He’s an assistant professor of management at Purdue’s Krannert School of Management and a researcher with a highly analytical background. Liu earned a double major in information management and economics at Peking University and has advanced degrees from UC Berkley and Cornell in statistics and marketing.
His research and teaching focuses on modeling consumer behaviors, competitive strategies, pharmaceutical marketing and social media marketing. After hearing his excitement about the future of advertising, we just had to share his insights with you:
PA.O: In your opinion, how is programmatic advertising – the growing prevalence of marketing automation, data mining and the cloud – changing the industry?
Dr. Qiang Liu: Programmatic advertising increases the effectiveness and efficiency of advertising with [a] real-time system and rich data from multiple sources. It facilitates the optimization of communication between brand managers and potential individual consumers. With programmatic advertising, brand managers can reach [the] right customers, with [the] right message within [the] right context at a lower cost. It is disrupting the traditional advertising industry, such as traditional media e.g., print and TV. It is also disrupting traditional advertising agencies. The firms without digital advertising expertise are definitely impacted the most.
PA.O: Have you seen any digital marketing campaigns that you especially like? Why?
Dr. Qiang Liu: Yes, Oreo’s brilliant Super Bowl blackout tweet really impressed me. The quick reaction to the big game blackout highlights the importance of a “real-time” marketing campaign in a digital age.
PA.O: What excites you about the future of digital advertising? What are you looking forward to?
Dr. Qiang Liu: The big data and deep machine learning developments excite me the most about the future of digital advertising. With this huge amount of data collected and the ability to learn automatically, firms can gain a more accurate, real-time and personalized understanding of consumer behaviors and be able to give each consumer what they want at the right time and place.
PA.O: Deep learning seems to be a big focus for you in your research. I am very interested in hearing what you have to say on what you think the future of advertising will be.
Dr. Qiang Liu: The future of advertising should be more personalized and data-driven. It should also be more subtle and intuitive. If you can make your advertising with data and at the same time, keep the creative being creative, you can tell the story that will probably work the best. This storytelling has two dimensions. One dimension is in programmatic advertising – which is doing pretty well at being data-driven automation. At the same time, you don’t want to lose that other side, the “being more creative“ – the telling of an interesting story. How do we do that in the future?
That is something deep learning will do for marketing in the future. You’re not just getting information and doing targeting with deep learning. You can actually create something, not just repeat something we’ve already seen before. With math and algorithms, you can create a story that can be attractive to a particular individual consumer. The compilation of big data with deep learning will dramatically change the landscape.
PA.O: Can you clarify – what exactly is deep learning?
Dr. Qiang Liu: Deep learning is basically machine learning. It’s not marketing automation; it’s more than that. Here is an example.
You have so many tweets and Facebook posts, and with computer programming, you can learn the sentiment of these comments. That is just the beginning of deep learning. Deep learning became even smarter.
Let’s say you are on Facebook, and you are wondering how it knows your friend’s faces. This software that recognizes what people look like is deep learning. You can do some amazing things with it.
Deep learning is even used in car theft systems. Let’s say you store some anti-theft device or program with deep learning capability in your car. It will learn your driving habits, so if someone steals your car, the computer program will notice that the driving habits are now different from the owner. It will call the owner and text message them to let them know the car was stolen and where it is.
Deep learning is a more sophisticated and abstract level of machine learning.
What we are doing now is just making copies of advertising. You use the programmatic advertising mechanisms to sell this to a particular individual consumer and get the media place. But that is not enough.
With deep learning software, as I said earlier, we can actually create something new every time. We will find out through algorithms that there is a big idea you need to communicate with an individual consumer. The machine would have actually learned about the consumer using gender, past purchases, movie viewing, articles the consumer has read – everything – to make a mix of information and understand how to speak to this person. I think in the future we’ll see deep learning software creating the advertisements themselves.
We are not doing this now. Google and Facebook are already using deep learning for facial recognition, but we haven’t seen advertisements made with it yet. As I saw earlier in the Super Bowl blackout, Oreo had a team of social media marketers that watch events, and when they thought they had a good opportunity, they decided let’s do it. It took them a little while to put together that campaign. With deep learning they could do this same process automatically – almost instantly.
This is something that really may happen.
PA.O: So, if I understand all of this correctly, deep learning is just algorithms, programs and software. If it is creating our advertisements for us, will we even need creatives or marketers anymore?
Dr. Qiang Liu: No, you still need people to make these things work. It takes time and effort to see something like what I have described to you.
PA.O: What are some of your concerns about the future of digital advertising?
Dr. Qiang Liu: The privacy issue imposes a major challenge to digital advertising in the future. Legislators are currently introducing bills to protect consumers’ privacy. However, overly protective actions may potentially make rich data unavailable to digital advertisers and prevent the industry from improving the effectiveness of targeting communication
Want to learn more about the machinations of Dr. Liu? Connect with him on LinkedIn.