Home Networking Reinventing the Wheel (To Run Yourself Over)

Reinventing the Wheel (To Run Yourself Over)

SHARE:

Networking“Networking” is a column focused on the evolving roles of networks in online advertising.

Today’s column is written by Michael Katz, President, InterCLICK.

Ok, I admit I didn’t come up with the phrase and I hate to be the bearer of bad news but (the top 25) networks aren’t going away anytime soon. Recently there has been a tremendous amount of hype surrounding demand-side platforms (DSP) and real time bidding (RTB). DSP’s are wildly popular among agency executives (and the media) while RTB is very popular among exchanges and yield optimizers (and the media). Seems like everyone still wants to displace the ad network, this time it’s a group of companies that are basically ad networks but not calling themselves such, at least not yet. While there are some things the DSP’s are doing right in terms of increased transparency, everyone needs to keep in mind these are primarily just ad networks operating without any real domain expertise. People are basically calling for the replacement of something proven to be effective with something that has really no proof.

While I hate predictions because nobody really cares who is right or wrong, I’m going to throw a couple of predictions out there. First, I predict that one of the agency trading desks calls it quits by mid-year. Second, some DSP’s will start calling themselves ad networks (again) by the end of the year. The reason: the general approach is flawed and they don’t know that they’re wrong because everyone is telling them that they are right including investors, the media, and some agencies.

The Concept of a DSP

A DSP is simply an ad network with transparent reporting around cost, inventory, and performance that doesn’t take any media risk. DSP’s offer a centralized buying terminal for agencies to transparently create “private networks” on behalf of their clients via technical integration into exchanges and yield optimizers, as well as traditional spot buys with individual publishers. Once aggregated, the DSP empowers the agency to bid on an impression-by-impression basis based on various bidding strategies and automated buying techniques such as real-time bidding (RTB). Offered either as a self-service platform or as a managed service, the DSP affords the agency transparent pricing via a “cost plus” relationship. The “cost” represents the cost of the inventory and the “plus” is a fixed percentage that varies depending on the level of service offered by the DSP. Additional benefits offered by the DSPs include insight reporting and global frequency cap management.

The Reality of a DSP

The promise of global frequency cap management is a complete misnomer when more than one DSP, ad platform, or ad network is used. Global frequency cap management is predicated on a single buying platform and as long as the number of platforms is limited to one, it makes no difference if it’s called a DSP or a network. Once two or three DSP’s or networks are added to the mix, goodbye global frequency cap management. There are actually some agency teams currently testing up to 6 DSP’s at once right now after removing all of their ad network partners.

“Private networks” are merely a set of approved inventory sources that are configured at the campaign or advertiser level. Inventory aggregation is one part of the equation and arguably it’s the easiest part of the equation. Access to inventory, even access to data is no longer the issue, value is in the execution. The execution must consist of more than just “an algorithm”.

No matter how effective the algorithm may be, a combination of automated and manual optimization is required in order to make campaigns perform successfully at scale. Its extremely naïve to think that there is the media buying equivalent of an “easy” button where campaigns get loaded into the DSP and magically perform at scale. That may work for one single campaign, it also may work for several campaigns without any scale, but it simply will not work for several campaigns attempted to being run at scale through one platform.

The self-service model doesn’t work for display advertising, so let’s forget it even exists -and now the economics of the DSP model start to fall apart. Fees for managed service range from 30-40% of media cost yet no leverage is being gained because inventory risk is not assumed. This is basically the same amount that networks have taken to cover the fixed and variable costs of building innovative businesses without the same ability to generate upside on performance.

Impression level decisioning can be effective although its still unproven at any scale, the quality of inventory accessible via RTB is still mostly low quality and weak performing inventory at this point (it will get better though, it will just be in Q4). Lastly, even when access to better quality inventory via RTB becomes a reality, without a coherent data strategy, people will just be making uninformed decisions in real-time.

Coherent Data Strategy

While inventory aggregation is important, it’s more important to have a coherent data strategy. Since nearly every campaign has a specific objective, the price of an impression is a reflection of the value created. In order to successfully determine that value of each ad impression, you must first understand the value of the inventory as well as the value of the data. It seems obvious; however, understanding the impact that data has on specific inventory is fundamental in determining when to apply data and which data to apply.

Optimal campaign performance may not always come from the target audience loosely outlined on the RFP, optimal performance may require complimentary or replacement pieces of data. These facts often come from various data providers so simply buying data from one provider and then attempting to find those users in a pool of aggregated inventory simply won’t cut it for so many reasons. It’s important to remember that data is a raw material, and no matter what your objective is—sheer access to raw materials does not guarantee successful execution. Data needs to be refined and applied in a way that delivers the best final product. You must have a platform purpose built to ingest and combine any kind of data along with the organizational structure to execute properly.

In all, I think some DSP’s may provide value and will ultimately be one part of the buy. They will power the percentage of each buy that remains in-house for the agencies and depending on how successful they are, that percentage will vary…

Follow AdExchanger.com (@adexchanger.com) on Twitter.

Must Read

Netflix Touts New Measurement Capabilities As It Struggles With “Modest” Engagement Growth

Netflix’s revenue grew 12% YOY to $12.9 billion in Q3, which it maintains is in line with its forecast. Its ads business, however, is lagging slightly compared with expectations, causing Netflix to tweak its forecast for the rest of the year.

Apple Publishes Its Plan To Wipe Out Web Tracking

Apple is coming for identity resolution. WebKit’s latest tracking crackdown targets the infrastructure behind post-cookie IDs – and switching to a first-party setup won’t necessarily spare vendors.

AI Slop Sites Are On The Rise. Is Ad Tech Ready For Its New MFA Challenge?

Advertising supply chain intelligence company DecryptAds uncovered more than 2,100 AI-generated recipe sites that are monetized with programmatic ads and feature fabricated author profiles.

Privacy! Commerce! Connected TV! Read all about it. Subscribe to AdExchanger Newsletters

How Australian Home Lender Lendi Measures The Invisible Work Of AI

Most brands and businesses are trying to figure out how to improve their metrics when it comes to AI – and also what those metrics even are.

AI Startup Minerva Built An Agentic CDP, But Don’t Call It That

Minerva wants to turn fragmented customer data into something marketers can use, with AI agents doing the work behind the scenes.

VideoAmp Bets On AI To Connect Ad Planning And Measurement

VideoAmp is competing in the measurement space by sharpening its focus on TV audience data, ad performance and, of course, AI. The company is also making strategic hires and promoting from within.