In the digital advertising world, IAB has always worked to light the way for the industry as we entered new and unexplored areas. With rising industry-wide conversations and interest from members, IAB is launching its first Artificial Intelligence (AI)/Machine Learning (ML) Working Group to help marketing, technology and advertising executives navigate the impact that AI and ML will have on the space.
As someone who works in this space every day, I speak with a lot of executives at major companies, and awareness and understanding of AI is still low. Here are some of the questions I hear regularly:
“Isn’t AI just the latest buzzword that’s happening far in the future so we don’t need to worry about it yet?”
Forrester predicts by 2020, (that’s 2 and a half years from now…) the companies who effectively master AI will steal $1.2 trillion per year from those that don’t. Many of the big tech companies, and a huge number of well-funded startups, are already using Artificial Intelligence and Machine Learning to gain a competitive advantage and plan for their futures.
If you’re not thinking about it yet, hold your wallet because the race is on.
“Hmm, I’ve been hearing a lot about AI and Machine Learning, I’m kind of embarrassed to ask, but what does it really mean?”
AI is a broad term referring to computer programs that mimic human behavior. Machine Learning is a powerful type of AI that mimics human thought. If you teach the computer how to do something, it will then get smarter and be more effective at that task as it continues to work on it.
“OK – got it, but that’s like self-driving cars and robots, right? What are some practical examples of how it will apply to the marketing and advertising space?”
As much as marketing and advertising have been influenced by technology over the past few years, some core principles remain the same – most marketers aim to do three simple things: find the right people, say the right thing and execute effectively.
AI and ML will have immense impact in the marketing world across these three areas:
- Find the right people – Volunteering for the armed services is a brave and selfless act. However, recruiting people is hard as so much of the decision is based on timing and circumstance. A cliché approach to recruiting for the armed services is “setting up a table in a shopping mall,” which is similar to the way that a lot of advertising targeting works – make a broad assumption (potential recruits will visit the mall) and hope for the best (maybe our sign will attract them). The US Air Force took a different approach earlier this year by using Machine Learning to analyze the different attributes of young men and women across the US and predictively target the people most likely to volunteer for service. This not only takes the guess work out of advertising, but it also identifies hard-to-reach audiences with the right message.
- Say the right thing – Advertising creative has evolved in recent years to be more personalized and take on a more authentic tone. Toyota and Saatchi LA recently used AI to train their advertising creative “a thousand ways to say ‘Yes’”, with an end goal of making “an ad for almost every single potential buyer of this car.” While the AI took a little time to learn various language nuances, in the end Toyota was able to deliver thousands of versions of this creative which spoke perfect English like, “Yes, it’s Mother Nature approved,” “Yes, this car is an ode to tech” and “Yes, the future is available now.”
- Market most effectively – Marketing is a mix of art and science, but the science portion is often hard to scale and insights are always tough to activate on. EBay has incorporated machine learning into their CRM marketing tactics to move from “Batch and Blast” emails, which previously sent the same deal on shoes (for example) to millions of their loyal customers. They found that not all of those people were interested in shoes, so they built a real-time, Machine Learning-powered system which would analyze behaviors of their subscribers to make sure they were emailing specific product deals to people who showed an interest in that product. They tied this system to their sales data so that they could measure success as well as constantly teach the machine how to be more relevant.
IAB AI/ML Working Group Goals and Next Steps
I’m excited to be co-chairing this group with the CMO of IBM’s the Weather Company, Jordan Bitterman, under the leadership of IAB’s Susan Borst, Deputy Director, Mobile. We had our first kick off meeting where more than 100 IAB member companies signed up to help guide the future of AI and plan to tackle relevant topics, including:
- Understanding how AI and ML will impact our business
- Simplifying, defining and setting standards for the space as it relates to the advertising and marketing industry
- Organizing tools for the industry to plan ahead
- Thinking about responsible usage of AI so that humans and machines work well together into the future
Moving forward, there will likely be a series of deep dives on various aspects of AI including bots, voice and more. We are excited to see the direction this energized working group takes and hope you follow along on the journey.
The IAB AI/Machine Learning for Marketing Purposes Working Group is open to IAB members only. IAB members who are interested in participating should email email@example.com to join the working group.