The robots aren’t here to take our jobs. Yet. But marketing AI (artificial intelligence) is here to stay.
While the fear exists that machines may soon replace us, reality is that AI has a lot of learning left to do before it can automate the work of strategists, executives and other key organizational decision makers. Even so, many companies are beginning to explore opportunities to leverage the power of marketing AI to make their work faster, smarter and more actionable.
In fact, according to Gartner, “Global business value derived from AI is projected to total $1.2 trillion in 2018, an increase of 70 percent from 2017.” What’s more, “AI-derived business value is forecast to reach $3.9 trillion in 2022.”
That’s a lot of potential business value! The business context isn’t surprising when you consider how AI is already abundant in our personal lives, whether we realize it or not – Gmail suggested email replies, Google/Facebook photo facial recognition, Netflix movie/TV show recommendations and even Amazon product recommendations all involve some form of AI. Now, more organizations are beginning to understand the business value of marketing AI in three key areas: improving the customer experience, generating new revenue and reducing costs.
With all the hype surrounding marketing AI, it’s already become somewhat of a “buzzword” and it can be difficult for organizations to know how to get started – or if they should at all. Large players, such as Google, are clearly making big bets on the future potential of AI technologies, but how can marketers tap into that potential to improve what they are doing and create a better experience for their customers today?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. - Google CEO Sundar PichaiClick To Tweet
3 Ways to Get Started with AI for Marketing Right Now
Gartner predicts that “In the early years of AI, customer experience (CX) is the primary source of derived business value,” which makes sense given organizations’ focus more broadly on CX today. Better CX typically yields happier customers, which means more revenue, and therefore more value to the business.
Here are three ways marketers can tap into the power of marketing AI today.
1. Personalization at scale
One of the greatest challenges (and opportunities) for marketers today is creating a connected, uniform CX. Customers no longer differentiate between channels throughout the purchasing process and have come to expect a seamless transition – from web to mobile to social to chat to app, the brand experience should be consistent and personalized. But simply adding a personalization token with [insert first name] to your website and emails is not enough.
Marketers are turning to AI to help solve the problem of personalization at scale. Products such as Uberflip and Seventh Sense are helping marketers solve this problem through the power of AI by optimizing what content users are seeing and when they are seeing it according to their preferences, and how they are most likely to engage. Look for more companies in this space as marketers work to create the feeling of 1:1 interaction with customers en masse.
2. Content creation/optimization
By and large, humans are still much better than machines at natural language generation (NLG); however, there are a number of companies tapping into the power of AI to generate content at greater scale (and hopefully, with greater impact) than humans. Phrasee, for example, uses AI to write email subject lines that are customized depending on your brand voice and can consistently outperform those written by a human counterpart. Automated Insights is developing AI that can conduct real-time analysis to turn data into insights. NLG still has a fair way to go before it can effectively write long-form content as well as we can, but look for this as an area of tremendous growth in the near future.
3. Analysis paralysis
We have data for everything. But sorting through and making sense of that data takes a significant amount of time. This is a natural fit for AI as machines can do this much faster and more effectively than we can. Google Analytics, for example, now has functionality that allows users to “Ask Analytics” plain language questions as part of their Analytics Intelligence features that “use machine learning to help you better understand and act on your analytics data.” Companies like PaveAI are using machine learning to plug-in to analytics and provide data-driven recommendations meant to help marketers increase the ROI of their efforts.
This is Just the Beginning for Marketing AI
Marketing AI is still very much in its infancy, and we’re going to see many more upstarts in addition to the big players enter the field with new tools designed to make us more effective and efficient as marketers. But it’s not too early to get started right now. Explore some of the tools that already exist – just make sure you have a solid business case before you do. Experimentation is good, but it should be done with purpose, typically either to increase revenue or cut costs. The companies that have implemented marketing AI successfully within their organizations have done so with specific uses in mind that allow them to focus their efforts and measure ROI once the experiment is complete. Happy tinkering!