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Spotlight on Innovations in SSP Technology

Spotlight on Innovations in SSP Technology

October 17, 2016

A transaction is a two-way process: the cycle only works if a buyer with money to burn is connected to a vendor with something to sell. But the value of a good supply system is often eclipsed by the need to satisfy demand — especially in the digital advertising industry. 

Within the programmatic sphere, for example, you’ll find plenty of praise for demand-side-platforms (DSPs) and the new opportunities they’ve created for marketers. Yet it’s likely you won’t hear much about technologies on the publisher side, like supply side-platforms (SSPs).

Despite the fact SSPs form a vital bridge between publisher inventory and the DSPs or exchanges that manage demand, their importance is greatly underestimated. As the tool used by most publishers to make digital ad impressions available on the open programmatic market, they are an essential element of almost any automated deal, and more besides.

So let’s take a deeper look at the advanced capabilities of this undervalued programmatic wallflower by bringing SSPs and their technological innovations into the spotlight.

Why SSPs matter to both sides

It’s true that the primary function of SSPs is providing publishers with the means to offer their inventory to a vast, aggregated group of demand channels and in doing so — drive both competition and cost-per-thousand impressions (CPMs) higher. But that’s not all they do.

SSPs enable publishers to enrich each impression with first-party data, which not only raises its price tag, and increases publisher yield, but also improves targeting accuracy. By assessing this data against their unique targeting criteria — which might include users in a certain location, with an interest in particular products — buyers can identify and bid for only the impressions that stand a good chance of reaching, and engaging, their ideal audience.

How have SSPs developed?

While DSPs have matured in the limelight, SSPs have quietly gone through an evolution of their own in the shadows. The technology began life as a yield optimization tool — used by publishers to help them distribute the inventory that had not been snapped up by direct buyers across a range of buying networks. In these early days auctions were shaped around price, with ad networks contacted in order of which one was likely to offer the best value.

Widely known as ‘the waterfall’ or ‘daisy chain’, this system had its problems. Chief among them was the risk that if an impression did not find a buyer in the first network — or if a network defaulted — it would go on to the next, and the next, with its price falling along the way. Then came the rise of real-time bidding (RTB) and the opportunity to integrate with multi-faceted DSPs that turned yield optimizers into SSPs capable of instantly linking publishers with an ocean of demand sources, and vice versa. The technology also developed smarter reporting and accounting abilities, as well as the capacity to set floor prices to keep impression values high, making it a comprehensive end-to-end solution for publishers.

Yet the race to stay on top meant SSP offerings reached a similar level, with the scope of their demand and the ROI they delivered the only true differentiators. So SSPs increased their power to make inventory more appealing by expanding options to sweeten deals with additional user data. And this brings us to the present day — where even data enhancement is becoming standard and SSPs once more need to bring something new to the table, like being able to use historic trading data to foresee what the best next decision will be.    

The future of SSPs

Having achieved mastery in matching buyer specifications with publishers’ audience data in real-time, the next logical step for SSPs is to start predicting which impressions buyers will want in the future, when they will want them, and in what creative format.

By harvesting data from billions of previous transactions and integrating with intelligent tech that can identify behavioral patterns and learn buyer, and publisher, preferences, SSPs can anticipate optimal matches between supply and demand before the auction begins. This will not only help ad ops managers build more efficient inventory trading processes, but also give buyers faster access to impressions that meet their needs and in turn, ensure ad quality and relevance continuously progresses — delivering a constantly improving experience for users.

Moreover, predictive data doesn’t have to be used for just streamlining deals; it could also become an integral element of business strategy on either side. With a precise view of the placements that have delivered the best results, buyers can make informed decisions about where to allocate spend. And for publishers, a complete view of which impressions are in high demand could inform floor prices or where they choose to make specific units available.

One more thing…

So, we’ve established that SSPs are the undiscovered gem of programmatic advertising, but before you adopt an SSP of your own, there is one more thing to consider.

For buyers and sellers, clarity is crucial — buyers want to trade in a transparent environment where they know who they are dealing with and what they are getting, and so do sellers. This means when choosing an SSP, publishers must take care to select a provider with not just an ethical code that matches their own, but also a reputation for above-board trading.

If publishers take care to partner with and support the greatest innovators of the SSP world, they will enable this underappreciated technology to flourish and develop further. Perhaps the time will soon come for SSPs to take their rightful place in the spotlight.

Follow Alex Bornyakov (@abornyakov) VertaMedia (@VertaMedia) and MarTech Advisor (@MarTechAdvisor) on Twitter.

(As published on MarTech Advisor)