This study focused on the role of automation and prediction about the future of a specific type of online advertising - pay-per-click advertising (PPC). The PPC advertising, also known as cost-per-click advertising is a competition-based charging method, which is a click-based purchase model for advertisers and charges them for only clicks that reflect the visits to the links provided by the advertiser. An amount that advertisers pay is calculated by predetermined factors by search engines, which are related to the bidding of competitors and quality of content published by the advertiser. After the rise of online advertising, companies attempt to target specific audiences with PPC advertising solutions on search engines by using detailed targeting options. PPC did not help companies only on search engines, but also served as a billboard on various websites that are Display Network’s partners like Google Display Network, Yandex Ad Network etc. Advertisers got the benefit of using contextual advertising and getting rare audiences with specific targeting features. Additionally, businesses were able to make data-driven marketing decisions by analysing historical data and switched from old school intuition-based decisions to data-driven decisions in this new digital marketing era. From the beginning of the rise of internet or online marketing, Pay-Per-Click become an actor in main marketing activities, merging 4 sides - PPC vendors (Google, Bing etc.) advertisers (businesses promoting their services and products), publisher websites who act as placements for display ads, internet users who are potential buyers and seek for information about products or services in different intent cycles like in sales funnel. In non-display ads, search engines themselves act as publishers of sponsored ads. Therefore, advertisers focus on focus keywords of internet users and other variables that affect the conversion probability of them, such as time, device category, household income, gender information provided by the advertising platform. As the advertising effectiveness depends on several factors, growing large PPC accounts become hard to manage and optimize. In that stage, automated optimization and management solutions become economically and practically available. Increasing the efficiency requires human intuition and routine optimization tasks for PPC managers in manual bidding. Although manual bidding gives more control on the PPC campaigns, larger accounts create larger challenges when managing thousands of keywords and ad groups. Additionally, human intelligence lacks to find all correlation among different variables for several campaigns at the same time. In order to decrease this guesswork many PPC management tools offered by third parties and Google Ads introduced its solutions to increase the advertiser experience. Both PPC agencies, which serve companies in the optimization, reporting, management of the advertising campaigns, third-party software companies and PPC platforms (Google, Bing etc.) introduce their unique solutions to manage PPC accounts. This study investigates the effect of automation solutions introduced by Google Ads, analyzes the results of using Google Ads Smart Bidding Strategies and the marketplace of PPC Automation, and gives a future prediction about the possible changes in the way of automation with non-empirical research.

This study focused on the role of automation and prediction about the future of a specific type of online advertising - pay-per-click advertising (PPC).