Bid Shading: How to Stop Overpaying in First-Price Auctions

Imagine you are buying a house. You know you would pay up to $500,000. The seller does not know that. So you open at $420,000. That gap between what you would pay and what you actually offer is where the deal gets made.

Real-time bidding does not work that way. In a first-price auction, if you bid $8.00 CPM, you pay $8.00 CPM. Every time. There is no haggling. There is no opening offer. Whatever you submit is the price you pay when you win.

That single mechanic is why bid shading exists.

The thesis is simple: In first-price auctions, the advertiser who understands what the impression is actually worth wins more often at a lower cost than the advertiser who bids on instinct. Bid shading is how that understanding gets encoded into every bid you place.

This article covers what bid shading is, how the bid shading algorithm works step by step, who builds and applies it, when it makes sense to use it, and what it means for publishers on the other side of the auction.

What Is Bid Shading?

Before answering this question, we must tell you a bit about 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 seem convenient for advertisers, second-price auctions have received a lot of criticism for their lack of transparency. NB: In a second-price auction, the winning bidder pays just one cent more than the second-highest bid, while in a first-price auction, the winner pays exactly what they bid, which can lead to overspending.

The transition from second-price to first-price auctions in programmatic advertising began around 2017, with major exchanges adopting this model to enhance transparency and reduce operational complexity.

The development of header bidding technology led to the prevalence of first-price auctions across the most popular ad exchanges, including Google Ad Manager and many others.

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

In simpler terms, when bid shading explained, it makes first-price auctions nearly as cost-effective as second-price auctions, enabling advertisers to pay less than in a first-price auction but 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?

Collecting Data

The platform with the bid shading programmatic feature continuously collects data from the previous auctions. This may include floor prices, past bids (winning and losing), clearing prices, demographics, the types of devices customers use, the time of day, etc. Also, the system is interested in the 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 correlations to 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 based 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 only milliseconds while the customer loads the webpage, so the process described above also happens extremely quickly. If the adjusted bid wins, the advertiser pays this sum (smaller than their initial offer). And if the bid loses, the data is recorded in the system and affects the next iteration of the process.

Now that you understand how bid shading process 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 their 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 a stable cash flow.

Also, there are 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 more quickly and painlessly, avoiding losses.
• Considers fresh data that may influence the outcome of the current auction, plus factors like seasonal trends.
• With the use of machine learning, the bid shading algorithm continues to improve over time. The more auction data it analyzes, the stronger its predictive power gets.
• Adjusts the bid to maximize the chances of winning while minimizing the risk of overpaying. As a result, this technology improves cost efficiency.
• Media buyers who understand what bid shading is and how to configure it in their DSP consistently see lower average CPMs than those running first-price auctions without any bid adjustment logic in place.
• It may become a competitive advantage. It’s advantageous in saturated markets.
• Enables better campaign performance metrics, including ROI, for advertisers.
• Ideally, with time, the bid shading mechanism can help balance advertisers’ and publishers’ interests.

Based on Epom observations, advertisers who configure bid shading parameters in their DSP rather than relying on automatic defaults consistently see average CPMs on premium inventory 15 to 25% lower, without a measurable reduction in win rate.

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 in recent years, you are not obligated to use 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 market 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 on your own may look like guessing, with significant risks of overpaying 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.

Dynamic bidding strategies can be adjusted in real-time based on the competitive landscape of individual auctions.

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.

As an Epom DSP specialist puts it: “The biggest mistake buyers make with bid shading is treating it as a set-and-forget feature. The algorithm improves with auction data, but your bidding strategy still needs to define the trade-off between winning volume and controlling cost. The platform cannot make that strategic decision for you.”

The Most Common Bid Shading Methods

Estimation of the optimal price can be done using various 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 slightly higher than the median.

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 such as demographics, user 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?

Bid shading has raised concerns among publishers regarding potential revenue reductions, as it allows advertisers to bid lower than they might otherwise in a first-price auction.

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 their details.
• Platforms see their bid shading programmatic tools as a competitive advantage, so they are reluctant to give away details.
• Bid shading methods continue to evolve, 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 their bidding strategies, avoid overpaying, and achieve greater 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.

FAQs

• What is bid shading?

  Bid shading is a predictive algorithm that adjusts your bid downward in first-price programmatic auctions by estimating the minimum price needed to win the impression and submitting that amount instead of your maximum bid. It draws on historical auction data, floor prices, win rates, and machine learning to find the optimal price. The highest bidder pays the adjusted bid amount, not the original maximum bid.

• How does bid shading work?

  The platform continuously collects data from past auctions: floor prices, winning and losing bids, clearing prices, device types, and time of day. Machine learning algorithms analyze that data to identify patterns and estimate the true market value of each impression. The system then automatically submits a lower adjusted bid during the live auction, which runs in under 100 milliseconds.

• Who does bid shading?

  Most major DSPs include bid shading as a standard or optional feature, including Google DV360 and The Trade Desk. Some ad exchanges and SSPs, such as PubMatic, also offer a free bid shading tool. Standalone bid-shading algorithms are also available to advertisers who want independent optimization outside their DSP.

• When to use bid shading?

  Bid shading aims to be most useful when you are buying in a competitive first-price auction environment, dealing with premium inventory where overpaying is costly, or entering a new market where floor prices and clearing prices are unclear. If you are still buying via second-price auctions or operating in a small, stable market with predictable pricing, the benefit is more limited.

• How does bid shading impact publishers?

  Bid shading lowers the prices advertisers pay per impression, which can reduce publishers' revenue per impression. Publishers respond by dynamically adjusting floor prices to set a minimum acceptable clearing price and by monitoring bid-shading behavior across their inventory. Over time, most publishers and advertisers find an equilibrium between bid efficiency and fair pricing.

• Is bid shading transparent?

  Not fully. Most DSPs and ad exchanges treat their bid shading algorithms as proprietary and do not disclose the exact logic. Some platforms offer partial visibility into how bids are adjusted and allow advertisers to customize parameters. Blockchain and AI-based transparency tools are in development but have not yet reached widespread adoption.