How Marketing Automation Will Use AI
If machine learning leverages data to provide insights, then marketing automation AI will take that data and help create superior segmentation actions and prescriptive suggestions. Machine learning is where smart database marketing becomes a reality.
No more missed correlations and opportunities from supposed marketing analyst unicorns. Yes indeed, welcome to the machine. However, even the machine is not a unicorn. It requires human input to learn and evolve the machine learning system of algorithms so they can function well as a tool for the marketing department.
In data science, this is called supervised learning, where human input and training algorithms coach the machine learning system on the validity of its output. In marketing, this should be considered the good process, ensuring that machine learning receives the guidance it needs to adapt to your business and its unique needs.
While supervised learning is always ongoing, a well-trained series of machine learning algorithms will better identify common points of interest amongst customers than a human analyst will. Marketing data elements leveraged by AI include traditional demographics, geographic, psychographics, past purchasing behavior, and customer content consumption patterns (their history on social networks, email and on your website).
The resulting segmentation can create smaller more precise lists. Marketo, Pardot, and other traditional marketing automation platforms are bolting on AI and evolving their platforms to provide this kind of functionality. They promise new capabilities, including:
Optimized subject lines and copy
Product recommendations and offers
Recommended send times
Segmentation for outbound communications based on time zone
Streamlined automated drip campaign builds
Automatic landing page generation and optimization
Marketo and Pardot already announced and are deploying their first AI branded solutions. Some marketing automation vendors are even promising the holy grail of digital marketing since the 1990s, the oft-promised but never delivered one-to-one personalized marketing communications.
Marketing Automation Players Burdened by Legacy
In many ways, the marketing automation vendors are late to the machine learning dance. While one can argue they have always had some form of machine learning in place, it has been primitive compared to other technologies developed by brands that are not solely focused on email marketing.
Large brands like Amazon have already created their own AI to deliver product recommendations, content recommendations, product delivery optimization, and much more. Amazon has made a conscious effort to integrate machine learning principles into the company’s culture.
Their recommendation engines and general ability to comprehend a customer’s potential purchase fuel one of the world’s most valuable brands. Also, like most technological things Amazon, Amazon Web Services resells its machine learning software and data science software to developers, data scientists, and other interested parties.
Advanced marketing automation brands want to bring some of those tools to the enterprise and eventually small business, particularly those that have no or little machine learning in their DNA. One way to look at the growing marketing automation AI trend is to look at it as a democratization tool for businesses. Marketing automation systems can provide an ASP model to those wouldn’t be able to create their machine learning systems.
However, legacy marketing automation systems may prove a hindrance for the established brands compared to next generation AI-based marketing systems that are rising to compete against them. Traditional marketing automation leveraged email and databases to create supercharged digital communications that scaled beyond human capability. Marketing automation logic is inherently human and fails to comprehend the customer’s larger omnichannel universe.
For example, if you have all of this data in one place, it would seem like a natural extension to extend this kind of intelligence and content into your online advertising buy with an omnichannel integrated campaign. Most automation systems fail to address advertising beyond a cursory integration into AdWords or Facebook Pixels.
After all, the same person will view these online ads and want to come to your website, at least in a world governed by marketing unicorn theory. Such integrated capabilities may include:
Targeted online advertising buys
Geo-based and retargeting efforts
Recommendations on which media to invest in and which to avoid
Extending optimized content into larger advertising campaigns
Modern marketing automation will look to integrate more aspects of customer interactions. Indeed the value is the intelligence gleaned from analyzing vast amounts of customer data to better segment and understand customers.
It would not merely revolve around email, instead of looking at which customers to interact with, and the content that drives customer conversion across the entire lifecycle. The tactical delivery of such material is the final execution of well-developed marketing strategies.
Marketing Automation AI — Beyond the Channel
I believe the real value of marketing automation AI is understanding and personalizing content and message strategy to meet the customer profile. However, much of the logic driving marketing automation AI focuses on optimization techniques for each channel.
The actual execution of those communications through email or advertising is where creative, social, advertising and traditional marketing automation benefit from machine learning-driven data analysis. Optimization and recommendations will answer questions like:
What’s the best headline?
What’s the best time for delivery?
What are the key terms and issues that will trigger buyers in this segment?
Which types of media work best?
What colors work?
Which variant of the campaign works best and why?
Marketing automation AI will answer these questions particularly in the realm of email campaigns, and their associated pieces, including landing pages, calls to action, and premium content that drives customers through the email chain and onto the website. However, advanced systems will also move into the domain of Google, Facebook, and other online platforms to begin optimizing advertising and social media communications, too.
On and on. Marketing automation AI will help marketers master the battle of inches, incremental boosts that yield more substantial single and double-digit percentage increases in customers. When we stop thinking of the channel, whether that’s marketing automation’s home turf of email or other channels and start thinking of the overall customer journey impact, marketers will have made a significant step forward from the tactical to the strategic.
“Why can’t the experience be channel-less?” asked Niraj Ranjan Rout, Founder of Hiver, an email collaboration tool, here on Medium. “Marketing automation with AI allows you to enhance customer satisfaction around the experience, not the channel. A customer’s appreciation is based on how responsive you are to their needs, and the channel doesn’t matter.”
Indeed, holistic marketing experience is often discussed by senior marketing executives but rarely achieved. Marketers get lost in the tactical execution of campaigns.