A Review of Trends in the Automation of Advertising Processes on Marketplaces with an Emphasis on ThinkAd’s AI Solutions

Аннотация

This paper covers the history and current trends in the automation of advertising workflow CITATION Dmytro Balan. (2025). A Review of Trends in the Automation of within marketplaces through AI solutions provided by Advertising Processes on Marketplaces with an Emphasis on ThinkAd’s AI Solutions. The American Journal of Management and Economics the ThinkAd platform. The study shall attempt to detail Innovations, 7(06), 82–89. drivers that have prompted a transition from manual https://doi.org/10.37547/tajmei/Volume07Issue06-08 bidding to intelligent autopilots. It also tries to present COPYRIGHT comparative analyses regarding the functionalities of © 2025 Original content from this work may be used under the terms of the creative commons attributes 4.0 License. leading AI services and empirical assessments of their effectiveness via real-world case studies. Such a work is meaningful since there has been a strong upward trend in cost-per-click on Amazon Ads, coupled with increasing difficulties that come with manual management regarding hundreds of thousands of product × keyword × time combinations, which cause both budget overruns and lost sales. Simultaneously, first-party data gains value in a cookieless world; intense competition demands instant strategy changes via hyper-personalization and goal-based bidding. The novelty of the study lies in the integration of descriptive statistics on CPC dynamics and sellers’ time savings, content- and case-analysis of AI-platform technical documentation, and a functional comparison of semantic-core generation modules, goal-based bidding, hourly day-parting, and multi-account mastering. Particular attention is paid to the ThinkAd platform, which forecasts ACoS 24 hours in advance, updates bids hourly, and consolidates data across multiple stores. The main findings indicate that intelligent automation can reduce ACoS to 22–25% while increasing advertising sales by 82–206%, freeing up to 20 hours of operational time per week, and The American Journal of Management and Economics Innovations 82 https://www.theamericanjournals.com/index.php/tajmei ensuring competitiveness for small and medium strategic decisions—testing new creatives, expanding enterprises under cookieless conditions and rising click assortments, and negotiating with suppliers—instead of costs. Integrated via the Amazon Ads API and supporting endless manual bid adjustments. multiple regions, ThinkAd sets a new efficiency standard As a result, advertising on marketplaces is no longer by combining a semantic module, predictive analytics, manual labor, not because specialists have become idle, and an autopilot. This article will be helpful to but because human time has become too expensive for marketplace advertising managers, e-commerce tasks that machines perform faster, more accurately, analysts, and small and medium business owners when and cheaply. The emergence of specialized AI platforms selecting and implementing AI tools for advertising such as ThinkAd marks a point of no return: algorithms campaign automation. assume operational routines, allowing companies of all Keywords: AI automation, marketplaces, ThinkAd, goal- sizes to compete with large brands based on reaction based bidding, day-parting, first-party data, ACoS, CPC. speed and data rather than budget size. INTRODUCTION MATERIALS AND METHODOLOGY Over the past eight years, advertising on marketplaces The research materials include an extensive review of has evolved from manual techniques into a publicly available sources and cases demonstrating the sophisticated system in which each keyword evolution of advertising processes on marketplaces and participates in instantaneous auctions and platform the application of AI solutions. Empirical data were algorithms apply real-time bid adjustments. A steady drawn from statistical reports on the dynamics of rise in cost-per-click accompanies competition for average click prices in Amazon Ads [1], figures on the customer attention on Amazon. For small and medium share of sellers who have already implemented AI tools enterprises with limited advertising budgets, the for listing and marketing optimization [2, 3], Google Ads previous approach of setting a bid and waiting for a Help materials on the upcoming deprecation of third- weekly report has ceased to be cost-effective: any party cookies [4], and studies on the role of first-party delayed action results in overspending and lost sales. data in a cookieless environment [5]. Additionally, technical changes in Amazon Dynamic Segments [6], Simultaneously, the informational burden has McKinsey’s findings on the effectiveness of hyper- increased. Today, merchandisers and marketers must personalization [7], and AWS reviews on the use of manage bids and maintain synchronization of prices, generative AI in retail [8] were analyzed. inventories, and content across dozens of platforms, monitor new ad formats, and adjust negative keywords. To evaluate practical AI