YEO Conference keynote speaker Paul Roetzer explains how AI constantly learns, and never forgets. It can be trained to leverage individual behaviors, preferences, fears, beliefs and interests to personalize experiences.
by Paul Roetzer, Founder, The Marketing Artificial Intelligence Institute
Gartner and McKinsey Global Institute forecast trillions of dollars in annual impact from artificial intelligence, yet most retailers still struggle to understand what AI is and how to pilot it in their organizations.
A recent research project from MIT Sloan Management Review and The Boston Consulting Group (BCG) analyzed AI adoption based on a global survey of 3,076 business executives. The report—Artificial Intelligence in Business Gets Real: Pioneering Companies Aim for AI Scale—broke responding companies into four groups:
Pioneers (18%): Organizations that both understand and have adopted AI. These organizations are on the leading edge of incorporating AI into both their offerings and internal processes.
Investigators (33%): Organizations that understand AI but are not deploying it beyond the pilot stage. Their investigation into what AI may offer emphasizes looking before leaping.
Experimenters (16%): Organizations that are piloting or adopting AI without deep understanding. These organizations are learning by doing.
Passives (34%): Organizations with no adoption or much understanding of AI.
Hear Paul Roetzer discuss AI exclusively at the 2019 Young Executives Organization (YEO) Conference in Springfield, Mo. May 1-2. Visit https://nagconvenience.com/2019-yeo-conference to register for the conference and view the agenda.
Now, keep in mind, this study is not specific to marketing, so the Pioneers percentage would be significantly less if only applied to our industry. The vast majority of brands we talk to at Marketing Artificial Intelligence Institute (MAII) fall into the Passives group, with some easing into the Experimenters category.
No matter how you look at it, we are in the infancy of AI adoption, meaning you and your organization have the opportunity now to be proactive in advancing knowledge and capabilities before your competitors beat you to it.
According to the report, “Pioneers, by deepening their commitments to AI, are establishing positions in both customer and labor markets that may make it hard for others to draft off of their hard work. The many advantages reported by Pioneers suggest that early AI movers may be especially hard to catch.”
How to Pioneers Approach AI?
So, what can we learn from the Pioneers? If you want to create a competitive advantage through AI, here are nine steps you need to take:
1. Think strategically.
It’s easy to get overwhelmed by AI if you don’t understand it. But, at the most basic level, it’s just smarter marketing technology. Therefore, you should think about it the same way you would every other marketing technology investment.
AI needs to solve real business problems by reducing costs and/or increasing revenue. There is no magic AI button that makes your marketing more intelligent and effective. And you can’t just go buy a single AI platform to replace all your existing technology.
AI is built to perform narrow, specific tasks at superhuman levels. So, your marketing technology stack will likely expand, which obviously creates complexity if you don’t plan ahead. Success with AI requires an understanding of what it is and what it’s capable of doing (and not doing), as well as experimentation, patience and a strategic vision.
2. View data as an asset.
A great starting point for thinking about the potential value of AI is to assess opportunities to get more out of your data.
For example, if your marketing team spends significant time every month organizing and visualizing performance analytics, and developing narratives to tell the story of what’s happening and why, that can all be intelligently automated.
You can also look across your marketing and consider all the ways you use data, or should be using data, to make predictions. If you strip away all the unnecessary complexity when discussing machine learning (a subset of AI), that’s in essence what it does. It makes predictions based on historical data.
But, machine learning continues to “learn” (thus the name) and alter its predictions as new data becomes available, much in the way Google Maps recommends alternate routes in real-time as traffic patterns change. This can be applied to predicting: email clicks and open rates, lead conversions, customer churn, content and creative performance, optimal ad budget distribution, ideal price points, audience targeting, consumer needs and preferences, product purchases, campaign ROI and hundreds of other use cases.
A simple rule of thumb when thinking about AI is that if it’s data-driven, a machine can be trained do it better and more efficiently at scale than a human.
3. Focus on revenue-boosting use cases over cost-reducing ones.
For many organizations just starting with marketing AI, cost-saving use cases are likely to be the most logical for gaining early wins and executive support. However, according to the MIT Sloan Management Review and BCG report, “Pioneers prioritize revenue-generating applications over cost-saving ones.”
So, as you’re building your marketing AI strategy, look for the obvious opportunities to drive efficiency and reduce costs with intelligent automation. But start developing the near-term vision for how to use AI to grow revenue through improved customer experience and identification of new markets and opportunities.
It also makes sense early on in your exploration to consider the AI capabilities of your existing marketing technology stack, specifically your marketing automation and CRM solutions. Again, AI is designed to solve narrow use cases, so you could easily end up adding a dozen or more new technologies as you scale.
Talk to your primary marketing technology partners and see if they have AI-powered features that you’re not using. Ideally, take your list of priority use cases from #4 and ask how many of those they can help you with.
4. Educate and engage management.
There is a very real chance that the first couple marketing AI pilots you run won’t work. Or, at least, they won’t generate the cost savings or revenue growth you hoped for.
You can NOT stop because of early failures. That means you’re going to need executive-level understanding and support of AI.
5. Be curious. Explore AI.
You have a choice. You can sit back and wait for the marketing world to get smarter and change around you, or you can embrace AI and be proactive in creating a competitive advantage for yourself and your company.
If you choose to take action, hear Paul Roetzer at the Young Executives Organization (YEO) Conference in Springfield, Mo. May-1-2. To register, visit https://nagconvenience.com/2019-yeo-conference.