What is Automated Bidding?

Automated bidding, or programmatic, is a strategy in digital advertising whereby advertisers leverage machine learning algorithms to handle the process of bidding for ad space on publisher platforms. It is a foundational component of the programmatic advertising ecosystem, and a key part of how advertisers manage ads at scale and maximize the performance of campaigns in order to achieve their goals.

Automated Bidding in Programmatic Advertising

Automated bidding is a fundamental component of programmatic advertising, enabling advertisers to purchase ad inventory in real time. Through integration with demand-side platforms (DSPs) and supply-side platforms (SSPs) advertisers can access diverse ad networks and bid dynamically based on predefined parameters. This process eliminates manual intervention, allowing campaigns to scale efficiently while maintaining alignment with advertiser goals.

How does automated bidding work?

The process of automated bidding comprises several key phrases: 

• Setting objectives: The advertiser begins by deciding what they want to achieve specifically, such as generating more conversions or increasing traffic to their site. This will inform how they go about utilizing automated bidding.
• Configuring the DSP: The advertiser sets up a demand-side platform (DSP), which connects them to third-party ad servers and networks where they can gain access to a wide range of ad inventory. This involves setting parameters for the types of inventory and publishers they are looking for, as well as bid parameters. They also set a bidding strategy that aligns with their goals, for instance, to optimize cost per acquisition (CPA) or return on ad spend (ROAS).
• Real-time auction: Once the advertisers have set up their DSP correctly, they can begin bidding for ad space. The DSP identifies suitable websites and platforms that align with the advertiser’s parameters and then makes automated bids on their ad inventory. Auctions take place immediately whenever a user visits a publisher’s platform, with advertisers engaging in real-time bidding. Throughout this process, the advertiser’s DSP uses algorithms to dynamically adjust bids and maximize cost efficiency.
• Analysis and optimization: The advertiser accesses the dashboard of their DSP, where they monitor their ad performance. They can then adjust their budget and targeting criteria where necessary to optimize their campaigns.

What are the advantages of automated bidding?

The key advantage of automated bidding lies in its ability to optimize ad performance using real-time data. By dynamically adjusting bids based on user behavior, competition, and campaign objectives, automated bidding ensures cost efficiency and precision targeting. This adaptability makes it a cornerstone of modern digital advertising strategies. Here are some advantages of Automated bidding:

• Workflow efficiency: Automated bidding eliminates the need to manually adjust and submit bids to publishers. This streamlines workflows, enabling marketers to invest time into more strategic or creative aspects of campaigns.
• Scalability: Automated bidding platforms can deal with complex bidding environments and large volumes of data with relative ease. This enables advertisers to manage a greater variety of campaigns and operate more effectively at scale.
• Real-time agility: By using automated bidding, advertisers can respond to situational changes with greater agility. Using data and machine learning, DSPs will automatically adjust bids in accordance with changes in user behavior or competition, for instance, to optimize performance.

Precision targeting: By leveraging machine learning algorithms, automating bidding platforms like DSPs can dynamically their approach, incorporating factors like user demographics, location, device type, and much more. This makes it much easier to target specific niche audiences with whom ads will perform well on key engagement metrics.

Conclusion

Automated bidding streamlines the process of buying ad inventory by leveraging machine learning to deliver efficiency, scalability, and precision. Its role in programmatic advertising is central to achieving campaign objectives, making it a critical tool for advertisers in the digital ecosystem.