Ad Tech’s Image Problem: Matt Fanelli of MNI on What Must Change

MNI Targeted Media Inc. (MNI) is a targeted media strategy, planning, and buying company. The company reaches more than 240MM uniques monthly and recently ranked #1 on comScore’s monthly US multi-platform report for the third consecutive year. We spoke with Matt Fanelli, MNI’s SVP of Digital, about the ad tech industry’s image problem and what the industry can do to correct it.

There’s a lot of talk in the ad tech industry about brand safety and inventory quality, especially since P&G issued several strong statements on what they saw as industry failures. What are the biggest problems that you see in ad tech for brands?

Brand safety and inventory quality is something that every vendor, publisher or ad tech company should have a position on, and process in place, if they are a true player in the digital space. One of the bigger misconceptions is that companies do not have a brand safety plan in place and instead are running blindly on questionable content or less quality inventory. As programmatic continues to advance, the industry has become more sophisticated in tracking and in utilizing verification partners like Moat, Integral Ad Science and DoubleVerify that allow publishers and ad tech companies to more closely monitor invalid traffic and poor inventory sources. In terms of challenges that ad tech companies will continue to face, staying on top of what the latest verification platforms are and the certifications necessary to run in a brand safe environment will be vital, as well as adhering to all of the metrics that go along with them. Educating brands on metrics such as viewability, invalid traffic, and how it relates to running in a brand safe environment will continue to be a hurdle companies will have to overcome regardless.

What can the industry do collectively to make the ecosystem more transparent and beneficial for brands?

The biggest lack of transparency stems from programmatic and gaining transparency into costs. Too many brands are running media where they have no insights into the data fees and/or sources they are utilizing to find their target audience. Also, things like fraud and viewability continue to be segmented based on the partner being leveraged without one solid standard across all digital media. This is something that will continue to cause issues for brands until it is solved.

There seems to be a notable shift toward a more holistic view of marketing among major brands. What are you seeing among your clients?

The conversation we’re having with our clients is about an integrated approach. Research from both the Association of Magazine Media (MPA) and Interactive Advertising Bureau (IAB) suggests that having a consistent message across channels can improve both upper and lower funnel metrics, with the best campaigns having a balanced mix of both digital and traditional media.

With an integrated approach, our clients challenge us to provide metrics around the most efficient channels. The industry as a whole is still figuring out attribution modeling, and we are no different. As we collectively agree on a more standardized approach to modeling, which includes the secure sharing of data both ways, we’ll see more and more integrated campaigns be put to the test when it comes to measuring brand awareness, purchase intent and sales lift.

Are we moving toward an “everything” algorithm as machine learning seems to take over, or are there specific cases where human eyes will always be needed?

Machine learning, particularly in the form of programmatic media, has allowed us to become more efficient and nimble when buying and executing digital media buys. As an industry, it allows us to be faster and scale our businesses, by making smarter decisions based on the data we obtain when running digital campaigns. However, no matter how smart the machine, there is always the opportunity for technical errors, which is why a human eye and touch is necessary to minimize errors. In order to optimize and ensure a campaign is running to the best of its ability, having the human element of strategy is also something that machine learning will never be able to replace. An automated system can certainly make performance-based recommendations depending on what tactic or partner is performing the best, however, understanding a brand’s objective and the campaign that is in place based on a client’s needs is something that will always require the human element in order to push digital efforts forward and provide clients return on investment (ROI) on their digital investments.

What do you see happening in the future as brands become more critical of inventory, outcomes and quality control?

Brands are going to become more aware of where their ads are running and what data is being leveraged to find their audiences, as they become more acquainted with programmatic ad buying. Brands will start to become more focused on quality of the data that they are leveraging and potentially the type of sites they are running on versus cost. In terms of outcomes, brand marketers will learn that by leveraging more enhanced data sets, they will drive more qualified traffic to their site, helping both lead based and conversion based advertising campaigns.

Learn more about MNI here.

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