Bid Shading - Is Price Floor A Lost Game for The Publishers?

Cognitiv created a stir in the market with its research on Bid Shading - $6.6 Million left on the table by the advertisers. Claiming it to be a blunt and unsophisticated tool, the research revealed -

“A third of Digital Media Buyers do not even know that bid shading exists, with only 35 percent of Digital Media Buyers “extremely confident” in their understanding of how a bid shading algorithm works and that they could explain it to others. Yet, 70 percent are paying an extra fee for this tool that they do not fully understand, blindly trusting that it is saving them money.”

There exists a critical gap in understanding and leveraging programmatic advertising technologies, where both potential gains and overlooked opportunities coexist. It’s a landscape full of technologies of the past and modern innovation. The point is, are you able to find and leverage the perfect solution for you?

Today, we will be diving into the buy-side pricing mechanism to find out the best counterparts for you. And while doing so we will also try to understand a few concepts belonging to the other side of the market.

Bid Shading - A Game Changer or Challenger

Bid shading is the algorithm-based solution with which DSP (and some of the SSPs) set the average bid for each impression, thus saving advertisers from overspending. It helps advertisers win impressions on ad space at the lowest possible price while still achieving their campaign goals.

Bid shading evolved out of necessity when the “second-price auction” transitioned to the “first-price auction”. 

Second-Price Auction

Also called the Vickery auction, the mechanism works backward. Advertisers will bid whatever they think the ad inventory is worth. However, the winner will have to pay just $0.01 extra to the second highest bid.
Suppose there are four qualified bidders in an auction. Bidder A bids $4, B bids $5, C bids $2, and D bids $8. The winner here, of course, will be bidder “D,”. But now he will be paying $5.01 for the same inventory instead of his initial bid of $8. 

Drawback for publisher -

Although the second-price auction created a competitive environment for the publishers, it also created the probability of money being left on the table. The second-highest bid might not be the correct market value of their inventory. 

First-Price Auction

A sealed-bid auction, the bidders here submit their bids, and the highest bidder wins and pays their exact bid amount.

So, if we consider the same example shared above, here, the winning bidder will be Bid “D” and the amount to be paid will be $8. Smells overpaying, isn’t it?

This change demands more strategic bidding from advertisers, as they risk paying their full bid amount. 

Drawback for publisher -

The direct correlation between bid and payment can lead to higher revenues per impression, assuming advertisers are willing to bid aggressively to secure premium ad spaces. 

However, the transition also requires publishers to more accurately price their inventory more accurately, as overpricing can deter bidders while underpricing can lead to revenue loss. The increased revenue potential comes with the need for greater market insight and pricing strategy refinement.

How Bid Shading Works

Bid shading works on algorithms. It analyzes a vast array of data points, including historical bidding data, the specific characteristics of the ad inventory, and real-time bidding dynamics. With this, the algorithms calculate a bid that is strategically lower than what the advertiser would be willing to pay in a maximum bid scenario but still competitive enough to win the auction. 

The "shaded" bid, therefore, represents a compromise between the outright aggression of a first-price auction bid and the bargain-seeking nature of a second-price auction bid.

Introduced by DSPs and some SSPs, bid shading emerged as advertisers' response to first-price auctions. The goal is to find the sweet spot where the bid is still high enough to win the impression most of the time but low enough to avoid overpaying significantly. And the platforms will take their share out of the amount saved per campaign. 

Challenges for Publishers -

• Revenue dilution: The primary concern for publishers revolves around the potential decrease in ad inventory prices. Since bid shading systematically aims to lower the bid price, the average selling price often drops, leading to diminished ad revenue.

• Market power dynamics: The technology and data analytics prowess behind bid shading are predominantly in the hands of a few dominant advertising platforms and networks. This concentration of power skews the market dynamics, leaving publishers with less leverage and forcing them to accept lower prices for their inventory.

• Hidden costs: Some forms of shading involve manipulating factors like viewability metrics, making it hard for publishers to assess the true value of their inventory and potential revenue loss.

• Technological disparity: Understanding and responding to sophisticated shading strategies require significant technical expertise and resources, which may not be readily available to all publishers.

• Fragmented landscape: The use of multiple ad exchanges and SSPs with different shading practices further complicates pricing transparency and revenue optimization for publishers.

Bid Shading Vs. Price Floor

Setting up the price floors has been the go-to response of publishers for every googly bowled by the supply side. It’s the minimum price the publisher is willing to accept for the inventory.

The question is how do you optimize and use the correct floor price mechanism to level the pricing game:

• Implement flexible, segment-based price floors. Set higher floors for premium inventory and adjust them dynamically based on real-time bidding data. This helps capture maximum value while accepting shaded bids on less valuable segments.
• Or go for advanced solutions like dynamic floor pricing. 
• Partner with transparent ad exchanges that reveal detailed bid information. This will allow you to understand the true value advertisers place on their inventory and set price floors accordingly, even if the final winning bid is shaded.
• Implement data analytics tools to analyze bidding patterns and uncover trends. By understanding how advertisers use shading across different segments, you can set strategic price floors to capture potential value even with lowered bids.
• Continuously monitor bidding data and adjust price floors to adapt to market trends and advertiser behavior.

However, at the same time, you will also need to keep an eye on the fill rate.

The Top 3 Strategies for Publishers to Counteract Bid Shading

Loss or no loss, one thing is sure. The way buyers bid for your inventory has advanced for Good. 

Now, it’s time for you to ramp up and respond.

1. Invest in technology - The market today is ruled by those who are ready to adapt to advancement. It’s time to flex the algorithmic muscle. 

Dynamic flooring is one such technology that you can use to claim your power in the pricing ecosystem. Solutions like Mile’s Dynamic Flooring* are built on ML modules. Here, the algorithm goes deep into granularity-

• Data analysis: Utilize machine learning algorithms to analyze historical data, current bidding patterns, and market trends to set optimal price floors for each impression in real-time.
• Micro-segmentation: Implement dynamic price floors for different inventory segments based on the above data and factors like device, audience demographics, and content type.
• Feedback loop: Leverages feedback loop (reinforcement learning) to observe how bidders are engaging with the set floor and adjust price floors proactively to capture maximum fill rate.
• Predictive modeling: Leverage predictive analytics to forecast future bid trends.
• A/B testing: Continuously test the impact on fill rate, revenue, and overall effectiveness.

 Result - Inventories sold at their best market price.

*Mile’s Dynamic Flooring is available for the Prebid environment. You can use UPR for GAM. Amazon TAM and UAM come with their own pricing mechanism. 

2. Capture more data - By sharing data and insights, publishers can gain a more comprehensive view of the advertising ecosystem, including advertiser behaviors, market trends, and pricing strategies. This collective intelligence can enhance publishers' bargaining positions and enable more informed decision-making.

• Create consortiums with other publishers to share bidding data, gain market insights, and collectively negotiate better terms with ad exchanges and DSPs.
• Partner with data providers to access insights into advertiser behavior, market trends, and audience demographics to set strategic price floors.
• Advocate for industry-wide standards on bid shading practices to increase transparency and create a fairer playing field for publishers.

3. Worship your users - Utilize technology like AI to personalize the ad experience based on user context, preferences, and real-time behavior. Create a more immersive and engaging experience for users and potentially command premium pricing.

• Design ad formats that engage users through gamified experiences, increasing ad recall and getting auctioned at higher CPMs.
• Implement real-time auctions within the ad unit, allowing users to influence ad pricing based on their engagement or choices.
• Offer micro-rewards or incentives to users for engaging with ads, promoting positive user experiences, and potentially attracting high-value brands seeking engaged audiences.

The Game Is Afoot (Not Lost)

Success is always there. The question is how willing you are to innovate and push the boundaries. Embrace data-driven insights, explore unconventional solutions, and continuously adapt to the ever-evolving landscape.

This strategic standoff can only shape the balance of power, pricing dynamics, and, ultimately, the revenue outcomes in digital advertising markets. By taking charge of innovation, you can transform from passive participants to active players, ensuring your voices are heard and your value is recognized in the digital advertising game.