We’re back with another episode of the Marketing AI Conference (MAICON) Speakers Series—recorded live onsite at the inaugural event in Cleveland, Ohio.
If you missed episode 1: Check out the premier post featuring a podcast with insights from Karen Hao (@_KarenHao), senior AI report for MIT Technology Review, and Cal Al-Dhubaib (@caldhubaib), chief data scientist at Pandata.
If you aren’t sure what MAICON is all about: The Institute's goal in launching MAICON was to help marketing leaders understand, pilot and scale AI in their organizations. More than 50 speakers joined in 2019 to help us do just that, including presenters from Facebook, Grant Thornton, HubSpot, IBM, MIT Technology Review, Publicis Sapient, SoftBank Robotics, The Natori Company and Yext.
At the conference, Paul Roetzer (@paulroetzer), founder of the Institute and creator of MAICON, sat down with leading AI experts to ask a few burning questions. You can tune into these conversations by downloading the four-episode podcast series on the MAICON Speaker Series, or you can simply start with episode two below.
For ongoing marketing AI know-how, subscribe to our Marketing AI Institute newsletter, and join us for MAICON 2020, July 14 - 16 in Cleveland.
In this episode, Paul interviews Loren McDonald (@LorenMcDonald), Program Director, Marketing Research at Acoustic (formerly IBM Watson Marketing) and Mike Kaput (@MikeKaput), Director of the Marketing AI Institute. He chats with the two AI experts about how to use AI to optimize email and content programs for success.
Below, get to know more about our featured guests—plus a full transcription following the recording.
Note that the transcript below was transcribed by Otter.ai. Please excuse any typos–the AI is still learning to understand human language flawlessly :)
He has written more than 500 articles and delivered more than 350 presentations and webinars around the world. Loren has more than 30 years of experience as a consultant, marketing executive and thought leader at companies including Arthur Andersen, USWeb/CKS, EmailLabs, Lyris, Silverpop and IBM.
PAUL: Hi, I’m Paul Roetzer, founder of Marketing AI Institute, and creator of the Marketing AI Conference (MAICON). MAICON is designed to help marketing leaders understand, pilot and scale AI in their organizations.
The inaugural event was held in Cleveland, Ohio, July 16 - 18, 2019 and drew 300 attendees from 12 countries.
There were more than 50 speakers, including presenters from Facebook, Grant Thornton, HubSpot, IBM, MIT Technology Review, Publicis Sapient, SoftBank Robotics, The Natori Company and Yext.
This (four episode) podcast series features insights from (seven of) our speakers who we interviewed onsite. The conference covers an array of topics including: what AI is, how to get started with AI in your organization, AI applications for voice, how to humanize your brand, and how AI will transform marketing moving forward.
AI is forecasted to have trillions of dollars in annual impact on businesses, and, yet, most marketers are still struggling to understand what it is and how to apply it to their businesses and careers.
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 now and be proactive in creating a competitive advantage for yourself and your company.
If you choose to take action, I hope you’ll subscribe to our Marketing AI Institute newsletter, and join us in Cleveland for MAICON 2020, from July 14 - 16.
Now, onto the podcast. Today’s episode we’ll focus on how to get started with AI in your organization.
PAUL: Our first guest is Loren McDonald, whose role at Acoustic is to produce research-based thought leadership content. He also educates marketers on digital marketing best practices and emerging trends, including the application and impact of AI and machine learning. Loren told us about his evolving role.
LOREN: So really excited. On Monday of this week here at at MAICON we actually announced a brand new company, Acoustic, and so it's actually the first time ever in the 108 years of IBM that they've actually spun off a company into a completely separate standalone company. so I've been part of what was called IBM Watson marketing division, which was basically all of the marketing software solutions within IBM and those were spun off and purchased by a private equity firm. And again we On Monday we very exciting launched the brand and the new name of the company is acoustic. And so my role basically is driving the thought leadership content. Fundamentally when possible sort of research based as a do a lot of benchmark studies and studies and surveys so really sort of helping drive forward a lot of other people I work with that actually sort of develop and produce the content but coming up with what are the trends what are the things sort of as kind of the thought leadership content expert and driving that.
PAUL: Our second guest is Mike Kaput, Director of Marketing AI Institute. This year at MAICON, he did a workshop for attendees about using Artificial Intelligence for Content Marketing and Email, and also led a session How to Future-Proof Your Marketing Career in the Age of AI . To begin our conversation, Mike told us about his role.
MIKE: I am the Director of Marketing A.I. Institute which is a media company that started in 2016 and one of the main drivers behind marketing conference as director of that company which was started by MAICON creator Paul Roetzer or I'm in charge of the overall strategy and content of this site. The site publishes to date hundreds of articles and resources for marketers to make A.I. more approachable and actionable for marketing professionals and teaches them to a variety of means how to use artificial intelligence in their career in their companies and how to build a competitive advantage with this technology.
PAUL: In addition to his role at Marketing AI Institute, Mike also works with me at PR 20/20, the marketing agency that powers MAICON. Mike used his experience in that role to talk about “intelligent” strategies and how they differ from a traditional approach.
MIKE: In addition to working at marketing AI Institute I'm actually a marketing consultant at PR 2020 which is a marketing agency that powers this whole event. I've spent the last decade working with hundreds of different clients all of whom are trying to create content and build marketing strategies online that actually drive leads customers and revenue. And as part of that obviously content is a big piece but it's not. Always been historically very intelligent. So companies will understand that creating content for customers that educates them on their offerings and builds relationships is important.
But that's about where the intelligent part stops because once you start creating that content. Historically there haven't been as many sophisticated ways of understanding what your audience wants what they're searching for what they're looking for what they would like to read consume and how they would like to do that. All of these things require data on your customers on readers on consumers. Historically companies just haven't had enough data and the ability to extract insights from that data to then inform what they're actually creating content around artificial intelligence has changed that. So artificial intelligence has given us the ability through certain tools and techniques to start intelligently understanding exactly what content consumers want when they want it and how they want to consume it.
PAUL: After establishing the benefits of implementing an intelligent strategy, you may be wondering where you could use AI in your own marketing efforts. Our guests shared some use cases that are emerging first as the “low-hanging fruit” for leveraging AI and ML technologies. Here’s what Loren said, especially as it pertains to email marketing.
LOREN: So you know one of the one of the first ones that sort of emerges has actually been around actually for a while something called send time optimization. And you know we can we can sort of debate among engineers and stuff if rather this technology is actually true machine learning and a lot of people – depends on on like the tool and the technology is – it's just it's really just math or predictive analytics. But fundamentally that's one of the ones that's that's a fairly easy low hanging fruit for companies what it basically is is you know I've been in the email marketing space literally for 20 years and there's two or three questions that marketers and email marketers have asked consistently for those 20 years one is sort of like what what's the average open rate I should be targeting or getting.
PAUL: And Mike shared his thoughts on the subject, emphasizing use cases for content marketers.
MIKE: So content marketing use cases especially narrow and well-defined ones are already occurring with artificial intelligence technology. So today at this conference there is a technology that can write email newsletters for you and hyper personalize them at scale. That technology exists today. There is technology that will tell you what customers and consumers are what preferences they have towards certain topics and products so that you can create content around those preferences that exist today. There also exists artificial intelligence tools available on the market that. Will even write email subject lines for marketing emails push notifications and ad copy. So today all of those applications already exist. Looking forward we can probably expect to see tools that take some of those initial use cases and expand them even further to artificial intelligence tools that write even longer form copy potentially or surface even more insights about what consumers and readers want at scale.
PAUL: Many people at the conference have talked about the barriers they face when trying to implement AI in their company’s marketing strategies. One approach to overcoming these barriers is to prove AI in small way before scaling efforts. We asked Loren for some simple email functions to get started to prove AI’s value.
LOREN: Another one that's kind of in the same vein is is subject lines you know subject lines or something that every every business person writes like every day you know you write you write subject lines to when you're sending emails to co-workers or to family members or something like that and as marketers. They tend to I'm going to generalize here and 9 out of 10 email marketers will wait till the last second to create the subject line so that they might spend days or weeks even like working with their designers and content teams and commerce teams or whoever you know depending on the company they're working with to come up with a message and landing pages and making everything great. And then it's like oh message is going out an hour we need a subject line and they'll come up with something they'll turn to like. Co-workers in their cube or something. And like what do you think or maybe they'll send it a couple of people if if they're you know having sort of their act together they might actually test three or four different ones. But this is where the power of machines computers sort of come into place where literally they can actually come up with billions of combinations in other words you can you you train these systems about like your own brand what is what words and tone things like Are you a serious brand are you a hip cool brand. You know and you basically you train those individual systems about your your own company and brand and what style of of language that you want to use as in scope and out of scope. And so then when you sort of feed in kind of your core goal for that particular messages and a sort of basic human developed subject line it can come up with literally billions of variations for that. And so ultimately the machine sort of. Learns and figures out and knows your customer base and as it learns over time it will recommend you know it depends on that sort of the vendor and tool and stuff. But a simple example is it'll come up with 10 machine driven subject lines and then you add in your human one and it tests it it tests those in it and whichever one wins then it sort of actually goes out and most of the tools out there it like ninety eight ninety nine percent you know delivering better better results than human based one and they're heading towards 100 percent right. So that's one again it's sort of a really simple concept but the reality is. You know if you have a subject line that has you know a five percentage point or two or three percentage point lift over your human driven one if you have you know a million subscribers and you're an e-commerce company I mean we can literally be talking about tens and tens of thousands of dollars for that one message over the year. You know you might be talking about hundreds of thousands of potentially millions and lift in revenue. So it's pretty significant.
PAUL: Mike added some other strategies for implementing AI in small ways, in order to build your employer’s trust in AI.
MIKE: So what we typically do with both clients and internally at our agency and the marketing AI Institute is take a look at the activities that you as a content team or content marketer do every single day, week, month or quarter. Chances are if you start listing out all the things you're responsible for from creating blog posts to uploading social media to promoting across channels. If you write all of this stuff out take just 15 minutes to do it. You're going to then be able to go down that list and you will notice some commonalities. There are probably going to be a lot of activities that are very repetitive. For instance on my team. Historically we would create three to five blog posts a week content creation happen regularly. It was immensely time consuming and it happened all the time. For each piece of content we would also be uploading posts scheduling social media and promoting that content. Within all of these activities the ones that are repetitive ones that are data driven. These can very likely to some degree be intelligently automated either today or in the near future.So we would start with very time intensive and repetitive tasks and then begin exploring what use cases there may be for artificial intelligence to do those tasks.
PAUL: A lot of guests at the conference have asked “What are some ways marketers can started in AI?” Mike offers this advice.
MIKE: So one of the top use cases I would start investigating would be intelligently automating potentially performance reporting so we all create performance reports either for clients for customers or internally of some type. Some people do it weekly some people do it monthly whatever you're trying to understand how Web site behavior through Google analytics or a similar tool. How those behaviors impact your strategy. And today. For most marketers that involves manually looking at Google Analytics noting a number of trends or data points from that tool and then writing them all up in a narrative for an executive team for their team for themselves. You're saying OK website traffic was up 10 percent this this week. What does that mean. Where did it come from and what should I do about it. We actually internally at PR 2020 we've used an intelligent automation tool today to automate those types of narratives. We used to spend five hours a month on these types of reports per client and we have dozens of clients today. It takes about 30 seconds so it's just a very clear simple use case that doesn't even use full robust artificial intelligence. It's just more intelligent automation so before you even get into what we would consider really sophisticated A.I. you can already save hundreds of hours for your organization by automating performance reporting.
PAUL: Loren urges email marketers to look at the obvious.
LOREN: Look at the tools that you are already using. I mean fundamentally you know we're talking about email marketing here it means that anybody that's listening to this and cares about email marketing I presume is already using some sort of an email marketing platform. And the reality is is that platform you're using probably already has you know like we talked about earlier send time optimization and things like that. It probably already has or some sort of recommendations or things like that in it that you can sort of start with and and and leverage. So what I would say is first is before you sort of run out to the marketplace and look at the thousands of startup A.I. vendors that have emerged is actually just see what you already have and are probably already paying for and it may not even either either be leveraging it or maybe you have somebody you like you didn't turn on like example I mentioned the send time optimization. Most of the tools you already have do. “Flip a switch” for lack of a better term to enable that. So if you don't turn that on like you're not taking advantage of machine learning. Right. And so that that's what I would say before you kind of go out and look at the landscape of a thousand vendors out there go through and sort of almost do an audit of the tools you're currently using and you might be surprised at what’s there already.
PAUL: AI can be daunting, but I think our guest today show that you don’t have to dive in head first. It’s okay, and potentially smarter, to get your toes wet and prove the value of an intelligent strategy for you company. I encourage you to try implementing one of these strategies in your own marketing efforts.
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I’m Paul Roetzer, owner and CEO of PR 20/20 and founder of MAICON. Thanks for listening to the Marketing Artificial Intelligence Podcast. If you enjoyed today’s discussions with Mike Kaput and Loren McDonald from this year’s MAICON event, I’d encourage you to check out our 2020 event at MAICON.ai. This annual conference is held in Cleveland, and brings together the leading experts of the marketing and artificial intelligence communities. We hope to see you there.
This podcast is a production of Evergreen Podcasts. A special thank you to:
Producers: Brigid Coyne & Dave Douglas
Audio Engineers: Sean Rule-Hoffman, Dave Douglas, and Eric Koltnow
Thanks for listening. We’ll see you next time!