The increasing prominence of machine learning in marketing is changing the way the industry operates. No doubt, this evolution is exciting, as it opens up new opportunities to connect with customers in ways that weren’t possible just a few years ago. But it is also terrifying, as the race between the data haves and have-nots intensifies, and marketing FOMO sets in. The good news is that while it may feel like everyone else has already become an AI marketing ninja, the truth is that the industry as a whole is still learning. According to a report by Salesforce, only 26% of business leaders have confidence in their organization’s ability to develop an AI strategy. And this statistic aligns with my own experience working with marketing clients across a range of industries: most companies are at the beginning stages of using data and machine learning in their marketing (but they are learning quickly).
The challenge for marketers right now is that the appetite for AI-infused marketing solutions is high, but the understanding of what AI actually does, is low. Unfortunately, this breeds an environment where vendors play fast-and-loose with the term “AI” and marketers are at-risk of being sold digital snake oil. As an engineer, this dynamic frustrates me. So, I’ve outlined five practical steps for getting smart about marketing with machine learning quickly, in an effort to help marketers become more informed buyers, whether they are evaluating AdTech solutions, interviewing agencies or building their own in-house data science teams.