Welcome to 2019. This year will see the publication of my fourth business book, Welcome to the Machine: A primer on artificial intelligence for Marketers.
Artificial intelligence represents the biggest buzzword to come to the IT industry since big data and Web 2.0. However, it also carries the weight of dystopian science fiction and negative views of robots taking over the world and perhaps your job. Marketing strategists hear AI — or machine learning as it is known to data scientists — will change their business. What is real and what is fiction?
Readers will learn how to approach machine learning and improve their marketing efforts in Welcome to the Machine. Sign up below for updates.
Welcome to the Machine was drafted in 2018. The book is now in its first revision and editing stage. Expect the book to be released in the second or third quarter of 2019.
Why Write a Book on Marketing AI?
Last spring I emerged from a two-year job as a CMO. In order to ensure that I was ready for the current marketplace committed myself to study the latest trends in digital and became increasingly concerned about the emerging AI wave that is spreading through every segment of the communications business.
At the same time, I took on an adjunct position at George Washington University to teach a graduate digital communications class. My research for both myself and the class revealed few texts on marketing and communications AI. The books that I found dealt with AI ethics and impacts on a society level. Two texts were extremely tactical and offered no overarching trend theory or how it would change communications.
So I started researching and writing Welcome to the Machine to fill this perceived need and explain how AI will transform my peers’ careers and their companies. I believe the book will be useful to today’s communicator offering important insights. The book augments digital marketing theory with pragmatic approaches on how to approach and implement marketing communications AI
In my mind, AI represents a sea change trend that will be as impactful on communications as social media was, if not more so. Every marketer and public relations professional needs to understand the impact that AI and data algorithms will make on all aspects of communications, from how they email their customers to qualifying influencers.
I hope you will find this book useful as your career continues into the next decade, and you encounter the certain AI-driven changes ahead.
I have some exciting news, which is that I am working on my fourth business book. The topic is marketing AI. To better integrate with the larger AI conversation, I have moved my regular publishing to Medium. Below find my most recent blogs on Medium.
To develop a wider audience, I started publishing my artificial intelligence articles on marketing via Medium. Subscribe to get there articles as they are published. Here are three published between July and August.
Artificial Intelligence or AI the buzzword suffers from additional unfortunate baggage. Thanks to an overwhelming body of dystopian and hard science fiction, society already has negative notions of AI. Those preconceived notions vilify robotics and AI, recalling a malevolent sentient machine that’s going to wipe out the human race.
Given the current state of machine learning in the space, worries about marketing automation AI and its brethren taking over the world in the next decade seems utterly unfounded to me. However, try convincing the general public of the current benign nature of AI.
That’s what happens when you choose a very unfortunate buzzword to describe your trend.
Permission marketing is not new. But the principles of opt-in marketing are often abused. AI will antagonize rising tensions about privacy and personal data usage.
While marketing as a profession do a great job of talking about ethics and best practices, most marketers do not or can not marshal the internal resources, buy-in, or knowledge to protect their companies from machine learning produced transgressions.
As a result, many brands will have what Brandon Purcell calls a “moral mirror” thrust upon them, showing them and their customers the unconscious biases of their businesses. Unfortunately, these challenges will be aired on the public stage, almost certainly creating a crisis in the worst instances.
More advanced brands in the marketing segment like Marketo are already deploying their early AI solutions. However, their legacy implementations may prove a hindrance compared to next generation AI-based marketing systems that are rising to compete against them.
One such system is Lucy, a platform developed by a company called Equals 3. Now two years old, Lucy has advanced to become a powerful segmentation, advertising and content optimization tool that’s already developed industry recognized campaigns for brands like BMW.
I interviewed Equals3 Co-Founder and Managing Partner Scott Litman, one of the company’s founders and marketing technology veteran. Here are some of the key questions and answers from our conversation together.
Marketers should celebrate the Artificial Intelligence movement or “AI” as the industry calls it. Don’t worry. AI is an overhyped Silicon Valley term that represents more of a natural progression in technology — machine learning — than the birth of sentient beings.
In the marketing technology space, AI attempts to replace many menial marketing tasks. This empowers more creative minds and strategic thinkers to focus on the work they love, rather than the “vulcanesque” data rich tasks that drive them crazy.
The machine learning marketing evolution brings a couple of caveats, of course:
1) First, strategic marketers must comprehend machine learning on macro level and how to use those systems to inform strategy and lead day-to-day tactical exercises.
Second, some more tactical marketing roles will be either replaced or impacted by algorithmic bots.
2) The idea of tasks being performed by bots scares people. But it shouldn’t. Marketers are seeing some of the most time consuming tasks in their business automated, specifically those that revolve around data points. Almost every marketer I know complains about having to do 3x work in 1x space. This relieves much of the pressure.
Still, to not understand machine learning tools antiquates one’s skillset. To stay relevant, marketers need to embrace new technologies and see how they can be incorporated. Algorithms and bots are not sentient. They need guidance to successfully interact with human.
5 Marketing Functions Impacted by Machine Learning
Here are the five marketing functions I believe will most likely get impacted by machine learning over the next three years:
1) Community Management
The inability to scale created the biggest knock on social media. Deploying teams of humans across the Internet to reply, engage, and build communities on various social networks remains the luxury of only the largest brands. Further early iterations of automation via Hootsuite and Buffer received low marks from conversation purists who found these offerings inhuman and unengaging.
Current iterations like Social Drift for Instagram level the playing field. New bots and algorithms are let community managers engage in real conversations while delegating mundane tasks of following, liking, and unfollowing fall to the wayside. Further, these new bots fulfill a critical role in identifying and targeting influencers, reducing hours of research.
Community managers should find their tasks to be more enjoyable and less frantic. They will have many tools to make their jobs more fruitful and successful if they adapt the latest tools. Community managers who fail to adapt will likely find themselves falling to the wayside based on performance.
2) Content Marketing
Content marketers will greatly benefit from machine learning. From finding competitive content and relevant source material to optimizing message and delivery preferences, algorithmic programs will greatly assist research and content creation.
Scoop.it is one content research example with its Internet scouring capability. While very helpful, Scoop.it results requires a lot of weeding. This is common with machine learning apps. The early results are not great. The better bots improve as their algorithm optimizes based on human input.
In the near term, AI is unlikely to replace content marketers, simply make them better and more efficient. However, like community managers, content marketers must stay up to date with the latest machine learning tools in order to stay relevant and functional in their jobs.
3) Customer Service
From chat bots and smart helpdesk sourcing of solutions to actual AI bots answering calls and of course, Alexa, Cortana, Google, and Siri-enabled applications. Yes, there will be a need for real live voices, but only for the most difficult problems.
Unfortunately, this is one of those areas where machine learning will create significant job loss, particularly in call centers. Expect to see customer service costs and jobs reduced significantly over the next three years.
4) Data Analyst
The data analyst, the person who combs through reports to find prescient data points, and then spits out reports for management will likely see their task automated in the very near future. Increasingly, reports will be offered by algorithms, which when steered and customized to a unique business, will eliminate much of the weekly dashboard testing.
Strong machine learning will also identify emergent trends before a human can, too. Lead scoring system Infer offers a great example of superior data analysis, identifying SQL opportunities well before the human-induced lead scoring algorithm used by most marketing automation systems.
A need remains to steer machine learning to source the right quality data points and ensure that algorithms continue to evolve and meet customer and business model changes. The more strategic data scientist(s) will be required for larger enterprises.
In small businesses, the marketing lead will need a deeper understanding of data science to remain relevant and functional. In essence, someone needs to guide and ensure that data analyzing bots are on point and at a minimum providing useful predictive information.
5) Digital Advertising
Digital advertising is becoming a game of bots. It should be no surprise as this is where the money is at. Google leads the AI ad market with its increasingly complex machine learning-based Google Ads solution that cross pollinates multi-channels to reach customers, even on their smartphones.
As machine learning-based advertising platforms mesh with automation systems and CRM databases, marketer interactions with those systems will increasingly revolve around management. Advertising bots will take inputted spend, target audiences and initial creative and then offer machine learning suggestions. There is a great need for ethics here, as evidenced by the Cambridge Analytica scandal.
In many ways the digital advertising manager will simply approve or correct these suggestions, and then allocate resources as necessary to fulfill them. In the near term, digital advertising agencies can get a leg up on customers by mastering the latest bots and algorithms.
These are just a few of the marketing roles that AI will impact over the next few years. There’s a bot to assist almost every marketing function available now.
But is worrying about job or role replacement the best way to approach the issue? Or should we dive in and embrace the tools provided to us?
Sometimes when talking about potential jobs and projects, I feel a sense of discriminatory ageism about my digital experience. Perhaps it’s the gray beard or that I am not as enthused about Fortnite coming to my Nintendo Switch as the rest of America.
Because I am a Gen Xer and not a hipster Millennial (whatever that is), when I do run into conversations with younger peers — and frankly older executives who assume you need to be in your 20s or early 30s to understand digital — age comes up more often then you’d you think.
Here’s a fictional comedic attempt combining many of the dialogue points I have heard over the past two months.
“So, you were early, one of the digital marketing pioneers. What was your first experience?” asks decision maker X.
“Oh, I hand coded EIA — the Electronics Industry Association’s — first website back in ’95.”
“Seriously? I haven’t heard of EIA.”
“They broke up and became the Telecommunications Industry Association, and the Consumer Technology Association, you know they run CES? That was my first trade show experience.”
“Wow! That must have been crazy! Hey [Grandpa], tell me about MySpace.”
“Well I marketed Sully Erna’s book on MySpace and sold 2,000 copies the first day. He’s the lead singer of Godsmack. But personally, I wasn’t on it, it struck me as pretty cheesy.
“My first social network was really blogging, then when Twitter and Facebook broke in the mid 2000s, I was one of the first power users. I am not on Twitter anymore, though. Deleted my 20,000 person account.”
“What? Why did you do that?”
“It’s a great place to be if you are a brand doing customer service, or a public celebrity or politician opining. Not being one of those, I can do without the troll kingdom and bots. Don’t get me wrong, the last brand I maintained was very active on Twitter, but I see little personal value.”
“So tell me about today’s digital strategy environment? I mean with digital advertising media and Hubspot.”
“Well, we are definitely in an era of data and analytics, which makes it a very exciting time for companies who want to invest in marketing that directly impacts their customers. Automation — Hubspot, Marketo or Pardot for example — is just one type of marketing technology that can empower precision communications. When I implemented Pardot…”
Combating Digital Ageism
It’s always a good conversation, yet potential employers or agencies hem and haw. You would think historical experience is an asset in digital, but many just believe your time has passed. Or dismiss you as overqualified (translation: too expensive) to handle the project they had in mind. Or because of your experience and age, you don’t fit their digital marketing unicorn image.
The question is how to combat ageism. Here are a few suggestions.
1) Training and Certification
Dismissing someone’s skills in today’s marketing world can be easy, even if you know the technology or medium well. That’s where training and certification can come in handy.
Becoming certified in a specific technology eliminates the questions. It’s just assumed you understand the marketing technology. Currently, I am embarking on Google Analytics certification, a crucial aspect of understanding today’s data environment for most brands.
Once I got past bubbling 20 somethings explaining to me on video how a blog works, I understood Hubspot within the context of general automation principles learned using Pardot. The strengths and weaknesses of both programs became evident, and as a result I am better able to have a conversation about marketing automation.
2) Dress the Part
Another way to demonstrate that technology hasn’t passed you by is to dress the part. Not only in your clothes. Don’t wear a shirt and tie when your colleagues are going to show up in a t-shirt and $200 designer jeans. That doesn’t mean look like a slob, but dressing casual — e.g. sport shirt, jeans and cool shoes for me — conveys “not antiquated.”
Dressing the part also means using relevant technology. That includes putting away that beat up iPhone 6 and carrying a modern device (Google Pixel 2 XL for the win), and perhaps a smart watch, too.
Use digital media, too. While no longer on Twitter, I am super active on Instagram, 500 px, LinkedIn, Facebook, and other social networks. I also podcast, and yes, still write a marketing article or two every month.
If someone really wants to look, they will see an active professional working in current media. Communicating with others via those media forms helps convey that indeed, I still get digital.
Marketers that know how technologies change quickly, and are media agnostic — e.g. able to shift as audience preferences change — can better guide companies through volatile evolutions. Consider how many brands were impacted this year by the collapse of SnapChat’s popularity, and Facebook;s self-inflicted data marketing wounds.
Even better, how many are shifting to experiment with Reddit given its corresponding surge in popularity? Successful experiences year after year in digital are the hallmark of a leader that can evolve as technology changes.
Also, be ready to discuss new trends like blockchain and AI and how they may impact a company or organization’s business in the future. It’s one thing to check the boxes, it’s another to navigate a company towards ongoing technology relevance.
What are your thoughts or experiences with digital ageism?
Eight months ago I did the unthinkable: I deleted my 20,000 person Twitter account.
Removing a presence that portrays influence and commands respect amongst many in the marketing world may be the equivalent of social media suicide. But it wasn’t.
While perception may suffer, the real life impact has been negligible.
On a personal basis, I don’t miss Twitter at all.
The Land of Trolls and Bots
Visit Twitter and you find a place dominated by angst, a dystopian social media nightmare filled with trolls, bots, and social media marketers spewing links. The level of vitriol, hate, and general nastiness, fueled by the ongoing toxic political environment made Twitter an unenjoyable experience.
Personal network engagement was fractional compared to other social networks like LinkedIn, Facebook, and Instagram. There was little personal value.
Don’t get me wrong. The brand I represented at the time maintained a healthy Twitter presence for customer relations and to reap the benefits of community engagement, Twitter search, and any Google and Bing SEO benefits.
At the time, I was in-house and not promoting a business. So I had little need for those benefits. It seemed natural to pull the plug.
At the same time I am looking for opportunity again, creating content and marketing myself. Will I return to Twitter and reap the same benefits many brands do?
The real value of social networking for the individual consultantorthe photographerremains peer connectivity. LinkedIn, Instagram, and to a lesser extent a post Cambridge Analytica Facebook deliver higher volumes of authentic engagement with my networks.
Many personal conversations include reference posts I made on LinkedIn or Instagram. That’s how word of mouth works, and that’s the way it used to be on Twitter. Plus there are other ways tomake yourself findable in Googlethese days.
Why invest in something unenjoyable with less yield? No, the solopreneur needs to value their time.
I don’t miss Twitter, personally or professionally.
Data drives almost every decision made in today’s marketing department, in large part because of improvements in yield. As every marketer adapts data-based precision marketing, you can foresee an inevitable ceiling to quantitative marketing.
According to Forbes, 66% of marketing data is used to better focus on targeting offers, messages, and content. That trend will only increase. In 2018, you cannot possibly take on any significant marketing job or project without embracing marketing data and analytics.
With data, marketers create stronger CTAs in more precise channels to deliver higher desired yield. Today, the danger for marketing is letting data-based intelligence become the only voice driving content. Qualitative data and creative are dismissed, at best relegated to a multi-variant test.
What do you get when every marketer in the world uses data to determine who, when and what they communicate? An endless stream of precise spam. That uniform spamming across channels produces a results ceiling.
“You can get the right eyeballs in the right time, the right format, and if you put something crappy there,” it’s all for naught, said Daniel Slotwiner, director of advertising research at Facebook (via Contently).
What the Ceiling Looks Like
Sooner or later, the better performing spamming organization — err marketing organization — will run into a competitive marketplace that provides growth challenges. When the only thing driving marketing and brand is data — while precise — that marketing organization will lose ground to savvier competitors. Those competitors use the same or better data to inform emotionally intelligent brand creative that inspires customers.
Spammy marketers always lose to stronger brands that invest in customer-driven product insights, creative, and content.
To see this play out in real time, look at the auto insurance market. If you think State Farm, GEICO, and Progressive aren’t operating off the same marketing data points, you are sorely mistaken. There a differences, but you can bet the differences are minute.
So why are these three the only auto insurance providers with double digit market share? Is it really because their competitors don’t have marketing automation, data centric approaches to customer marketing, etc.? For example, All State certainly has access to extensive marketing data tools.
It comes down to understanding what compels customers. And the better, more relevant the product’s value proposition, creative content and communications are, the bigger the advantage.
In spite of GEICO’s still often funny ads, the brand sits at number two these days. One can argue that State Farm’s new simplified direct buying process, recent modern creative advertising, and ongoing agent-based distribution channels have simply made it more relevant. As the ad says, you can feel the connection.
Data-based marketing is not a panacea, and has its issues. There is a data glut, and the ongoing uncertainty about which data sets matter most. That in turn produces missteps.
When you dive into the inevitable navel gazing amongst the data marketing influencer set, their answer for marketing data’s weaknesses remains extending networks for more data, such as social networks or CRM. Or even better, identifying the quality data that matters.
Yes. All true.
Data and social analytics provides the compass towards the customer’s specific needs. They can tell you what keywords may work best, when to deliver your messages, and how. Data cannot deliver intangible emotional intelligence or creative brilliance, though.
Therein lies the problem. While the very best most precise data can tell you where to go, it cannot craft the ultimate strategy and campaign content needed to succeed. Perhaps AI and automation can deliver said content, but these tools still need the logic. In essence they cannot drive.
Testing and Artificial Intelligence
Right about now, you will hear data marketers argue they can test creative and content messages, finding the right communication. On this we can agree.
Let’s not pretend that the data revolution provided a new revolutionary way to think about creative: Testing. Smart brands have invested in testing creative for decades. Data has simply made testing cheaper and more accessible to small brands. In the data era, surveys and focus groups are often replaced with live A/B and multi-variant tests of content across small sample sizes.
What the data marketer needs to understand is value. Until you invest in quality content and creative, you will only get stock creative value and crowdsourced level results. You get what you pay for. Since most data-centric organizations are bottom line focused, they will only invest in creative and communications when the larger market forces their hand.
A more interesting argument revolves around artificial intelligence (AI). An algorithm that learns based on performance will provide better and stronger communications to customers.
Will marketing AI replace strategy, creative communications, and content? Unlikely. Perhaps at a base level, much like how simple sports stories are written by algorithms. Instead, AI will replace much of the data analyst’s responsibilities, providing a much more precise view of which data points are compelling customers.
Whatever marketing AI’s impact will be, it’s not ready yet. Is search better because of AI? Yes. Do you still need to enter queries multiple times in different ways to find what you are looking for? Yes.
Human Insight and Spirit is Missing
Today, we value the measurable over the immeasurable. Data fixation as the primary method for determining marketing direction has dismissed the intangible emotional intelligence necessary to compel customers.
The truly successful marketing brand will use data to fuel incredible campaigns that leave its lesser sister brands in the rearview mirror. In addition to supporting the general thesis of this post, the above TEDx chat from Tricia Wang has a fantastic case study about leveraging qualitative data to dominate a market.
Netflix ignored quantitative data about its service in favor of a qualitative data set. The qualitative data showed that people enjoyed bing watching content series for hours on end. The rest, well, that’s history. Today, Netflix has more online video customers than Amazon, Hulu or any traditional Hollywood media brand.
Imagine that. A Silicon Valley data centric company using qualitative human intelligence to dominate a market.