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Automated Bid Adjustments in Search Engine Advertising

Written by Mazen Aly

Paper category

Bachelor Thesis


Business Administration>Marketing & Sales




Thesis: The search engine perspective The research proposed in this paper mainly solves advertising problems from the perspective of advertisers. However, it is also important to consider the point of view of search engines, because advertisers' work stems from search engines. For this reason, this section introduces the challenges faced by advertising from the perspective of search engines. Rather than paying for impressions, advertisers prefer Overture’s model of paying only for clicks. Google is another search engine that is just getting started. Around 2002, it adopted a model very similar to Overture and launched their advertising platform Adwords. Google has made some important changes to the Overture model in terms of how advertisers bid and the ads displayed. Adwords receives a set of keywords and their respective bids from each advertiser. It also receives a stream of search queries from users. The challenge is to select and display several advertisements from many possible advertisements that are eligible to be displayed for the same search query. It is worth mentioning that the goal of a search engine is to maximize its revenue by displaying an appropriate advertising set. It requires an online algorithm. This means that search engines can only see one query at a time and must make an irrevocable decision to decide which advertisement to display. It can’t go back and change the ads shown in the past, and it doesn’t know what queries will appear in the future. Overture uses a naive heuristic to sort advertisers by bid, and the highest bidding ad will be ranked first. It turns out that this is not the best way, because ads behave very differently in terms of how often they are clicked. Therefore, putting the ads of the highest bidders first is not the best algorithm for maximizing search engine revenue. The contribution of Google Adwords is the introduction of using the average click-through rate of each advertisement to calculate the expected revenue of each advertiser multiplied by the bid and the click-through rate of the advertisement. In other words, it sorts advertisers by expected revenue, not by bid. If the CTR of each advertisement is known and the advertiser’s budget is not limited, then a simple algorithm of sorting advertisers by expected revenue is actually optimal, but in fact advertisers do not have unlimited budgets and clicks on ads The rate is unknown. The balance algorithm is aimed at the situation of advertisers with limited budget. In order to estimate the click-through rate of an advertisement, a very simple solution can be thought of, that is, to display a large number of advertisements and calculate the historical click-through rate. Although this is the correct approach, there are two challenges with this approach. The first is that the click-through rate actually depends on location, because search engines may display multiple ads for a given query. 2.1.2 Search advertising terms In order to understand the topics discussed in this project [36], it is important to understand the most commonly used definitions throughout the paper. Cost-per-click (CPC): The maximum cost an advertiser pays when clicking on an ad. Cost-per-click: The highest price an advertiser is willing to pay when clicking on an ad. Average cost-per-click: The average cost an advertiser pays per click. It is the ratio of the total cost to the total number of clicks. Cost: The total amount the advertiser spends on clicks. Conversion rate (CR): The ratio of conversion rate to ad clicks. Cost Per Acquisition (CPA): The average cost an advertiser pays for each conversion. It is the ratio of total cost to total conversions. Inverse of Cost Per Acquisition (ICPA): It is the ratio of the total number of conversions to the total cost. Return on Ad Spend (ROAS): Ratio of total revenue to total cost. Improving conversion rates requires optimizing impressions and clicks. In a conversion funnel consisting of three stages, impressions, clicks, and conversions. Each phase of the funnel is narrower than the previous phase. Therefore, the process of increasing the number of conversions needs to increase the number of relevant impressions, thereby increasing the number of relevant clicks, and thus leading to more conversions. 2.1.3 Advertising auctions In order to place advertisements on SERPs, advertisers enter the auction between all advertisers who bid for advertisements with keywords that match the user's query. There are many types of auctions, but the standard auction used extensively in the literature is the Generalized Second Price Auction (GSP) [25]. In a GSP auction, the price paid by each advertiser is equal to the bid of the advertiser who ranks below them. Since we are using the Adwords platform in this project, it is important to describe how Googleauction (which is a variant of GSP) works. The motive of the auction is to reconcile the interests of the three parties, namely advertisers, users and search engine Google. Each party has concerns or motivations to participate in the auction. Advertisers want to display relevant advertisements for their products or services so that users can click on them and possibly convert. Users do not want to be disturbed by spam or other irrelevant advertisements. Google hopes to create revenue and create a good experience for advertisers and users so that they can use its services again in the future. Every time a user makes a query on Google, ads related to the search query (in terms of keyword similarity) will participate in the ad auction. The auction determines whether the ad will be displayed and where in the SERP it will be displayed. The first step in the auction is for Google to ignore substandard advertisements. Read Less