The realm of advertising, in particular, has experienced remarkable changes fueled by AI’s ability to sift through vast volumes of data, identify patterns, and generate insights that lead to more informed and efficient decision-making.
One such decision-making process revolutionized by AI is programmatic advertising bidding. AI’s inherent ability to identify the most suitable audiences for specific ads help determine the most opportune moments and ideal platforms for ad display. This precision level helps advertisers get a more significant return on their ad spend.
Today’s post examines automated versus manual bidding and explores the unique advantages of integrating AI into these processes.
Automated bidding eclipsed manual bidding
Because most advertising channels are now auction-priced mediums, understanding the ins and outs of effective bidding has become one of the fundamental skills of marketers. Few practitioners will argue that a solid bidding strategy can mean the difference between a successful ad campaign and one that fails to meet its goals.
As digital advertising’s landscape evolved, the process of ad bidding has seen significant advancements. Manual bidding, once the staple of ad campaigns, has gradually given way to automated strategies, and for a good reason.
With manual bidding, advertisers need to manually set and adjust their bids for each ad impression. This requires a considerable amount of time and effort and leaves room for human error. Moreover, the manual bidding process can become incredibly complex when dealing with large-scale campaigns that involve numerous ad placements across various platforms.
On the other hand, automated bidding — which has become the norm — eliminates these issues.
Automated systems can analyze vast amounts of data and adjust bids in real-time, ensuring optimal ad performance without the need for continuous manual intervention. In addition, these systems can consider a wider range of factors than a human possibly could, from user behavior patterns to market conditions, leading to more effective
Rules-based vs. AI Bidding
The first type of automated bidding to supplant manual methods, rules-based bidding, has become the gold standard of auction-based advertising. It relies on predefined rules set by advertisers specifying how much they will pay for ad impressions. For instance, an advertiser might set a rule to pay up to $1.50 per thousand impressions on a particular website.
While this approach provides a level of control and predictability, it comes with its set of limitations. Even though much of it is automated, practitioners must set up, monitor, and optimize the rules that drive rules-based bidding. It necessitates continuous manual intervention, which can be labor-intensive and prone to human errors. Plus, its effectiveness is restricted by the number of rules that can be set. Advertisers may only reach specific audience segments or leverage particular platforms if they have set a specific rule.
However, as new AI bidding capitalizes on machine learning algorithms to process vast amounts of data in real-time, automated bidding is, well, in fact, finally becoming more automated.
AI algorithms consider user behavior, ad engagement, and market conditions to determine the most effective bid for a particular ad impression. For example, if an advertiser bid on a sports website during a major event, AI could recognize increased viewer engagement and adjust bids accordingly.
The beauty of AI bidding lies in its adaptability and breadth of consideration. It can swiftly adapt to changes in market conditions or competitive landscapes. If a competitor suddenly escalates their bids for a specific audience segment, the AI system can respond in real-time to keep you in the competition.
AI bidding also considers a broader range of variables than its rules-based counterpart. It can integrate and analyze data from various sources like social media platforms, search engines, and website analytics, enabling a more comprehensive understanding of the audience and market dynamics. This holistic view allows for more effective and efficient targeting of audience bidding decisions.
AI-powered bidding will soon be the norm
Ultimately, AI bidding is significantly advantageous over rules-based or manual bidding strategies in the ever-evolving digital advertising landscape. With the ability to adapt instantaneously to market fluctuations, factor in the broader array of variables, and make real-time optimizations, AI will quickly redefine the bidding landscape. By integrating AI into their bidding strategies, advertisers can amplify their campaigns’ performance and extract the maximum value from their ad spend.
The transformative power of AI in advertising bidding is more than just a trend; it’s a seismic shift redefining the industry norms. AI is not just the future of advertising bidding — it’s already here, making waves and setting new standards. It’s time for advertisers to ride this wave and reap the benefits of AI-driven bidding.
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