I just returned from attending several spring digital marketing conferences – Adobe Summit and Martech West. In both the art of the possible was on full display and got me thinking about whether fully-automated AI-driven digital marketing could ever be a thing, and what realistic automation goals look like.
Spurred on by conference highs and three years of ramped-up writing on AI in digital marketing, it seemed the right time to step back and ask a few questions:
- Is fully automated digital marketing even possible?
- Will marketers wake up one day and find themselves obsolete?
- What should marketers be doing today to prepare for tomorrow?
Is fully automated digital marketing even possible?
Digital marketing continues to be on the leading edge of AI advances and high-tech innovations. Surveys repeatedly indicate AI professionals aim their efforts at infusing intelligence into digital marketing. In fact, for nearly 10 years running, Rexer Analytics’ Data Science survey lists these digital marketing pursuits in the top 10 analytics goals of data scientists [i]:
- Improving understanding of customers
- Retaining customers
- Improving customer experiences
- Selling products/services to existing customers
- Market research
- Acquiring customers
- Improving direct marketing programs
And every day we’re inundated with news of more advances in marketing automation such as:
- Customer behavior data that is automatically processed, like whether someone used a mobile app in the last 30 days
- Lights-out, always-on marketing programs that are triggered automatically and run themselves, often fueled by the pre-computed customer behavior data
- Advances in process automation and examples of programmatic marketing jobs that previously involved human intervention, such as wave/drip campaigns and paid media buys
- Helper tools out the wazoo, like website and mobile app builders, grammar checkers, content taggers, SEO using AI [ii], and many more
Couple all that with a host of technological factors spurring on AI and automation like:
- Digital devices, tags, and pixels gathering data at breakneck speeds
- Falling data processing and cloud storage costs
- Free open source tools and freemium pricing models that put more software in the hands of more marketing users
- Adaptive algorithms that learn which offers customers respond best to without supervision or manual testing
- Natural language generation handling some previously thought to be untouchable human tasks, such as automated writing (although today’s NLG performs just simple writing tasks)
From all this, some might conclude the end of human-powered marketing is close at hand. But others, unconvinced by these tenuous signs, might simply respond, “Poppycock!”
With years of history to draw on, during which digital marketing was born and came of age, perhaps the real answer lies somewhere in between. In pouring over this progress and assessing the full landscape of today’s automated processing and AI in digital marketing, it’s clear humans have played and will continue to play a crucial role.
In the last 25 years, we’ve seen human ingenuity cause marketing to go digital, get more scientific, and its content to get richer, more compelling, and hyper-personalized. So, without a doubt, AI in digital marketing is a real thing. It has improved reach and targeting, quickened the pace of experimentation, automated direct impression and response tracking, and compressed marketing program cycles.
To accomplish all that, marketers have employed a plethora of applications, from SEO tools to email tools to campaign management systems to creative suites to mobile messaging platforms. And make no mistake – automation has paid dividends and enabled more personalized marketing at scale. Companies that use marketing automation in the development and execution of their tactics have improved conversion rates, grown revenues, and become more efficient. In my career, I’ve seen piles of firms lift response and conversion rates up to 3x, and in some cases as high as 12x, doing so without exponentially increasing team sizes. And all along, technology-minded humans have remained instrumental components of both developing and executing those systems.
Will marketers wake up one day and find themselves obsolete?
Ironically, during this period of hyper-automation, the number of digital marketing jobs has grown, not shrunk. And the outlook is rosy, not bleak. In fact, the US Bureau of Labor statistics projects another 24k jobs will be added by 2026 in the US alone [iii]. In 1995, there was no such thing as an SEO analyst, a social media marketer, or a mobile marketing manager. Though some old jobs have disappeared, and some are at risk, there’s no indication that people gainfully employed in digital marketing today have anything to worry about.
If you’re a grizzled old marketing vet like me, you’ve already seen automation encroach on various tasks. For instance, writing email subject lines, deciding the best time to send that email, or even deciding how much to bid for digital ads – can all be automated. Yet simultaneously you’ve watched as new roles have emerged. If you’re a little younger, you’ll see even more amazing things in the future.
As certain aspects of marketing production become machine-executed, such as when to trigger a re-marketing treatment, new marketing opportunities emerge that require human intellect, such as determining if augmented reality provides marketing lift.
It’s a given AI will improve to where more complex tasks – and whole jobs – can be performed by machines, such as completely replacing telemarketers as suggested in this landmark Future of Employment study[iv]. This phenomenon is not new. It’s known as collective learning and has been affecting human advances since people invented language, writing, and tools. It’s one of the main reasons for societal and technological evolution as it fosters sharing and accumulating knowledge by allowing us to pass down knowledge and build on it via spoken and written communications. And it’s what’s enabled us to refine and evolve our machines.
But collective learning is not just about machines advancing. It’s the combination of humans evolving together – essentially becoming one system. As such, it’s not rational to assume AI in digital marketing will cause all human jobs to succumb to computerization. Expect instead machines to take over simpler roles just as they’ve taken over much of our manual labor in farming. They’ll ride shotgun with us, learning from us, correcting us, and mastering our simple and repetitive tasks – while we move on to create, invent, and fine-tune new, more complex ones. And along the way, we’ll be assisted by machines as we invent those new brand-new roles.
In my recent article on AI and technology trends that are affecting marketing (5 predictions for CRM’s AI applications in 2019), I discuss the trend toward effective combinations of crowds of human and machine intelligence. Organizations that build open systems that take advantage of this power and embrace it will outperform those that don’t.
To better understand why digital marketing won’t be fully autonomous anytime soon, it’s helpful to inspect the full journey of a marketing initiative, from idea inception to program execution. Marketers work in two main factories:
- Creative factories where ideas are born, iterated, refined, vetted, simulated, and approved for use
- Operational factories where select ideas are executed, monitored, tested, tracked, and retired
Creative Marketing Laboratories
Narrow (single purpose) AI systems have enjoyed some interesting achievements recently, such as painting masterpieces and writing books (this one, a riveting read on lithium-ion batteries). In marketing, AI has written image captions, tagged content, and even helped with content generation. But it’s far – way far – from putting all these pieces together and being the de-facto creator of new ideas. Humans own this space and will for some time. Responsibilities in jobs such as program strategists, copywriters, SEO experts, product marketers, and graphical/interactive designers have progressively increased. Consequently, these people do more and do it faster with automation’s assistance.
Operational Marketing Factories
Operation managers are inherently driven to streamline, rationalize, and automate processes. And they use industrial engineering and machines to do it. But just as an old-model car has limits on how much it can be modified, production marketing systems have the same inherent limitations. And there is no evidence that the cloud, low code, or agile is changing that. After about ten years, old systems need to be replaced or they reach a point of diminishing returns.
And radical change involves teams of people organized in large efforts to transition to new technology and redesigned processes. No machine accomplishes this without humans. Enterprises still employ hundreds if not thousands of humans to design and test their new marketing engines. Once in production, people feed the machines, monitor them, and fix them when they break. There’s plenty of work to go around. Expect digitization and human-machine process reengineering to accelerate, possibly compressing the marketing system replacement cycle from ten years to five years.
As this happens, expect marketing tasks like this to become more automated:
- Customer data processing and summarization
- Some feature engineering for model data prep
- Pattern detection and event-based triggers automatically kicking off insight gleaning tasks and/or marketing treatments. Examples:
- Detecting customer intent, such as intent to purchase based on multiple signals
- Predicting and detecting key life events, such as a move, and providing proactive valuable offers
- Certain marketing programs that run completely lights out with automatic monitoring and tuning
- Send-time optimization for all types of customer interactions
- Automatic impression and response capture
What should marketers be doing today?
One lesson is don’t fear automation and AI in digital marketing, embrace it. Marketers and CX professionals must automate to remain competitive and ensure their survival. They must reduce the cost to acquire and deepen customer relationships, or standby while their competitors do it.
Ultimately, the savviest marketers build systems that entice customers to engage in less expensive and fully automated channels. By doing so, buying cycles are compressed, the cost to serve comes down, and customer satisfaction rises. But marketers must carefully monitor to see that satisfaction, revenue, and market share are improving. They must constantly ask, “Are these automated or semi-automated interactions delivering hyper-personalized, frictionless, and valuable experiences?”
So regardless of how you rate your marketing capabilities today, there’s plenty of room for improvement. Presently, most marketers still take about three months to create and execute new programs from inception to execution. And many interactions, whether via branch, store, call center, or email, are still inefficient and labor-intensive.
Marketers must strive for efficiency and excellence in creative and operational areas. Here are some things to consider in both:
The Modern Creative Laboratory
Consider these checklist items and benchmarks:
- Form small teams of five to seven using modern collaboration tools like Slack
- Incent teams to do research before brainstorming sessions. Don’t reinvent the wheel
- Hold brainstorming sessions in public and private. Limit sessions to a few hours in public and a few days in private
- Don’t mute wild ideas; encourage them. Don’t just end up with a better buggy whip
- Limit testing wilder ideas to 10% of budget, time, effort
- Ensure the process, ideas, and outputs are transparent and easily accessible by others
The Modern Marketing Operations Factory
Consider these checklist items and benchmarks:
- Employ small teams of five to seven using modern agile and marketing operations tools that force item prioritization, templated based case management, workflow, task creation, and work sprints (for repeatable processes)
- Integrate content management systems and processes with marketing automation. Fuse output to final step revision and deployment management systems and processes
- Separate business-as-usual (BAU) changes from capability changes. For example, making minor adjustments to an existing promotion would be treated as BAU, and these kinds of changes packaged into revisions that are deployed daily. Capability changes that require more work, testing, and approvals can be deployed weekly or monthly
- Automate and streamline as much work as possible, looking for ways to turn it into BAU work, via templates, re-use of assets, and rationalizing unnecessary steps and approvals
- Look for as many places as possible to reduce or eliminate key entry
- Once programs are in production, set up ways to automatically throw alerts when things go wrong or need to be adjusted. For example, if response rates are low trigger a notification that includes key statistics and diagnostic tips
- Use an always-on marketing approach to most customer interactions. In this way, there becomes just one main program: The Next-Best-Action program. That system is simply fed new offers that come and go, but the program itself is evergreen – just on 24x7x365 -always arbitrating for the next-best-action when a customer comes in a channel, and the next-best-touch for outbound outreach.
Although “never say never” applies to nearly anything, it’s unlikely your marketing job will be taken by AI. But another human that knows how to use AI in digital marketing more effectively than you, well that’s another story.
And as modern marketers design the transition and march
toward using technology for increased automation and AI in digital marketing, they
must ensure consumers get what they want – relevant, rewarding, and timely value
exchanges. If marketers relentlessly
automate without seeking continuous feedback from customers on the resulting
experiences, they’ll fail. Great brands
will be those that can think creatively, design effectively, and execute
flawlessly to deliver seamless experiences woven together by machines and
humans. Using this approach, marketers
and their marketing machines will stay gainfully employed.
[i] Rexer Analytics, http://www.rexeranalytics.com/data-science-survey.html, 2017
[ii] Websitepromoter, https://websitepromoter.co.uk/how-to-adapt-your-seo-for-ai, 2019
[iii] Bureau of Labor Statistics, https://www.bls.gov/ooh/management/advertising-promotions-and-marketing-managers.htm, 2019
[iv] Oxford Martin School, https://www.oxfordmartin.ox.ac.uk/publications/view/1314, 2013