered by a search user. These ads are usually in text format and may include additional links and information like phone numbers, addresses and specific product pages.[15] This additional information moves away from the poor user experience that can be created from intrusive banner ads and provides useful information to the search user, resulting in higher Click-through rates for this format of Pay Per Click Advertising. Having high click-through rate isn't the only goal for an online advertiser who will occasionally develop campaigns to raise awareness and sacrifice click-through rate for the overall gain of valuable traffic.

Estimating the Click-Through Rate for Ads:

Search engine advertising has become a significant element of the Web browsing experience. Choosing the right ads for the query and the order in which they are displayed greatly affects the probability that a user will see and click on each ad. This ranking has a strong impact on the revenue the search engine receives from the ads. Further, showing the user an ad that they prefer to click on improves user satisfaction. For these reasons, there is an increasing interest in accurately estimating the click-through rate of ads in a recommender system.

sumber: wikipedia

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