Gartner and McKinsey Global Institute forecast trillions of dollars in annual impact from artificial intelligence, yet most marketers 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:
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.”
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:
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.
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.
Just because marketing technology companies claim they use AI, machine learning and deep learning, doesn’t necessarily mean their solutions are actually much more intelligent or efficient than what you’re already using.
Often times there is some form of AI in select features within their product, but the product as a whole probably isn’t as advanced as their marketing messages may lead you to believe.
Many of the marketing technology companies are just starting to experiment with AI themselves, and while they may have roadmaps for more integration of AI moving forward, it’s still early. So, they’re caught in a tough spot. They want to tout the intelligent elements of their products, but they don’t want to overpromise what it will deliver in the short term.
The other reality is that many of the marketers and salespeople at these marketing technology companies who are responsible for branding and selling the AI technology don’t actually understand it themselves.
This all causes a big disconnect in the market, which creates confusion and frustration on both ends.
The more you understand AI and what to look for in solutions, the greater chance you have of finding the right technologies and creating value for your company.
The most effective way to approach marketing AI is one use case at time, since AI is built to do very specific tasks (e.g. optimize email send time, predict lead conversions, write email subject lines, recommend content to users).
The key is thinking about everything your team does regularly, and then considering two primary factors:
The value to intelligently automate all or portions of that activity, with value being defined by potential time and money saved, and the increased probability of achieving business goals.
The ability to intelligently automate the activity, based on existing AI tech, or solutions that could be built with the right resources.
We built a free, ungated assessment tool that can give you a headstart. AI Score for Marketers enables you to explore and rate more than 60 AI use cases, and get personalized recommendations for AI-powered vendors.
The use cases are rated on a 1 - 5 scale based on the same question: “Assuming AI technology could be applied, how valuable would it be for your team to intelligently automate each use case?”
The final report page surfaces all use cases you rate 4 - 5, and provides vendor matches based on your ratings. You also receive an overall AI Score, as well as section-by-section scores that are designed to help prioritize your research in the areas you value highest. The entire assessment takes about 7-10 minutes.
>>> Prioritize your marketing AI pilot use cases with AI Score for Marketers .
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.
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. The C-Suite has to be bought in on the value and importance of transforming your marketing.
The velocity of change is going to accelerate because of AI, and it will be at a rate unlike anything we’ve seen before in the industry, including email, social, mobile and the Internet itself.
“AI is one of the most important things that humanity is working on. It’s more profound than, I don’t know, electricity or fire,” — Sundar Pichai, Google CEO (Recode/MSNBC)
The change may appear to be gradual, but you don’t want to be left behind when all of the sudden everything has evolved.
Don’t try to convince executives using jargon and buzzwords. Talk to them about the metrics that matter and show them how AI can solve real business problems in a more efficient and intelligent way. For example:
The true pioneers will involve the entire marketing team in learning and adopting AI through education, interactive training and experiences. At minimum, you want key members of your team to be enthusiastic, rather than fearful, about the opportunities ahead and have the ability to identify use cases and business problems that AI will solve more efficiently.
In the M IT Sloan Management Review and BCG report, Tassilo Festetics, VP of global solutions at Anheuser-Busch InBen, shared how he took his entire team for a weeklong immersive experience in AI. Festetics said, “ It is important for the team to understand the basics of machine learning and AI to be able to identify game-changing opportunities for the company, be it for commercial, supply, logistics, or employee-related topics.”
As a starting point, Google offers a collection of free educational resources at ai.google . You can also experiment with AI technologies through IBM Watson . IBM offers free demos of AI solutions such as, natural language understanding, natural language classifier, personality insights, tone analyzer and visual recognition.
>>> Bring your team to the Marketing Artificial Intelligence Conference (MAICON) , July 16 - 18, 2019 in Cleveland. Group discounts are available.
In the process of making marketing more intelligent, AI has the potential to make brands more human by enabling marketers to focus increasing time and energy on listening, relationship building, creativity, culture, and community. AI should make us better people, professionals and brands.
However, this won’t happen without a focus on privacy, ethics and morals. AI gives us superpowers, which can be used for good or evil.
Think about how the rudimentary marketing technology we have access to today is already used to manipulate opinions, emotions and behaviors. Now imagine that technology is 10x, or even 100x, more powerful.
AI constantly learns, and never forgets. It can be trained to leverage individual behaviors, preferences, fears, beliefs and interests to personalize experiences. It can know where you’ve been, where you’re going, who you’re with, what you’ve written in your emails, what you’ve asked of your voice assistants, what songs you listen to, what mood you’re in, what groups you belong to, what stores you shop at and more. And it can use all of this information to provide the right product at the right time, sometimes before you even know you need it.
Pioneers will consider the ramifications of the AI technology they create and use. I truly believe AI will have a disproportionate net positive impact on the industry and society, but it will alter career paths, displace jobs and continually chip away at our privacy as consumers.
We have to be willing to have the hard conversations as an industry now, to make sure we don’t ruin what will be the most transformative technological shift we experience in our lifetimes.
>>> What You Need to Know: AI + Ethics
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, I hope you’ll join us at the Marketing Artificial Intelligence Conference (MAICON). Visit www.MAICON.ai to view the full agenda!