Google Quality Score
In optimizing their revenue from advertising, Google is incentivized to have the best ads on their site so that they can get the most money for each ad slot–a higher click through rate on an ad will yield greater profits. If an ad is bad, they’ll charge more for it to make up for the lost profits in decreased click through rate. As a result, a search engine, “Rather than assigning advertisers to the best slots in decreasing order of their bids, bj, . . . assigns them in decreasing order of the product of their bid and quality factor, qjbj” (Easley and Kleinberg p.460). Further, because the search engine completely controls the method for computing the quality score and does not make it publicly known to advertisers, it provides companies like Google the power to control the ultimate ordering of advertisers in slots. At the same time, this quality calculation also gives advertisers a way to effectively pay less for a better slot by achieving a higher quality score. Consequently, understanding how to improve this “mysterious” quality score provides valuable information for advertisers.
Google’s algorithm to measure the “quality” of ads is determined by the factors of click through rate (how many people click on the ad), landing page experience (that takes into account mobile browsers), and relevance to the searched term. The quality of the ad is then measured up and compared to other ads that are vying for the same ad slot. Each of these factors are given a rating of “below average”, “average” and “above average,” which contribute to the total quality score that ranges between 1-10. In his article, a chapter from a book, Frederick Vallaeys looks in depth at how advertisers can modify their ads in order to increase their quality score by improving their rating on each of these factors.
Vallaeys defines expected click through rate as a measure of “how likely your ad is to generate a click when the search term is exactly the same as your key word” (Vallaeys). He advises avoiding generic words that can mean many things rather than specific keywords and instead suggests, for example, using the keyword “dog food” versus “dog” if your ad is about dog food. With respect to landing page experience, Vallaeys describes it as whether a user immediately leaves your page or stays. He highlights several features that contribute in a positive way to the user’s experience. Some features are technical, such as how quickly the web page loads and the quality/ease of use of the web page on a mobile device. Others include a targeted page or content rather than simply landing on the homepage. For the final factor, ad relevance, Vallaeys recommends breaking up ads into smaller ad groups, each of which targets a specific service or product from a broader selection and ties to more targeted keywords.
Interestingly, one company that offers a tool for optimizing Google ad campaigns, claims to have studied the advertising campaigns of over 15,000 companies worldwide and determined a more precise formulation of the quality score calculation. In their analysis, they state that improving click through rate and landing page experience helps the ad’s quality score twice as much as keyword relevance (SEISO).
We are learning about how search engines auction off different ad slots and how they make revenue from that and try to optimize it. This article goes more in depth about the specific way that Google rates these ads using a quality score and makes the decision on who wins the auctions. Through the quality score Google can ensure they get the best ads included in the auctions and advertisers can use this information to achieve a higher ad ranking.
Citations:
https://searchengineland.com/google-ads-the-quality-score-formula-revealed-348063
https://www.searchenginejournal.com/ppc-guide/quality-score/#close
https://www.cs.cornell.edu/home/kleinber/networks-book/networks-book-ch15.pdf
-Camila Orr