Machine Learning and AI for Content Marketing Automation

Current Shifts: Machine Learning & Content Automation

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Rapid advancements in machine learning are creating a whole new set of content marketing tools for producing and delivering hyper-personalized content at scale. In view of the accelerated speed at which the machine learning and content automation markets are set to grow over the next 3-5 years, we expect brands and agencies who don’t use them may be left behind.

Clearly, users prefer to receive tailored content when it is helpful and relevant to their immediate needs. Digital marketers who can deliver content at the right time will easily outrank their competitors. Content marketing automation tools make this possible.

The Machine Learning Behind Content Automation

Machine learning is an offshoot of AI, in which the computer, rather than the programmer, develops and refines algorithms using a brain-like neural network. Only this one isn’t limited by data volume. It uses a technology called natural language understanding (NLU) to segment, connect, and even understand massive amounts of unstructured data. Using natural language generation (NLG) it intelligently communicates data back in a very human-sounding way and in a tone and style designed to resonate with the unique individual being targeted.

All of the major AI companies (Google, Apple, Amazon, etc.) have been heavily investing in machine learning technologies, so every day new data new patterns and connections are made. As these learnings build upon the previous ones, big data is bringing machine intelligence to a tipping point so machine intelligence is growing exponentially.

Current and Emerging Content Marketing Technologies

Over the past few years we have seen machine learning technology advance and combine with other new technologies (like computer vision, speech and voice recognition, etc.) to develop highly predictive and personalized content in various forms. These include personalized search results, customized ad placements (with auto-generated imagery), and user-specific videos. News agencies, financial firms, and similar fact-based industries are now using it to automate content faster and more accurately than any human could.

Here are some ways machine learning is combining NLG and NLU to make content marketing more efficient and targeted:

  • Content ideation and curation—identifying the types of content the user is most likely to engage with and make recommendations for what content to create next.
  • Content strategy—automating the timing and sequence of delivery based on the user.
  • Content optimization—showing which headlines, voice, tone, and style will resonate with the intended user.
  • Content generators—creating titles, subject lines, and descriptions.
  • Content updating—automatically updating content with up-to-the-minute stats and data.
  • Customized reporting—automatically creating content containing user-specific data reports in the vernacular and tone most likely to engage.

Other Machine Learning Technologies to Fuel Content Marketing

As AI integrates with learnings from the Internet of Things, digital marketers will have the capacity to track and record a single user across all touchpoints; both online and offline. With machine learning growing exponentially, we will soon have the intelligence needed to automate fine-tuned content for each one. IBM predicts by 2020, “85% of all customer interactions will be handled without a human agent.” This will be done with a level of responsiveness, accuracy, and efficiency not humanly possible; and at a fraction of the cost.

At present, here are a few of the machine learning technologies at play, which also intersect with content marketing—all of which we expect to rapidly grow and evolve:

  • Chatbots—Automatically generated content powered by AI and creative content combined.
  • Computer vision—Visual recognition software that can link personal data with in-person imagery to make personal recommendations online.
  • Augmented reality—Shopping apps that can also be leveraged to tell stories and compel users to take action.
  • Voice recognition—Speech activated technology that can be embraced by brands to engage and interact with users.

What’s Ahead for Content Marketing

With these and other content marketing tools becoming increasingly utilized, we anticipate a realignment of digital marketing roles to take place in the not-too-distant future. Demographic profiling will be replaced with a focus on behaviour, intentionality, and next-step predictions. Ultimately, AI-driven marketing strategies will become so hyper-focused personas and customer journeys will be done away with altogether. Instead, interactive end-to-end communications will be customized to the individual user.

How will this impact the job of the content marketer? As with other industries being disrupted by AI, it will simply mean an exchange of mundane, repetitive, and tedious tasks for those requiring a great deal more creativity and ingenuity. New technologies will provide new opportunities for expression and strategy. And quality, distinctive content will be of ultimate value.

We see AI as a good thing. As it progresses, content marketing will just become more fun.


‘Current Shifts’ are developing trends in technology and digital marketing that we’re monitoring. Join us for more discussions as we identify, research and provide insight on current and upcoming topics across the digital landscape. Watch for our ongoing posts here.

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