Director, Decision Sciences, GlobalWide Media
As audience-based advertising strategies continue to draw a sizeable amount of ad dollars into the tech industry, the definitions of “Digital Transformation’ and “Digital Innovation” have begun to converge for businesses. Brands are now focusing on creating personalized ads that match up to the modern customer experience standards. To know more about the state of adtech in 2018 and the major pain points that advertisers should get rid of, we spoke to Zackary Cantor, Director of Decision Sciences at GlobalWide Media.
Tell us about your role and how you got here. What inspired you to be part of an advertising technology company?
I lead Decision Sciences at GlobalWide Media (GWM), the team responsible for developing and implementing the predictive analytic solutions that underpin our ad-serving logic. I started my career as a financial analyst within a global investment management firm. However, it didn’t take very long before I realized that the culture at these investment firms is not for me. Luckily, this realization coincided with an industry-wide hiring boom in which ad tech companies were looking to ramp up their data and analytics organizations, and financial analysts like me were heavily targeted by recruiters.
What has kept me interested and inspired after moving to ad tech is the constant supply of novel, interesting problems that we need to solve to stay competitive in a rapidly evolving climate. The industry has also served me well from a work culture perspective in that work-life balance is prioritized, organizations are less hierarchical and advancement is truly merit-based; none of which I found to be true in finance.
From the point of view of a data-driven technology company, how would you define “Digital Transformation’ and “Digital Innovation”, respectively?
“Digital Innovation” is any technology, product or service that achieves the goal of making digital experiences more relevant. Incremental innovations typically come in the form of incorporating new data sources or identifying novel applications of existing data. Whereas “Digital Transformation” is radical or disruptive innovation, which typically introduces a new paradigm or approach within digital advertising. A recent example from GWM was the introduction of our RYPL platform.
How do personalized ads match up to the modern-day customer experience standards?
I think the modern-day consumer would argue it’s a poor match. This is partially the result of the high bar set by innovations like a la carte TV or product customizer tools like those offered by Nike and Harley Davidson, just to name a few. However, this is also partially the result of the basic rationale behind marketing, and the resulting incentive structures. Companies serve ads to prospective customers to increase their market-share or otherwise increase revenue. It is impossible to achieve growth without engaging a group of people who ultimately won’t be interested in your product or service.
The key for marketers is to ensure the stockpiles of consumer data that we’ve been generating are intelligently deployed, increasing predictive accuracy and diminishing the error margin in personalized advertising. I’m a big proponent of open-source solutions like the R Project for Statistical Computing or the Python scientific computing packages like NumPy, pandas, etc.
What are the major pain points for advertisers when they deal with the multi-touch video engagements?
In our experience, the biggest pain point is sticker shock, especially when an advertiser has strict direct response goals but deploys traditionally upper-funnel, expensive media executions like multi-touch video. An alternative is to combine high awareness video engagements, which introduce new prospects in the funnel, with lower-funnel display executions that provide a more cost-efficient call-to-action.
How do you see the convergence of Data Science, Programmatic and Customer Experience technologies impact advertising budgets?
I believe advertising budgets will continue to grow at more or less the same rate. What will change is the distribution of advertising dollars. For example, the cord-cutting trend means traditional television advertising budgets are being slashed in favor of digital executions that tap into OTT. Within digital, the efficiency of programmatic advertising technologies, combined with the highly-targeted messaging made possible by data science, means that customer acquisition carries a smaller price tag. As a result, we’re seeing larger budgets for upper-funnel, high awareness digital media campaigns.
What tools does your marketing stack consist of in 2018?
GWM has focused on developing an in-house marketing technology stack consisting of a proprietary DMP, a predictive analytics platform, and an exchange-integrated DSP. GWM enhances its stack by working with 3rd parties for data enhancement (Oracle Data Cloud, Adobe Audience Manager), advertising verification (MOAT, Double-Verify, IAS) and independent media attribution (NCS, Placed, Convertro, VisualIQ).
Would you tell us about your standout digital campaign at GlobalWide Media?
Our most recent standout digital campaign involved testing RYPL, our newest platform capability, for JohnnyWas, a national apparel brand. RYPL identifies users that are inclined to influence others and then intelligently messages those users to stimulate the offline conversation about a brand. The RYPL-powered campaign generated a 39% lift in sales over the campaign that messaged only prospective consumers. Rob Trauber, CEO of JohnnyWas, attributes this success to the authenticity and credibility that comes from hearing about a brand from a trusted peer rather than a paid celebrity.
How do you prepare for an AI-centric world as a marketing leader? How do you leverage AI capabilities at GlobalWide Media?
GWM has made significant investments in technology to support a platform capable of real-time marketing automation. Such technologies were viewed as cutting-edge just a few years ago, but are increasingly becoming that standard. That said, it is important to understand that AI is a tool for accomplishing a marketing goal, but is not the “be all and end all” solution. The TI-83 calculator is a wonderful device capable of performing all manner of statistical calculations. However, if I gave my mother the TI-83 and asked her to use it on the AP Statistics exam, I dare say she wouldn’t fare very well. We in the industry should be mindful that machine-learning, by any other name, can produce calamitous results when employed by people who don’t have the domain expertise to understand the problem being solved. At GWM, we combine years of marketing experience with cutting-edge predictive analytics to produce superior performance outcomes for our clients.
Thanks for chatting with us, Zackary.
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