AI and IA: How artificially intelligent automation is driving scalable marketing
What happens when you combine marketing automation and artificial intelligence? Contributor Andy Betts delves into the topic and explores what's ahead.
Talent is a major concern for organizational leaders, given that labor costs and services together now account for a whopping 53 percent of total marketing budgets (Gartner). But even as companies struggle to find humans to manage their newly implemented technologies, many CMOs have yet to define exactly how Artificial Intelligence and Intelligent Automation are meant to transform their business models and processes in the first place.
We’ve talked at length in previous columns about the benefits of finding that synergy between talent and martech, and bridging the talent gap that’s holding up more widespread adoption of machine learning. In this column, we’ll peer through the other side of the looking glass, at the technology profoundly impacting modern marketing employees and how to deploy it at scale.
Understanding the role of AI in IA
We’ve tended to think of technology, particularly software, in terms of automation until very recently, but taking a legacy approach to new tech can only result in lackluster performance.
Automation is a task-driven imperative with a sole purpose: to get machines to do the repetitive tasks we creative, free-thinking humans don’t want or really need to do. Automation performs calculations for us. It improves communication. It runs machinery, assembles product, steers vehicles and more.
Advances in machine learning, natural language processing and other areas of computing are being spurred on by a veritable explosion of data, more than human teams could ever activate. Intelligent automation combines the efficiency-finding, time-saving benefits of straight automation with elements of AI — gathering input, analyzing data, and even making decisions.
Take support requests, for example. Automation can make this traditionally labor-intensive task more manageable by automatically completing predictable, repeatable tasks according to a defined set of rules: autoresponding, flagging for specific departments, applying a priority, designating a status or notifying administrators.
Artificial intelligence adds a critical layer of understanding, a typically human trait. Natural language processing can enable the software to “read” support tickets and make decisions about prioritization, or even respond intelligently to resolve a ticket.
Intelligent automation improves scalability exponentially, while driving customer satisfaction, employee performance and business results. Recent research from KPMG shows that digital-first companies like Amazon have a distinct advantage when it comes to IA, but that shouldn’t hold your organization back. All companies have the opportunity today to evaluate (or re-evaluate) technologies through the lens of business model opportunities and constraints.
Deploying Intelligent Automation in martech
The long, bumpy road of manual marketing processes is receding in the rear-view now, as we hurtle at breakneck speed onto a wide-open freeway of AI-enabled possibility. Here’s what automation in various marketing practices and channels looks like today, and what we’ll see in the not-so-far-off-future.
Automation is the very foundation of email marketing, enabling us to manage more contacts and send a greater volume of email than we’re likely to achieve on our own. We can schedule emails to send at a particular time, create and manage templates and send customized messaging to buckets of subscribers based on the insights we’ve gathered about them.
More intelligent automation will take that personalization to its most granular level — to the individual. Our tech will analyze each subscriber’s email habits to determine the optimal time to send our emails to each person. We’ll be able to target promotions based on each individual’s search and transaction history, as gathered from any number of sources. AI-powered IA will even perform A/B tests and make decisions about subject lines, visuals and calls to action.
Artificial intelligence isn’t new to ad targeting, but GDPR may have an impact on how it develops in the future. Despite that, we’re already finding that CLV (customer lifetime value) is old news. Networks and ad exchanges are now measuring CFV (customer future value), based on predictive analytics that then drives placement recommendations.
Automation gave rise to the programmatic ad industry by automating the process of buying and selling. Now, artificial intelligence is being added to the mix to analyze both first- and third-party data, then make campaign optimization decisions to improve performance. IA will be critical in coming years in managing the massive amount of data available from multiple inputs and across various devices and networks.
It’s going to take a great deal of content to fuel all of this personalization and targeted outreach. As marketing communications become ever-more granular, humans simply won’t be able to keep up with the messaging required to fuel the machines. Imagine the hit your ROI would take if half a page a copy resulted in only two email opens, as it only applied to two prospects?
Perhaps the most controversial aspect of IA on the horizon is the very real prospect that machines will create content. We’re comfortable using automation to distribute, promote and measure content performance. But can humans let go of the wheel and let our technology actually do the creative work of writing an email or a landing page? The answer is yes. According to BrightEdge, over 60 percent of marketers intend to use artificial intelligence (AI) to develop content marketing strategies. Machine learning will be able to create, test, optimize and recreate content personalized for each interaction, based not only on more data points than we could ever hope to wade through, but also on real-time cues from users.
Social media marketing
Outside of the massive potential of social ad targeting, IA will power deeper and more meaningful brand-consumer relationships than ever before. It will be able to analyze content interaction and write social content based on those insights, to share out the most enticing, engaging snippets from each piece. It will determine not only when users are online, but when they’re most likely to be receptive to brand messaging.
IA will quickly and more accurately find and engage influencers, capitalize on real-time interactions and optimize content for sharing. As social listening is increasingly automated, our martech will make smarter decisions about which interactions and input should be distributed internally, enabling brands to make more informed business decisions.
Search engine optimization
While some aspects of SEO are currently automated, it’s still a fairly labor-intensive process requiring human creativity and ongoing management. IA will build on currently automated processes by making recommendations for optimizations and eventually, going ahead and making those optimizations. Imagine meta descriptions that optimize as rankings shift, or image alt text that is written based on the algorithm’s understanding of every other similar image on the internet.
SEO audits are so cumbersome today that many companies never bother with them. But soon they will happen regularly as a background process. New site builds will apply optimizations based on real-time data, rather than best practices and months-old recommendations. Google and other search rankings are dynamic and constantly shifting. In the near future, intelligent SEO software will analyze masses of data, make optimization decisions and measure results, too.
Human + artificial intelligence = Better together
Having the right talent was the single most important factor for driving organizational growth, according to 35.3 percent of CMOs in Deloitte’s 2018 CMO Survey. Technology and data were the primary concerns for 20.8 percent of respondents. It’s fair to say that all three are weighing heavily on CMOs’ minds.
As AI proliferates and automated martech becomes more and more intelligent, we’re going to see our technologies learning from experience and making better decisions. The most successful CMOs will be looking to IA not only to facilitate processes and create efficiencies but also to drive the digital transformation that will keep their company on the leading edge.