AI Marketing
Intermediate
4 min read
What is automated bidding?
Automated bidding uses artificial intelligence to optimize ad bids in real-time, aiming to achieve specific marketing goals like conversions or clicks more efficiently.
Key points
- Uses AI and machine learning to manage ad bids automatically.
- Optimizes bids in real-time based on various data signals.
- Aims to achieve specific marketing goals like conversions or clicks.
- Saves time and often improves campaign performance and efficiency.
Automated bidding is a powerful feature in digital advertising that uses artificial intelligence (AI) and machine learning to manage your ad bids automatically. Instead of you manually setting how much to pay for each click or impression, the system takes over. It analyzes a vast amount of data, including user behavior, device type, location, time of day, and historical performance, to decide the optimal bid for each ad auction.
The goal of automated bidding is to help you achieve your marketing objectives more effectively within your budget. Whether you want to get more website visits, increase sales, or generate leads, automated bidding strategies are designed to find the best opportunities to show your ads and get the desired outcome without constant manual adjustments.
Why it matters for marketing teams
Automated bidding brings several significant advantages to marketing teams. First, it saves a lot of time. Instead of spending hours adjusting bids, marketers can focus on strategy, ad copy, and creative development. Second, it often leads to improved performance. AI can process data and identify patterns far beyond human capabilities, making more precise bid adjustments that can increase conversions or lower costs per acquisition. It also allows for real-time optimization. The digital advertising landscape changes constantly, and automated bidding can react to these shifts instantly. This means your campaigns are always working to their full potential, adapting to new trends or competitive changes without delay. Ultimately, it helps marketing teams get a better return on their advertising investment by making smarter, data-driven decisions.How automated bidding works
At its core, automated bidding relies on complex algorithms that learn from your campaign data. When you select an automated bidding strategy, you tell the system your primary goal. For example, you might want to maximize conversions, reach a target cost per acquisition (CPA), or achieve a certain return on ad spend (ROAS). The system then uses machine learning to predict the likelihood of a conversion or other desired action for each potential ad impression. Based on these predictions and your set goals, it adjusts your bid in real time for every auction. This means a user who is highly likely to convert might receive a higher bid, while a user less likely to convert might receive a lower bid, all to optimize for your chosen objective.Common bidding strategies
- Maximize conversions: Aims to get the most conversions possible within your budget.
- Target CPA (cost per acquisition): Tries to get as many conversions as possible at or below a specific average cost per conversion.
- Target ROAS (return on ad spend): Focuses on achieving a specific average return on ad spend, useful for e-commerce.
- Maximize clicks: Designed to get the most clicks possible within your budget, often used for brand awareness or website traffic.
Best practices for using automated bidding
To get the most out of automated bidding, there are a few key practices marketing teams should follow:- Ensure accurate conversion tracking: Automated bidding relies heavily on conversion data. Make sure your conversion tracking is set up correctly and reliably reports all the actions you want to optimize for.
- Provide enough data: Automated systems learn from historical data. Campaigns need a sufficient volume of conversions (often at least 15-30 per month, depending on the platform) for the algorithms to learn and optimize effectively.
- Set realistic goals: While automated bidding is powerful, it's not magic. Set target CPAs or ROAS goals that are achievable based on your historical performance and market conditions.
- Be patient and monitor: Give the system time to learn and optimize, usually a few weeks. Avoid making drastic changes too frequently, as this can disrupt the learning process. Monitor key metrics but resist the urge to micro-manage.
- Combine with other optimizations: Automated bidding works best when combined with other strong marketing fundamentals, such as compelling ad copy, relevant landing pages, and proper audience targeting.
Real-world examples
E-commerce store boosts sales
An online shoe retailer uses Google Ads' "maximize conversions" bidding strategy. The system automatically adjusts bids for different keywords, user devices, and times of day, leading to a 15% increase in online sales within a quarter for the same budget.
SaaS company improves lead quality
A B2B software company uses Meta Ads' "target CPA" bidding to acquire new leads. The automated system learns which users are most likely to fill out a demo request form, bringing down their average cost per qualified lead by 20% over two months.
Common mistakes to avoid
- Not having proper conversion tracking set up, which starves the system of vital data.
- Making too many manual changes too quickly, which disrupts the learning phase of the automated system.
- Setting unrealistic target goals (e.g., a target CPA that's much lower than historical performance), hindering the system's ability to bid effectively.