A Conversation With Anil Kamath, VP of Technology, and David Karnstedt, SVP of Media and Advertising Solutions
All catch phrases aside, algorithms, data and predictive analytics are some of the most important parts of today’s marketing process. Most of us seem to love the flipping of phrases. Take the ubiquitous and colloquial phrases “50 is the new 30,” or “nerdy is the new cool.” As Mad Men has helped enforce, the debonair, quick-on-his-or-her feet marketers were the quintessential centerpieces of advertising for decades. They drank scotch at noon yet never ceased to produce the quickest quips on command.
Yet the digital era has ushered in a need for a complimentary counterpart to the creative marketer – one who focuses on data. Many people have recognized that data – not just the mere collection of it but the analysis and predictive implications of data — holds the key. However, there were some early industry trailblazers, such as Anil Kamath, founder of Efficient Frontier, who now serves as VP of Technology at Adobe in the Marketing Cloud Digital Marketing business, that were quick to recognize data’s significant role in the future of the industry. David Karnstedt, SVP and GM of Media & Advertising Solutions at Adobe, was another.
Anil and David recently provided us with thoughtful views on the rising role of the data scientist in marketing, or what we used to call algorithms engineer.
What was your “A-ha” Moment for Data Science?:
Anil: What Efficient Frontier did right when we founded the company in 2003, and what we are building upon at Adobe now, is taking the lead on building algorithms-based marketing systems. There have been many companies that aggregate large amounts of data and provide reports and analytics on this data so that marketing teams can understand what impact they are having and make decisions. But a good analogy is the difference between a smart dashboard and fancy controls for a car vs. a self-driving car. Algorithms have been used in advertising campaigns for quite some time as well, but data-influenced, end-to-end decisioning systems are a recent phenomenon, and Efficient Frontier was an early pioneer in that area. I had seen it taking place on Wall Street, and my ah-ha moment was seeing that it could be done in marketing back in 2002.
At Adobe, we are looking to expand this paradigm to web experience management, social advertising, and more. Adobe’s marketing products use data and algorithms for many aspects of digital marketing. Two major ways we use it are: to make the actual marketing decisions driven completely by data+algorithms and second by aiding (augmenting) marketing professionals with data+algorithms driven insights and predictions to enable them to make better decisions. We analyze large amounts of data to extract signals and make predictions. We then use these predictions to make decisions that automatically optimize marketing campaigns to drive peak marketing performance. Adobe customers benefit from both aspects of data activation and have a choice in which way they utilize us and our data.
David: I agree and can’t stress enough how important activating data is. It’s not simply about data collection but leveraging it and creating insights. That’s where the real magic is. Adobe has an incredible team of diverse roles coming together to humanize data, analyze it, bend it and make it sing for our clients. It’s imperative to look at the field almost like physics.
What are the critical skills of today’s data scientist?:
Anil: We look for 3 skills in a data scientist. First, they must love working with data – lots of data, slicing and dicing and analyzing data in different ways to understand it better. Second, they must be good at math – statistics, machine learning, and optimization. They need to construct mathematical frameworks to solve practical marketing problems with the data. Lastly they need to program – write software that uses the data and the math to actually solve the marketing problems and iterate and improve the software to deliver better marketing results.
David: Analytical and well-versed in marketing and marketing trends is a must for our data executives. Data scientists and marketing executives have become the perfect complement to one another. Our team of data scientists has driven ROI that has powered our fast-growing business into the leading provider of digital marketing solutions in the industry.
Ten years ago, could you have imagined data scientists would be as important and in demand as they are becoming?
Anil: The ubiquity of the term is surprising. But in hindsight it seems inevitable that this would happen. The explosion of data availability that became possible with the Internet and the speed at which decisions can now be made meant that data analysis and algorithms driven by data that can make these quick decisions had to be done by people versed in that science – the data scientists.
David: Yes, I was betting on it! I hope that kids and young adults today who are interested in technology can easily access the resources they need to grow into innovators of tomorrow and keep this trend on the rise.
A study from The McKinsey Global Institute last year states that by 2018 the demand for deep analytical positions in the Big Data world could exceed the supply by 50–60% of those qualified. How do you think young people can be lured into this profession early on while in college?
Anil: It is already happening – the hype around BigData and algorithms has led to a big increase in people taking an interest in Data science. A recent online artificial intelligence course offered by Stanford attracts an unprecedented 160,000 students from over 190 countries. There is now an incredible access to the information on data science. Online courses on databases and machine learning from the best professors at MIT and Stanford are now available for free online. If you need practical experience with real world data there are large real data sets made available by companies like Netflix on which anyone can experiment.
David: Data scientists are in high demand, and we need to harness the interests of our youth today in the US. We need more emphasis on this training in the coming years in education institutions.
How do you feel about the term Big Data? What does it mean to you?
Anil: The term Big Data has different meanings to different people based on what they do with the data. The part of Big Data that is meaningful to me is the processing and analysis of large amounts of data from a variety of sources to do actionable analytics and predictions that can then be used to by algorithms to drive marketing performance.
David: Big Data is just another buzz word. When it hits Dilbert cartoons you know the term has reached a place of almost meaninglessness. The next overused word will probably be attribution or media mix. But the intention behind Big Data for many is powerful. One of the driving forces for our announcement of both software and a place for marketers to excel in their work moving to the Adobe cloud is data and how it’s driving much of the innovation and evolution of what’s happening in digital marketing forward.
Is Data a Threat to Creative Professions and Creativity in Marketing?:
Anil: There are many areas of marketing where human insights and creativity are critical — like in designing ad copy or offers. At the same time, data-driven algorithms do a much better job in marketing areas that involve analyzing large amounts of data and using them to make quick and complex decisions. Even where human creativity is important, data science can augment human intelligence by providing insights that can help creative people to see things that they normally might not.
David: It’s just the opposite, really. Data ignites the power of creativity. It allows for automation where it’s needed and provides context around what creative is working, and how it inspires and engages. Our rich heritage in the creative industries drives us in digital marketing to preserve and strengthen the ties between the marketer and the creative professional for the best business results.