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Approaching the wilds of yield optimization can feel a lot like a bustling bazaar in Marrakech. But instead of being lured by exotic goods at every corner, you’re swarmed by a kaleidoscope of ad networks, exchanges, servers, SSPs, and platforms, each willing to increase your website’s ad revenue. Or promising to do so.
While the sheer number of options can be puzzling, the solutions themselves are usually pretty straightforward. They boil down to the exact obstacles you might be facing and the journey you’ve already passed collaborating with different AdTech vendors, their business model, analytical capabilities, and ups and downs.
What does the perfect media inventory yield optimization depend on? In this article, we’ll go over such common thorny issues publishers face and look at the techniques that make yield optimization a lot less cumbersome to pull off.
Key takeaways:
To clear up any initial confusion, let’s first define the canonical functions of an ad server and a supply-side platform (SSP). Indeed, certain SSPs now provide services that traditionally fell under the domain of an ad server. Some even offer fully integrated ad servers within their SSP platforms. These are, however, distinct services.
An ad server serves as the backbone for storing, preparing, dynamically selecting, and delivering relevant ads based on predefined campaign parameters on a publisher’s website. Unlike SSPs, it focuses on managing ad creative files and doesn’t facilitate advertiser connections to the programmatic ecosystem.
Publishers have the option to either host their ad server or utilize third-party services for hosting and management. A prime example of a hosted ad server is Google Ad Manager that seamlessly integrates with their ad exchange to streamline demand reception.
From the publisher’s perspective, an SSP offers a means to diversify advertising demand beyond reliance on a single platform. It provides access to various demand sources across different platforms and exchanges connected to the SSP. However, it may lack certain functionalities of an ad server.
But which choice is truly the optimal one for a publisher and their cherished website?
1. Data control
Opting for a hosted ad server means relinquishing full control of your data. Additionally, your customization options are restricted by the limitations imposed by the host.
2. Setting a price floor
While a self-hosted ad server could be a potential solution, it still comes with its own set of flaws. And constant updates, integration challenges, and maintenance burdens are not the only ad server drawbacks. Because although having your own ad server offers direct control over creatives and reporting, it lacks one crucial ability: to set a price floor.
Let’s take a closer look at it and why setting a price floor is vital. In general, there are two pricing mechanisms:
| Second-Price Auction (SPA) | First-Price Auction (FPA) |
| Winner pays the price of the second-highest bid plus a minimal increment | Winner pays their bid amount |
As the first-price auction method gains traction, advertisers are embracing a strategy known as bid shading. Utilizing both algorithmic and non-algorithmic tools, AdTech partners determine a value that falls between the second-price and first-price bids, aiming to secure impressions at the most competitive rate. This practice reduces profits for publishers.
Price floor optimization was a solution created in response to make sure publishers receive a fair deal for their inventory.
So, an SSP can adaptively modify your minimum price threshold according to a curve representing the relationship between fill-rate and price. It can progressively elevate this threshold until the point where further price increments begin to diminish overall yield due to a plateauing demand curve, causing fill rates to decline beyond compensatory levels. Likewise, it can give precedence to ad networks with the most substantial incoming bids and fill rates.
3. Tool purpose
Another crucial aspect to consider stems from the direct purpose of these tools: for ad servers, it’s ad serving, while SSPs primarily focus on managing inventory and facilitating resale. Essentially, SSPs let publishers capitalize on surplus ad space in real-time, which means they optimize the value of each pageview.
4. Delivery
And yes, with an ad server, you have the autonomy to serve ads according to your own guidelines, although without any profit assurances. Conversely, utilizing an SSP entails adhering to its delivery rules, relinquishing some control, but with the assurance of generating revenue by the end of the month.
In short, the the best SSP for publisher yield optimization is one equipped with additional features beyond basic ad serving.
However, publishers can also opt for a combination of an SSP and an ad server, such as Google Ad Manager, to retain control over ad serving orders and benefit from SSP revenue assurance. It’s a common approach to inventory yield optimization. In this case, monetization of the available ad space for every single page view would look like this:
Turn to Oxagile’s AdTech experts to deliver a platform that’ll let you maximize advertising efficiency.
If you’re still finding your footing in advertising or have fairly low traffic and are on the hunt for the most effective way to sell ad space, it’s likely you’ve encountered platforms that either underperform or have limited functionality in reporting or other perks. In such a case, our expert suggests several potential scenarios that would be most optimal for you.
One effective method, which is both straightforward and highly beneficial, involves connecting with a wide array of multiple demand partners (SSPs/ad exchanges) in your region.
There are two avenues for accessing demand partners: either directly contacting them for assistance with monetization, or engaging with third-party partners who can facilitate access to premier demand partners (such as PubMatic and OpenX).
Another possibility to explore involves collaborating with an AdTech middleman.
Such middlemen gather mid-scale publishers to tap into larger ad exchanges and connect with extensive ad networks and SSPs. These intermediaries may also offer their solutions for optimizing yield, akin to SSPs but with additional features, providing more comprehensive market insights regarding pricing, competition, and even recommendations for ad layout optimization.
Plus, they can grant several websites access to their GAM account, which they configured themselves, with ad exchange, header bidding, and lots of other third-party partners.
Using both header bidding and waterfall approaches offers another way to work things out, optimizing yield. You can start off with header bidding for your top inventories and then proceed to sell the rest through the waterfall method. This is done to reach comprehensive inventory sales with optimal pricing throughout the process.
The waterfall method, or ad network waterfall, is a sequential process where ad requests are sent to various ad networks or demand sources in a predetermined order until an ad is successfully filled.
Header bidding transforms the conventional approach of soliciting bids from buyers one by one. Instead of sending bid requests individually, all selected buyers receive simultaneous bid requests from the publisher. Unaware of each other’s bids, each buyer submits an offer for the same inventory. The bids are then relayed back to the publisher’s header bidding server or wrapper, where the highest bid wins the inventory.
The beauty of the waterfall approach is that it allows publishers to observe the origins of demand along with the monetary worth of their bids. Consequently, publishers can optimize for the highest cost per mille (CPM) attainable.
Sometimes, even using generally decent solutions for ad revenue optimization raises questions due to high and impractical service costs associated with these solutions and the lack of precise information about internal calculation mechanisms and analytics. And transparency in processes is precisely what provides confidence that you are getting the best price for your ad inventory.
A black box solution is the one that keeps its inner workings concealed or not entirely clear to the user. Essentially, users are aware of what inputs are needed and can see the results, but they don’t have a thorough grasp of how the system operates to produce those outcomes.
A publisher has the option to develop an in-house bid floor optimization solution. By doing so, they can address several challenges:
Learn how Oxagile delivered a supply-side platform for a digital advertising company. The solution can handle enterprise traffic volumes, processing more than 45 billion ad transactions every month. It also allows premium publishers to boost ad revenue via real-time bidding, automate yield optimization, and has advanced analytics.
Publishers face plenty of other challenges in maximizing revenue through yield optimization beyond the ones we’ve outlined here. For instance, manually inputting parameters and setups across different advertising systems is an overarching concern that could benefit from automation, potentially using AI technology.
Additionally, there’s a growing opportunity to incorporate AI for analyzing data insights and guiding decision-making processes, such as adjusting bidding prices, refining targeting strategies, and implementing whitelisting or blacklisting practices, to name a few.
There are more solutions to address challenges that keep websites from reaching optimal profitability, and our experts can walk you through them.
Bring your current setup, and our team will scope the right SSP and ad server mix for your traffic and goals.
An ad server stores, manages, and delivers ad creative based on campaign rules, while an SSP connects publishers to multiple demand sources, like ad exchanges, DSPs, and ad networks, and can auction off unsold inventory in real time.
It is typically one that goes beyond basic ad serving, offering price floor optimization, multiple demand connections, and transparent reporting, or is paired with an ad server like Google Ad Manager for full control.
Bid shading is when advertisers use algorithmic tools to bid below their true value in a first-price auction, aiming to pay closer to what they would have paid in a second-price auction, which can reduce publisher revenue if not offset by price floor optimization.
