Bidding strategies fueled by AI can help businesses large or small deliver ROI and unlock new growth avenues.

As the integration of AI into business strategies continues to grow, only a small percentage of companies are utilizing it to its full potential. Helen Mussard, the Chief Marketing Officer of IAB Europe, along with two marketing experts have agreed that AI is transforming bidding strategies and providing companies with a competitive advantage. Nick Brady, the Head of Search Bidding Growth and Optimization Score at Google, and Alvaro Verdeja, the Global Data and Cloud Director at Making Science, have also confirmed real benefits of predictive AI in bidding and how it can be used to maximize value.

These experts are providing an data and confirmations of how AI in bidding algorithms is realistically working to deliver predictive decision making data for ROI and new growth avenues for businesses. The importance of predictive AI in understanding consumer behavior and setting accurate bids is going to be the wave of the future.

The benefits of value-based bidding, include its alignment with business objectives and the ability to adapt in real-time to changing environments. I will also provide real-world examples of how predictive AI has been used to optimize bidding strategies, such as with a hotel chain’s cancellation policy. Finally, I will offer tips for maximizing the value of AI in bidding, including focusing on data quality, breaking down data silos, and prioritizing real-time decision-making.

Key Takeaways

• Predictive AI is essential in understanding consumer behavior and accurately setting bids in bidding algorithms.
• Value-based bidding offers benefits such as alignment with business objectives and real-time adaptability.
• To maximize the value of AI in bidding, companies should focus on data quality, breaking down data silos, and prioritizing real-time decision-making.

Overview of AI in Bidding Algorithms

AI has become increasingly integrated into business strategies, with three-quarters of organizations utilizing it in some form. However, only 12% of these organizations are using AI at a level that gives them a competitive advantage.

Predictive AI is a key component of bidding algorithms and has been around for many years. It is used in a variety of Google tools, such as Google Maps and Gmail, and is particularly important in bidding, where it can take into account billions of signals to predict how likely a user is to convert and how much they are likely to spend. Value-based bidding (VBB) is one area where predictive AI is particularly useful.

VBB is aligned with business objectives and can adapt in real-time based on customer changes, business changes, or macro-environment changes. For example, a retailer with varying profit margins across different product categories can pass margin data to VBB, which will automatically place bids based on product margins. This means that VBB can maximize overall margin by placing higher bids on products with higher margins and lower bids on products with lower margins.

One key benefit of VBB is its ability to respond in real-time based on changing circumstances. For example, a hotel chain that experienced a sudden increase in cancellations due to COVID-19 was able to use VBB to predict which bookings were likely to be cancelled and adjust their bidding strategy accordingly. This flexibility is a key advantage of VBB.

To maximize the value of AI in bidding algorithms, it is important to focus on data quality and to start small, improving accuracy over time. Real-time responsiveness is also crucial in the digital world, where circumstances can change rapidly. By following these tips and taking advantage of predictive AI in VBB, marketers can build a competitive advantage and achieve better results.

Predictive AI and Its Applications

According to a recent study, 75% of organizations have incorporated AI into their business strategies, but only 12% are using it at a level that gives them a strong competitive advantage. Predictive AI, which has been around for many years, is being used in bidding algorithms to help marketers and their companies build a competitive advantage.

Predictive AI is able to take in and incorporate billions of signals to predict how likely each user is to convert and how much they are likely to spend. This is particularly useful in value-based bidding, where the main benefits for marketers are that it is aligned with their business objectives and can adapt in real-time based on customer changes, business changes, or macro-environmental changes.

Value-based bidding can be used to optimize bids based on products that have higher margins, lower margins, and everything in between. This means that over the course of thousands or hundreds of thousands of products, it is maximizing overall margins just by using data and being able to do that in real-time.

Making Science, a digital acceleration company, has been investing in a platform called GA AI for six years. This platform makes it easy to get data, make predictions, and activate data into bidding platforms like Google Ads. They have seen this as an advantage in performance marketing in many sectors such as education, e-commerce, and travel.

One of the customers that Making Science worked with is a hotel chain called Ru. They had to rethink their business model because of cancellations due to COVID-19. Making Science was able to help Ru get signals like time of the day, device, and channel to make a prediction if those users were going to cancel or not. With this prediction, they were able to tell Google and other platforms which bookings were worth it and which ones were not. Google’s algorithm was then able to bring the good users that they were looking for who would not cancel.

To maximize the value of AI, it is important to focus on doing things step by step and improving accuracy gradually. It is better to have good data than a lot of data. It is also important to focus on being real-time and breaking data silos. By taking this approach, AI can be used by everyone, not just e-commerce companies or digital natives.

Value-Based Bidding (VBB) Benefits

Value-Based Bidding (VBB) is an AI-powered bidding strategy that is revolutionizing the way marketers build a competitive advantage. By aligning with business objectives and adapting in real-time based on customer changes, VBB is helping marketers achieve their goals and maximize their overall margin.

One of the main benefits of VBB is its ability to incorporate billions of signals to predict how likely each user is to convert and how much they are likely to spend. This predictive AI is able to set accurate bids based on the advertiser’s goals, ensuring that the bids are aligned with the business objectives.

Moreover, VBB is able to optimize bids based on product categories with varying profit margins. By passing margin data to VBB, it can automatically place bids based on products with higher margins, lower margins, and everything in between, maximizing overall margin.

Real-time adaptation is another key benefit of VBB. It can adapt to changes in customer behavior, business changes, or macro environment changes in real-time, ensuring that bids are always optimized for maximum performance.

To maximize the value of AI in bidding strategies, marketers should focus on using their own data, testing it, and improving it step by step. Data quality and breaking data silos are also crucial for effective AI-powered bidding. Additionally, marketers should prioritize real-time optimization to ensure that bids are always aligned with the changing market conditions.

Real-World Applications of Predictive AI in Marketing

According to a recent study, only 12% of organizations are currently using AI at a level that gives them a strong competitive advantage. Predictive AI, which has been around for many years, is one area where AI is revolutionizing bidding strategies and helping marketers build a competitive advantage. AI is being used in value-based bidding (VBB) to help marketers achieve their business objectives.

Predictive AI takes into account billions of signals, including location, time of day, device, and past behaviors, to predict how likely a user is to convert and how much they are likely to spend. This information is then used to set accurate bids based on the advertiser’s goals. For instance, Google Maps uses predictive AI to help users get to their destination faster, while Gmail uses smart compose to complete sentences based on how users type.

Value-based bidding (VBB) is a form of predictive AI that is aligned with a company’s business objectives. By passing on profit data, revenue data, or lifetime value data, VBB can adapt in real-time based on customer changes, business changes, or macro-environment changes. For example, a retailer with varying profit margins can use VBB to automatically place bids based on products with higher or lower margins, maximizing overall margin.

Making Science has used predictive AI to help a hotel chain predict cancellations based on signals like time of day, device, and channel. By using this information to tell Google which bookings are worth more, Google’s algorithm can bring in the right users who are less likely to cancel.

To maximize the benefits of predictive AI in marketing, experts recommend focusing on data quality over quantity, using your own data, and testing it. Real-time predictions are also crucial, as the digital world is all about real-time. By following these tips, any organization can use predictive AI in marketing to achieve their business objectives.

Case Study: Hotel Chain Bidding Strategy

Value-based bidding (VBB) is aligned with business objectives and it allows marketers to pass profit data, revenue data, or lifetime value data to optimize bids. This means that VBB can adapt in real-time based on customer changes, business changes, or macro environment changes, leading to maximized overall margin. For example, a retailer passing margin data to VBB can automatically place bids based on product categories with varying profit margins, increasing bids for high-margin products and decreasing bids for low-margin products.

Predictive AI, especially in VBB, is being used to improve performance marketing for businesses. For instance, a hotel chain was facing a high cancellation rate due to a new policy introduced by a third-party booking platform. Predictive AI was used to analyze signals such as time of day, device, and channel to predict whether users would cancel their bookings. This allowed the hotel chain to pass on information to Google and other platforms about which bookings were most valuable and likely to lead to a cancellation, enabling the algorithm to bring in users who were less likely to cancel.

To maximize the value of AI, try focusing on data quality and breaking data silos, as well as thinking in real-time. I suggest starting with your own data and testing it thoroughly before expanding, and using VBB to align bidding strategies with business objectives. Overall, AI can help marketers build a much-needed competitive advantage in bidding strategies.

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Maximizing AI Value in Bidding

According to a recent study, 75% of organizations have integrated AI into their business strategies, but only 12% are using it to gain a strong competitive advantage. AI is revolutionizing bidding strategies and helping marketers and their companies to build that much-needed competitive advantage.

Predictive AI is being used in bidding, specifically in value-based bidding (VBB), to optimize bids and align them with business objectives.

Predictive AI is able to incorporate billions of signals to predict how likely a user is to convert and how much they are likely to spend. In VBB, the main benefit for marketers is that it is aligned with their business objectives and can adapt in real-time based on customer changes, business changes, or macro-environment changes.

For example, a retailer with several different product categories and varying profit margins can pass margin data to VBB to optimize bids based on products with higher margins, lower margins, and somewhere in between. This means that VBB can maximize overall margin by placing bids on products with higher margins and lower bids on products with lower margins.

The platform called GA AI makes value-finding at scale easy by predicting and activating data into bidding platforms like Google Ads.

To maximize the value of AI in bidding, experts suggest focusing on doing things step by step, using good data instead of trying to have more data, and thinking about real-time. Using your own data and testing it is also important to optimize bids and align them with business objectives.

Overall, AI has the potential to revolutionize bidding strategies and help marketers and businesses build a competitive advantage by optimizing bids and aligning with business objectives.

Tips for Implementing AI in Bidding

Implementing AI in bidding algorithms can be a game-changer for companies looking to gain a competitive advantage. Here are some tips for marketers looking to maximize the value of AI in their bidding strategies:

• Focus on value-based bidding (VBB): VBB is aligned with business objectives, such as profit or revenue data, and can adapt in real-time based on customer changes or macro environment changes. This means that it can maximize overall margin by placing bids based on products with higher margins and lower margins, depending on the profit data passed to it.
• Use predictive AI: Predictive AI is able to take in and incorporate billions of signals to predict how likely each person is to convert and how much they are likely to spend. This allows marketers to set accurate bids based on their goals.
• Start small and improve: AI is for everyone, and it is becoming easier to use every day. Start by doing things step by step and focus on improving accuracy over time.
• Focus on data quality: It is better to have good data than a large quantity of data.
• Break down data silos: Make sure that your data is not siloed and can be used across different platforms and tools.
• Think real-time: Digital has been about real-time for many years, so focus on making things fast and try to go real-time.

By following these tips, marketers and businesses can maximize the value of AI in their bidding strategies and gain a big competitive edge in their industry.