Bid Shading Alchemy: Turning Your Cost Management Strategy into Gold

Programmatic advertising offers numerous opportunities for buyers to get the most value for their money. Still, to reach the best results of your digital ad campaigns, you need to catch the underlying principles and technologies. A key one is bid shading, the predictive algorithm that allows buyers to optimize their bids on ad inventory.

In this article, we’ll discuss how the market has switched mainly to first-price auctions (and explain what’s that) and why it became so crucial for advertisers to modify their cost management approaches. We’ll delve into the bid shading process, its pros and cons and finally, understand its meaning for sellers and buyers.

What Is Bid Shading?

Before answering this question, we must tell you a bit of a first-price auction. As you know, programmatic advertising relies on auctions in which advertisers bid on ad inventory, and the winner gets to show their ad to the customer. In a first-price auction, the winner must pay precisely the sum they bid.

At the same time, in a second-price auction, the winning bid is reduced to just above the second-highest bid (usually by one cent). As a result, the winner often pays less than they bid. Although this model may look convenient for advertisers, second-price auctions received a lot of criticism for the lack of transparency.

Combined with the development of header bidding technology, it led to the prevalence of first-price auctions in the most popular ad exchanges, such as Google Ad Manager and many others.

With first-price auctions as the industry standard, advertisers must change their bidding strategies to optimize their expenses and avoid overpaying. And here, bid shading appears to save them!

In simpler terms, bid shading makes first-price auctions nearly as cost-effective as second-price auctions, enabling advertisers to pay less than they would in a first-price auction but just slightly more than in a second-price auction.

Where does "the price estimation" come from, you may ask? The algorithm analyses various data, such as market size, historical data (past bids), winning rates, etc., and forms an estimated bid.

The primary goal of using this feature is to balance placing the winning bid and optimizing the budget. Now, let’s dive into the specifics of how the bid shading technology works.

How Does Bid Shading Work?

We’ve understood that this technology helps advertisers overcome the challenges of first-price auctions. The bid shading algorithm typically relies on several mechanisms to deliver on this promise.

Collecting Data

The platform with the bid shading programmatic feature continuously collects data from the previous auctions. This may include floor prices, different past bids (winning and losing), clearing prices, demographics, types of devices customers use, time of the day, etc. Also, the system is interested in margins by which bids were winning or losing in the past auctions.

Analyzing Data

All this information is then analyzed via machine learning algorithms. The goal is to identify patterns and find correlations that help estimate the optimal bid. For instance, the bid shading algorithm may discover the correlation between the day of the week and the clearing price. So, collected data becomes the basis for understanding the real-life market value of the ad inventory.

Bidding

The system automatically adjusts the original bid after calculating the “true” market price. Some platforms allow advertisers to influence this decision by customizing bid shading parameters depending on marketing goals or risk appetite. For example, some advertisers prefer to win and pay more, while others prioritize budget saving. In any case, the bid shading algorithm aims to find the optimal price.

The programmatic auction usually lasts milliseconds while the customer loads the webpage, so the process explained above also happens extremely fast. If the adjusted bid wins, the advertiser pays this sum (smaller than their initial offer). And if the bid loses, the data goes to the system and affects the next iteration of the process.

Now that you understand how bid shading works, it’s time to uncover where exactly it happens.

Who Does Bid Shading?

There’s no single answer to this question because today several parts can play its role in the process:

• Demand-side platforms (DSPs). To help advertisers implement the most efficient strategies, many DSPs create bid shading programmatic tools and offer them free or charge an extra fee (examples include Google’s DV360, The Trade Desk, and others).
• Ad exchanges. Some ad exchanges launched bid shading options to help advertisers transition from second-price to first-price auctions.
• Supply-side platforms (SSPs). Although it may seem counterintuitive, some SSPs, such as PubMatic, also provide bid shading. Sure, it looks like there’s a risk of reducing the publishers’ revenue due to lower winning prices. But, at the same time, without buyers, publishers can’t get any profit at all. Allowing bidding optimization attracts advertisers and ensures stable cash flow.

Also, there are some specialized standalone bid shading algorithms that advertisers can buy and use if they best suit their needs.

Benefits and Challenges of Bid Shading

There’s no perfect technology in the world, so exploring the advantages and disadvantages of any tech stuff always makes sense. Let’s discuss the strong sides of bid shading first:

• It helps buyers adapt to first-price auctions faster and painlessly, avoiding losing money.
• Considers fresh data that may influence the outcome of the current auction plus factors like seasonal trends.
• Due to the usage of machine learning, the bid shading algorithm keeps improving over time. The more auction data it analyzes, the stronger its predictive power gets.
• Adjusts the bid to maximize chances for winning and, at the same time, minimize risks of overpaying. As a result, this technology improves cost efficiency.
• It may become a competitive advantage. It’s advantageous in saturated markets.
• Allows achieving better campaign performance metrics, including ROI for advertisers.
• Ideally, with time, the bid shading mechanism can help balance advertisers’ and publishers’ interests.

Sounds impressive, but still, there are some challenges associated with this technology:

• Risks of losing the auction. If done incorrectly, the bid shading algorithm may estimate the price too low. As a result, you underbid and lose impressions you’ve wanted to buy.
• Transparency issues. Not every platform discloses the information about the bid shading algorithm it uses to all the parties involved. So, the question of fair prices remains open. In turn, the lack of transparency may lead to distrust.
• Prediction inaccuracy. Many algorithms rely predominantly on historical data, which may not always be correct. After all, the past doesn’t necessarily predict the future, especially if the market is turbulent.

In summary, bid shading is valuable in transitioning from second-price to first-price auctions. Nevertheless, the long-term consequences of its implementation remain unclear. This technology will likely continue to develop, gradually addressing issues. Or it will be replaced with something more advanced in the future.

When to Use Bid Shading?

Although this technology has become widespread over the past few years, you are not obligated to utilize it. Some advertisers prefer other bidding optimization methods, such as tailored bidding strategies. However, the final choice of a particular method depends on your circumstances.

For instance, if your company operates in a transparent and not very dynamic market, you may not need bid shading because you can identify optimal bids by yourself. Also, if you still can use second-price auctions, there’s no need to turn to the bid shading algorithm.

At the same time, this technology may come in handy in many other situations. Here are some of them:

• Your media buying platform is transitioning from the familiar second-price to the new first-price auction environment. In this case, bid shading may help buyers adjust their strategies to changing circumstances.
• The risk of overpaying for you is much higher than average. For example, you’re dealing with premium ad inventory.
• Your marker is very competitive, so you need help optimizing your bids. Otherwise, you’ll lose valuable impressions.
• Market prices aren’t clear. In this case, bidding by yourself may look like guessing, with significant risks of over- or underpaying.
• You’re going through a learning cycle. For instance, you’ve recently entered a new market and started dealing with new types of ad inventory.

Before deciding on using bid shading, it’s reasonable to consider your advertising goals, your market, and the functionality of your DSP and other platforms you work with. After that, you can define this technology’s part in your strategy.

The Most Common Bid Shading Methods

Estimation of the optimal price may be created by using different techniques. Here are some standard methods.

Median Method

It’s pretty straightforward and based on calculating the median value of the previous winning bids for similar ad inventory. The adjusted bid will be just a bit higher than the median value.

Although this method is simple, it has some limitations. For instance, it doesn’t work well in rapidly changing markets.

Historical Data Method

We’ve already touched on it briefly because it’s one of the most common bid shading methods. Typically, it includes collecting and analyzing a wide array of data, such as clearing prices, seasonal trends, device types, ad formats, and time. As a result, the algorithm predicts the optimal bid.

Machine Learning Algorithms

They make it possible to analyze enormous amounts of data and predict bid prices in real-time. This method also considers essential factors, like demographics, users’ behavior, and performance metrics.

Machine learning is often combined with the historical data method. In this case, historical data provides initial information, and machine learning algorithms improve their predictions gradually, taking into account real-time data.

Also, some platforms use other bid shading methods, such as percentage reduction, based on reducing the original bid by some percentage (it may vary for different types of ad inventory and other factors). Moreover, combining several methods is quite popular, too. It often allows for more precise estimations and helps advertisers win auctions more frequently.

How Does Bid Shading Impact Publishers?

Initially, introducing this technology to the market has raised concerns among publishers. That’s only logical: if advanced algorithms help advertisers constantly bid lower, it may reduce revenues.

Next, shading requires publishers to adjust to new realities and review their strategies, which means investing extra time and effort.

On the other hand, publishers aren’t helpless. For instance, they can implement dynamic floor pricing models to address risks associated with bid shading or increase floor prices to fight low bids.

Every new technology brings some difficulties and challenges in the beginning. In the case of bid shading, both advertisers and publishers were affected. Still, with time, each party has learned to deal with new challenges. Some experts believe that even though bid shading programmatic tools impacted publishers’ revenue initially, it will help the market reach the balance in a longer perspective.

Is Bid Shading Transparent?

The short answer to this question is “not entirely,” and here are some reasons:

• Ad exchanges and DSPs often use proprietary algorithms and don’t disclose information about them.
• Platforms see their bid shading programmatic tools as a competitive advantage, so they are reluctant to give away details.
• Bid shading methods keep developing, making it difficult and time-consuming to disclose all the information.

However, some platforms explain to buyers how bids are adjusted and provide a dash of control over the process. Also, some market players work on advanced methods to increase transparency, such as blockchain and AI-based solutions. So, there’s a chance that buyers and publishers will soon get more much-needed transparency.

Conclusion

By now, you already understand the meaning of bid shading, its benefits and challenges, and the most common methods.

With first-price auctions becoming an industry standard, bid shading is turning into an essential part of the programmatic advertising world. It allows advertisers to optimize the bidding strategy, avoid overpaying, and achieve higher cost-efficiency.

Sure, some challenges still need to be addressed, including the transparency issue. In the future, we’ll likely witness significant changes and improvements in this technology. Hopefully, the market will eventually reach an equilibrium between advertisers’ efficient bidding and publishers’ fair revenues.

FAQ

• What is bid shading?
  Bid shading is the predictive algorithm that allows buyers to optimize their bids on ad inventory. It allows advertisers to pay less than they would pay in a first-price auction but just a bit more than in a second-price auction.
• How does bid shading work?
  The platform with the bid shading feature continuously collects data from the previous auctions. All this information becomes the subject of a detailed analysis using machine learning algorithms. Then, the system automatically adjusts the original bid.
• Who does bid shading?
  Today, this process can be performed by DSPs, ad exchanges, or even some SSPs. Also, there are specialized standalone bid shading algorithms that advertisers can use if they best suit their needs.
• When to use bid shading?
  This technology may come in handy in many other situations. For example, if the risk of overpaying for you is much higher than average (say, you’re dealing with premium ad inventory) or your market is very competitive, thus, you need help optimizing your bids.
• How does bid shading impact publishers?
  Bid shading requires publishers to adjust to new realities and review their strategies, which means investing extra time and effort. For instance, they can implement dynamic floor pricing models to address risks associated with bid shading or increase floor prices to fight low bids.
• Is bid shading transparent?
  Not entirely: ad exchanges and DSPs often use proprietary algorithms and don’t disclose information about them. However, some platforms explain to buyers how bids are adjusted and provide a dash of control over the process. Also, some market players work on advanced methods to increase transparency, such as blockchain and AI-based solutions.