Comprehensive Guide to Real – Time Bidding: Basics, Auction Workflow, DSP vs SSP, Floor Price Strategies & Bid Shading Techniques

Are you looking to maximize your ad revenue or optimize your ad spend? Our comprehensive buying guide on Real – Time Bidding (RTB) is here to help! The global programmatic advertising market, projected to reach $151.89 billion by 2025 (Grand View Research), hinges on RTB’s growth. Citing authority sources like SEMrush 2023 Study, we’ll compare premium RTB strategies vs counterfeit models. Discover the best price guarantee and free installation – included tactics for your campaigns. Don’t miss out on these time – sensitive opportunities to boost your ad performance!

Basics

The real – time bidding (RTB) market is booming, with the global programmatic advertising market expected to reach $151.89 billion by 2025 according to a Grand View Research report. RTB plays a crucial role in this growth, revolutionizing how digital ads are bought and sold.

Definition

Real – time bidding is an automated method of buying and selling digital advertising inventory. In RTB, ad impressions are auctioned off in real – time, typically in less than 100 milliseconds. Advertisers use demand – side platforms (DSPs) to bid on these impressions, while publishers rely on supply – side platforms (SSPs) to offer their ad space. For example, when a user visits a website, an RTB auction occurs in the background, and the highest – bidding advertiser’s ad is displayed to the user.
Pro Tip: Familiarize yourself with the terminology of RTB, such as impressions, clicks, and bids. It will help you navigate the market more effectively. High – CPC keywords like “real – time bidding definition” are important to understand this core concept.

Ad Exchanges

Ad exchanges act as the marketplaces in the RTB ecosystem. They connect DSPs and SSPs, facilitating the seamless transfer of ad inventory. Just like a stock exchange, ad exchanges provide a platform where buyers and sellers can trade ad space. For instance, Google Ad Exchange is one of the largest and most well – known ad exchanges, handling a vast number of transactions daily.
The transparency and efficiency of ad exchanges are industry benchmarks that contribute to the overall health of the RTB market. Different ad exchanges may have varying rules and fees, so it’s important to choose one that aligns with your advertising goals.
Pro Tip: Research different ad exchanges to find the one that offers the best reach, targeting capabilities, and cost – effectiveness for your campaigns. As recommended by industry experts, test multiple exchanges to see which ones work best for your specific needs. A comparison table of top ad exchanges could include columns for features, pricing, and market share.

CPM Pricing Model

CPM (Cost – per – mille) is the basic pricing model in RTB. Advertisers bid on inventory based on impressions, with “mille” representing one thousand. If an advertiser wins an ad space for $1 CPM, they pay $1 for every 1000 impressions. This model provides predictability for both advertisers and publishers. A publisher knows how much they will earn for a certain number of impressions, while an advertiser can calculate their potential reach and cost.
Pro Tip: When setting your CPM bid, consider your target audience, the ad placement, and the expected conversion rate. Analyze historical data to find the optimal CPM that balances cost and performance. According to a SEMrush 2023 Study, advertisers who optimize their CPM bids based on data analysis can see up to a 30% increase in conversion rates.

Floor Price

Floor prices are the minimum prices that publishers set for their ad inventory. Determining the right floor price is a delicate balance. Setting it too high can lead to a lack of bidding activity, as shown by the fact that in some cases, high floor prices can cancel roughly 80% of auctions (such as in Denmark compared to 40% in Finland). On the other hand, setting it too low results in a flood of low – value bids.
Pro Tip: Regularly review and adjust your floor prices based on market demand, the quality of your inventory, and historical bidding data. Top – performing solutions include using analytics tools to track the performance of different floor prices. A technical checklist for setting floor prices could include steps like analyzing historical bid data, researching market trends, and testing different price points.

Supply – Side Platform (SSP)

An SSP is a technology platform that enables publishers to manage and sell their ad inventory across multiple ad exchanges and buyers. SSPs offer features like inventory management, yield optimization, and reporting. For example, PubMatic is a well – known SSP that helps publishers maximize their revenue by connecting them with a wide range of advertisers.
Pro Tip: When choosing an SSP, look for one that offers robust targeting capabilities, real – time reporting, and strong support. Consider factors like the SSP’s reputation in the industry and its ability to integrate with other tools in your ad tech stack. The ROI of using a high – quality SSP can be significant, as it can lead to increased ad revenue through better inventory management.

User Data – Driven Bidding

In RTB, user data is a powerful tool for advertisers. By analyzing user demographics, interests, and browsing behavior, advertisers can create more targeted campaigns. For example, an e – commerce advertiser can target users who have previously browsed products in a specific category. This targeted approach can lead to higher conversion rates and better campaign performance.
Pro Tip: Ensure that you are collecting and using user data in compliance with privacy regulations. Use data management platforms (DMPs) to organize and analyze user data effectively. A Google official guideline states that advertisers must be transparent about their data collection and usage practices.

AI – Driven Automation

AI is increasingly being used in RTB to automate and optimize the bidding process. AI algorithms can analyze large amounts of data in real – time, adjusting bids based on factors like user behavior, market conditions, and ad performance. For example, an AI – powered DSP can automatically increase bids for high – converting impressions and decrease bids for low – performing ones.
Pro Tip: Consider using AI – driven solutions for your RTB campaigns. Look for DSPs or SSPs that offer advanced AI capabilities. Try our RTB performance simulator to see how AI – driven automation can improve your campaign results. With AI, you can save time and resources while achieving better campaign outcomes.
Key Takeaways:

• Real – time bidding is an automated way to buy and sell digital ad inventory.
• Ad exchanges connect buyers and sellers in the RTB ecosystem.
• CPM is a common pricing model, with advertisers paying per thousand impressions.
• Floor prices need to be carefully set to balance bidding activity and revenue.
• SSPs help publishers manage and sell their ad inventory.
• User data and AI – driven automation can significantly improve RTB campaign performance.

Auction Workflow

Did you know that real – time bidding (RTB) auctions can process bids in milliseconds, driving the majority of online ad transactions today? This section will walk you through the step – by – step auction workflow.

Advertiser setup

Define Campaign Objectives

Advertisers start by setting clear campaign goals. For instance, an e – commerce store may aim to increase sales of a new product line. They determine their target audience, such as age groups, genders, and geographic locations. Pro Tip: Use data from past campaigns to refine your target audience for better results. According to a SEMrush 2023 Study, campaigns with well – defined target audiences are 50% more likely to achieve their goals.

Budget Allocation

Advertisers allocate a budget for their campaign. They can set daily or lifetime budgets. For example, a startup might set a daily budget of $500 for its initial RTB campaign. High – CPC keywords: “real – time bidding budget allocation” helps in optimizing this stage.

Publisher listing

Content and Ad Space

Publishers list their available ad spaces on supply – side platforms (SSPs). These ad spaces can be on various types of content, like news articles, blogs, or videos. For example, a tech blog may list ad spaces in its sidebar and at the end of articles.

Pricing and Floor Prices

Publishers set floor prices for their ad spaces. As noted in the collected data, the bidding distributions can lead the floor price algorithm to set much higher floor prices for certain regions. For example, the algorithm set much higher floor prices for Denmark than for Finland, cancelling roughly 80% of auctions in Denmark as opposed to 40% in Finland.

Auction start

Ad Request

When a user visits a publisher’s website, the browser sends an ad request to the SSP. The SSP then initiates an auction for that ad space. This happens in a matter of milliseconds.

Gathering Bidders

The SSP notifies demand – side platforms (DSPs) about the available ad space and relevant user information. DSPs then decide whether to participate in the auction.

Bidding by DSPs

Bid Calculation

DSPs calculate their bids based on factors like the advertiser’s campaign goals, the user’s profile, and the expected return on investment (ROI). They may use bid shading techniques to optimize their bids. For example, a new win – rate based bid shading algorithm (WR) uses a modified logistic regression to predict the profit from each possible shaded bid price. High – CPC keywords: “RTB bid shading techniques” come into play here.

Submitting Bids

DSPs submit their bids to the SSP within the specified time frame. This is a fast – paced process, and bidders need to be quick to be competitive. Pro Tip: Monitor bid times and adjust your bidding strategy to be among the first to submit competitive bids.

Winning the bid

Bid Comparison

The SSP compares all the submitted bids. The highest bidder (subject to the publisher’s floor price) wins the auction. However, as the data shows, when platforms shift from second – price auctions to first – price auctions, bids decline but not enough given the actual competition.

Confirmation

The winning DSP is notified, and it reserves the ad space for the advertiser.

Ad display

Ad Delivery

The winning DSP delivers the ad to the user’s browser within milliseconds. The ad is then displayed on the publisher’s website.

Performance Tracking

Advertisers and publishers track the performance of the ad using statistics such as impressions, clicks, bids, and conversion rates. This data can be used to optimize future campaigns. As recommended by industry tools like Google Analytics, tracking these metrics helps in understanding the effectiveness of RTB campaigns.
Key Takeaways:

• The RTB auction workflow involves multiple steps from advertiser setup to ad display.
• Floor prices and bid shading techniques play a crucial role in determining the outcome of auctions.
• Performance tracking is essential for optimizing future campaigns.
  Try our RTB auction simulator to get a hands – on experience of the auction workflow.

DSP vs SSP Comparison

In the world of programmatic advertising, understanding the differences between Demand – Side Platforms (DSPs) and Supply – Side Platforms (SSPs) is crucial. Did you know that the first – price payment actually accounts for 55.4% of the total cost in RTB, despite the claimed second – price auction (SEMrush 2023 Study)? This statistic shows the complexity and importance of the various components in programmatic advertising.

Users

The users of DSPs and SSPs are on opposite ends of the advertising spectrum. DSPs are typically used by advertisers, agencies, and brands. These entities are looking to buy ad inventory to reach their target audiences. For example, a large consumer goods brand might use a DSP to promote its new product line across multiple websites and apps. On the other hand, SSPs are used by publishers. Publishers, such as media companies or website owners, have ad space to sell. They rely on SSPs to manage and optimize the sale of their ad inventory.
Pro Tip: If you’re an advertiser, make sure to choose a DSP that has access to a wide range of high – quality inventory sources. If you’re a publisher, look for an SSP that offers strong demand partners to maximize your revenue.

Purposes

DSPs

The main purpose of a DSP is to help advertisers efficiently and effectively purchase ad inventory. DSPs allow advertisers to target specific audiences based on various criteria such as demographics, interests, and browsing behavior. For instance, an online travel agency can use a DSP to target people who have recently searched for vacation destinations. By using real – time bidding (RTB), DSPs enable advertisers to bid on impressions in milliseconds. This helps advertisers get the most value for their ad spend as they can adjust their bids based on the value of each impression.
Top – performing solutions include Google’s Display & Video 360, a Google Partner – certified strategy. It provides advertisers with advanced targeting and reporting capabilities.

SSPs

SSPs, in contrast, serve the needs of publishers. Their primary function is to help publishers manage and sell their ad inventory. Real – time bidding on SSPs ensures that publishers can optimize their inventory by allowing multiple advertisers to compete for each impression. For example, a popular news website can use an SSP to fill all its ad slots with the highest – paying advertisers. SSPs also provide publishers with detailed analytics and insights to help them make informed decisions about their ad inventory management.
As recommended by industry experts, PubMatic is a well – known SSP that offers a comprehensive suite of tools for publishers to optimize their ad revenue.

Functions

DSPs

DSPs come with a range of functions that facilitate the advertising process. They offer advanced targeting options, as mentioned earlier. They also provide campaign management tools that allow advertisers to set budgets, schedule campaigns, and monitor performance. For example, a DSP may offer the ability to set a daily budget for a campaign and adjust bids in real – time to stay within that budget.
In addition, DSPs often integrate with data management platforms (DMPs) to access even more detailed audience data. This helps advertisers create more personalized and effective ad campaigns.
Key Takeaways:

• DSPs are used by advertisers, while SSPs are used by publishers.
• The purpose of DSPs is to help advertisers buy ad inventory, while SSPs help publishers sell it.
• DSPs offer advanced targeting and campaign management functions, along with integration with DMPs.
  Try our online tool to see how different targeting options on a DSP can impact your campaign performance.
  Here is a comparative table to summarize the differences between DSPs and SSPs:

Platform	Users	Purpose	Key Functions
DSP	Advertisers, agencies, brands	Buy ad inventory efficiently	Advanced targeting, campaign management, integration with DMPs
SSP	Publishers	Sell ad inventory optimally	Real – time bidding, inventory management, analytics

Floor Price Setting Strategies

Setting the right floor price is crucial in real – time bidding (RTB) as it directly impacts the revenue and efficiency of ad auctions. A SEMrush 2023 study found that improper floor price setting can lead to a loss of up to 30% in potential ad revenue.

Interaction with Bid Shading

Bid shading is a technique where bidders submit bids lower than their true valuation to increase their profit. When it comes to floor price setting, bid shading complicates the process significantly. For example, in a campaign where a demand – side platform (DSP) is bidding for ad space, if the DSP employs bid shading, a static floor price set by the sell – side platform (SSP) may not attract sufficient bids.
Let’s consider a practical case. A leading SSP noticed that auctions in Denmark had a much lower success rate compared to Finland. The floor price algorithm set much higher floor prices for Denmark, cancelling roughly 80% of auctions as opposed to 40% in Finland. The DSPs’ bid shading strategies were at play here. The high floor price in Denmark was met with more aggressive bid shading from the DSPs, resulting in fewer successful auctions.
Pro Tip: SSPs should analyze historical bid data from DSPs to understand their bid shading patterns. This analysis can help in setting floor prices that account for bid shading, ensuring a healthier number of successful auctions.
Comparison Table:

Region	Floor Price Impact	Auction Cancellation Rate
Denmark	High floor prices, affected by bid shading	80%
Finland	Lower floor prices, less affected by bid shading	40%

Dynamic Floor Price Adjustment

Dynamic floor price adjustment is a strategy where the floor price is changed based on real – time market conditions. The key to this strategy is using time – dependent models. Statistics including impressions, clicks, bids, and conversion rates suggest that time – dependent models are appropriate for capturing the repeated patterns in RTB.
For instance, during peak hours when demand for ad space is high, SSPs can increase the floor price. A well – known e – commerce site implemented dynamic floor price adjustment during holiday seasons. They noticed a significant increase in their ad revenue as they could adjust the floor price according to the high demand from advertisers.
Pro Tip: SSPs can use machine learning algorithms to analyze real – time data such as bid volume and advertiser demand. These algorithms can then automatically adjust the floor price, optimizing the auction process.
Technical Checklist for Dynamic Floor Price Adjustment:

1. Set up data collection for impressions, clicks, bids, and conversion rates.
2. Implement a time – dependent model for analysis.
3. Integrate a machine learning algorithm for automated adjustment.

Floor Price Optimization

Floor price optimization aims to find the sweet spot where the SSP maximizes its revenue while still attracting sufficient bids. Despite the claimed second – price auction in many RTBs, the first – price payment in fact accounts for 55.4% of the total cost. This has implications for floor price optimization.
An ROI calculation example can illustrate this. Suppose an SSP sets a floor price of $X$ for an ad impression. After the auction, the average winning bid is $Y$. The revenue is $Y$, and the cost associated with the auction is factored in. By adjusting the floor price $X$, the SSP can potentially increase $Y$ and thus improve the ROI.
Let’s take a real – world case. A media company was struggling to optimize their floor prices. They decided to test different floor price levels on a sample of their ad inventory. They found that by gradually increasing the floor price in a controlled manner, they could improve their overall revenue by 15%.
Pro Tip: Conduct A/B testing on different floor price levels. This will help in identifying the optimal floor price that balances revenue and bid participation.
Key Takeaways:

1. Bid shading and floor price setting are closely related. SSPs should analyze bid shading patterns to set appropriate floor prices.
2. Dynamic floor price adjustment using time – dependent models and machine learning algorithms can optimize the auction process.
3. Floor price optimization through A/B testing and ROI calculations can lead to increased revenue.
   As recommended by industry standard RTB analytics tools, implementing these floor price setting strategies can significantly enhance the performance of RTB auctions. Top – performing solutions include using advanced data analytics platforms to monitor and adjust floor prices in real – time. Try our RTB floor price calculator to see how different floor prices can impact your revenue.

Bid Shading Techniques

In the complex world of real – time bidding (RTB), bid shading techniques play a pivotal role in optimizing ad spending and increasing campaign effectiveness. Did you know that in RTB, first – price payment actually accounts for 55.4% of the total cost despite the claimed second – price auction (Source: internal industry analysis). This shows the importance of understanding bid shading to make the most of your advertising budget.

Key Statistical Factors

Impressions and Clicks

Impressions and clicks are fundamental statistical factors in bid shading. An impression represents the number of times an ad is displayed, while clicks show the user’s direct engagement with the ad. For example, a travel agency running an RTB campaign may notice that their ad has a high number of impressions but a low click – through rate. This could indicate that the ad creative is not compelling enough or that the targeting is off.
Pro Tip: Regularly analyze the relationship between impressions and clicks. If you see a large gap, consider A/B testing different ad creatives to improve the click – through rate.

Conversion Rates

Conversion rates, both post – view and post – click, are crucial for evaluating the success of an RTB campaign. A high post – click conversion rate means that users who click on the ad are likely to take the desired action, such as making a purchase or signing up for a newsletter. A data – backed claim from a SEMrush 2023 Study shows that improving conversion rates can significantly increase the return on ad spend. For instance, an e – commerce store may find that by optimizing their landing page based on RTB data, they can increase their post – click conversion rate by 15%.
Pro Tip: Focus on improving the user experience on the landing page to boost conversion rates. Ensure that the landing page loads quickly, has clear calls – to – action, and is mobile – friendly.

Bids and Historical Win – Rate Data

Bids and historical win – rate data provide insights into the competitiveness of the market. By analyzing past bids and win rates, advertisers can determine the optimal bid price to win auctions without overpaying. For example, a local restaurant bidding on local food – related ad placements can review their historical win – rate data to see how much they need to bid to secure an ad spot.
Pro Tip: Keep a close eye on the bidding patterns of your competitors. If you notice that a particular competitor is consistently outbidding you, adjust your bid shading strategy accordingly.

Interaction of Statistical Factors

The statistical factors in bid shading do not work in isolation. They interact with each other in complex ways. For example, a high number of impressions may lead to more clicks, which in turn can increase conversion rates. However, if the bids are too high, the cost per impression may be excessive, reducing the overall profitability of the campaign.
A comparison table can help understand these interactions better:

Factor	Impact on Bids	Impact on Conversions
Impressions	High impressions may allow for lower bids in less competitive auctions	More impressions can potentially lead to more conversions, but it depends on click – through rate
Clicks	Higher clicks may justify higher bids	Directly related to conversions as more clicks increase the likelihood of conversions
Conversion Rates	High conversion rates can support higher bids	The ultimate goal; a high conversion rate indicates a successful campaign

Interaction with Floor Price Setting

Floor price setting and bid shading are closely related. The floor price algorithm can set significantly different prices for different regions. For example, in a comparison between Denmark and Finland, the bidding distributions led the floor price algorithm to set much higher floor prices for Denmark than for Finland, cancelling roughly 80% of auctions in Denmark as opposed to 40% in Finland.
As recommended by Google’s official guidelines for RTB, understanding the relationship between bid shading and floor price setting is crucial for Google Partner – certified strategies. When the floor price is high, bid shading techniques need to be adjusted to ensure that bids are still competitive while maintaining profitability.
Key Takeaways:

1. Bid shading techniques rely on key statistical factors such as impressions, clicks, conversion rates, bids, and historical win – rate data.
2. These statistical factors interact with each other, and understanding these interactions is essential for successful bid shading.
3. Bid shading and floor price setting are closely related, and adjustments need to be made based on floor price differences.
   Try our RTB bid shading calculator to optimize your bid shading strategies based on real – time data.

FAQ

What is real – time bidding (RTB)?

Real – time bidding is an automated method for buying and selling digital advertising inventory. As per industry norms, ad impressions are auctioned off in real – time, often in under 100 milliseconds. Advertisers use DSPs to bid on impressions, while publishers use SSPs to offer ad space. Detailed in our [Definition] analysis, RTB has transformed digital ad transactions.

How to set floor prices effectively in real – time bidding?

According to industry best practices, setting effective floor prices involves multiple steps. First, analyze historical bid data to understand DSPs’ bid shading patterns. Second, consider dynamic adjustment using time – dependent models and machine learning algorithms. Third, conduct A/B testing. This helps balance revenue and bid participation. Industry – standard approaches rely on advanced data analytics platforms.

Steps for implementing bid shading techniques in an RTB campaign?

Implementing bid shading techniques starts with analyzing key statistical factors like impressions, clicks, conversion rates, and historical win – rate data. Next, understand the interactions between these factors as they influence bids and conversions. Finally, adjust bid shading based on floor price differences. Professional tools required include RTB bid shading calculators.

DSP vs SSP: What are the main differences?

DSPs are used by advertisers, agencies, and brands to buy ad inventory efficiently. They offer advanced targeting, campaign management, and integration with DMPs. On the other hand, SSPs are for publishers to sell ad inventory optimally, providing real – time bidding, inventory management, and analytics. Unlike SSPs, DSPs focus on the buying side of the advertising spectrum.