Marketing AI Institute | Blog

What’s Stopping Marketers from Getting Started with AI?

Written by Sandie Young | May 22, 2019 2:17:00 PM

Editor’s Note: This post is part of a series featuring speakers from the Marketing Artificial Intelligence Conference (MAICON). For more information, visit www.MAICON.ai.


Artificial intelligence (AI) in marketing is a game changer. It has the potential to increase revenue growth and increase productivity and efficiency across your team.


But, it’s also intimidating.


Those who shy away from the unknown will undoubtedly fall behind. That’s what Carl Schmidt (@schmidtdisturbr), CTO and Co-Founder of Unbounce (@Unbounce), will address at the Marketing AI Conference (MAICON) this July in Cleveland.  During his session—How Marketers Can Overcome the Barriers, Shift Cultures and Earn a Competitive Edge Using AI—Carl will share how innovative digital marketers are and can adopt AI to drive better results.


In this Q&A, we asked Carl why marketers are having trouble getting started, challenges to expect during those initial trials, and more. Read on for a preview of his session.

Q: What are the most common reasons stopping marketers from adopting AI?

A: Unbounce recently asked over 400 marketers about their sentiment towards AI, and while over 80% of them believe that AI will have positive impacts on their marketing efforts, they faced a variety of challenges including lack of budget, immature data infrastructure and an inability to map AI efforts to tangible ROI, amongst others.

More broadly, there seems to be a general lack of understanding around the state-of-the-art—what’s possible today, which vendors are harnessing AI to drive real tangible results and how to apply AI techniques in-house. These unanswered questions are making it tough for marketing leaders to make the call to invest in AI. Before anyone was even talking about AI, there was already an overwhelming number of marketing tools and software to choose from.

Today marketers are even more overwhelmed by the options and confused by the many claims of what AI can and cannot do. I’m happy to see a conference that aims to educate marketers on AI. I think it will give marketers the perspective, insights and education they need and want to start making larger investments into AI.

Q: What steps should marketers take to get started with AI?

A: Start with education. Marketing teams, executives and other senior leaders really need to develop an understanding of the kinds of things AI can do today, and where this technology is headed in the future. I imagine that the transition to AI will have at least as much impact as the transition to the Internet did back in the late 90s. For those that recall, lots of companies really missed the boat because they failed to understand the fundamental impacts of a connected world. The transition to a world filled with intelligent machines is likely to be disruptive.

Q: What challenges should marketers expect when piloting their first AI project?

A: It’s important to remember that the goal of any innovation initiative should be to learn something new and take risks. This commitment means accepting that these initiatives can fail, and companies need to allow for that. Rather than putting all of your efforts into a single project and potentially exhausting your innovation budget, consider leaving yourself room to make a number of attempts and counting on a smaller number succeeding.

The second thing I’ve seen is that the notion of what AI can do relative to human-level performance is really challenging for many individuals to accept. Often folks want a smart machine to provide them with insights so that they can exploit their hard-won expertise to make decisions based on those insights. However, what we’re learning is that this rarely produces the best outcomes. In fields such as medicine, law and science, we’re seeing that if you can build an AI model around a particular function or task, machines will very often beat the human-level performance of the same task (even if, sometimes, we’re unable to explain exactly why). In 2018, Unbounce launched a 6-week pilot program aimed at exploring how we can use AI to help our customers increase their conversion rates. We experienced some of these challenges as well. Even when we could demonstrate superior performance, the black-box nature of these systems didn’t always leave marketers with confidence and trust in the system. You have to ask yourself if you’re ok with better results, even if you can’t always explain them.

Q: How can marketers measure the ROI of AI-based projects?

A: Avoid projects where the ROI is intangible. Focus instead on AI efforts that drive tangible results such as more leads generated per dollar of ad expense, higher email open rates, increased sales, etc. Tools that promise only better marketer productivity are interesting, and they may solve problems within your marketing organization, but it’s going to be much harder to demonstrate the business impact.

Q: How can AI create a competitive advantage for marketers that adopt quickly?  

A: At Unbounce, we see the increase in Google and Facebook advertising costs as being an increasingly large barrier for companies and marketers. AI technology in the conversion optimization space can help marketers find new ways of increasing conversions (rather than increasing their budget) by optimizing lower in the funnel.

We’ve also identified that many tools that offer conversion optimization today require lengthy testing and feedback cycles that can take months, require high traffic volumes, free-flowing ad spend and a level of scientific rigor most marketers don’t have. Again, AI technology can help remove these roadblocks and as a result, elevate campaign performance.

Q: What are you most excited about at MAICON 2019?

A: If I had to pick just one thing, it’s the chance to connect with folks who are digging into AI and marketing, and who are genuinely excited about the space!

Q: What advice do you have for marketers just starting with AI?

A: Be patient. For many organizations, this is going to require a pretty big cultural shift, and that takes time, incentives, buy-in; everything you’d expect with a large, disruptive change. Oh, and go read The Innovator's Dilemma to get a sense of what you can look forward to.