Marketing technology has evolved rapidly over the past decade, with one of the most exciting developments being the creation of publicly-available, cost-effective cognitive APIs by companies like Microsoft, IBM, Alphabet, Amazon and others. These APIs make it possible for businesses and organizations to tap into artificial intelligence (AI) and machine learning (ML) technology for both customer-facing solutions as well as internal operations.

According to Statistics MRC, the Machine Learning as a Service (MLaaS) market is expected to grow to 7.6 billion dollars by 2023. The impact AI/ML will have on businesses over the long-term promises to be revolutionary.

Authoring Efficiencies Powered by AI and ML

The current application of AI and ML in content management is more akin to power-assisted steering than a self-driving car. You remain in the driver’s seat, but you now have an enhanced set of tools to deploy.

These tools make it possible to automate routine operational tasks, freeing you and your team up to focus on higher-value, innovative marketing strategies, such as nurturing your audience, growing your business, and tapping your digital channels to create highly-engaged customers and brand advocates.

We’ve identified three specific areas within content marketing that are primed for the application of AI and ML technology: content tagging using classification models, faceted image search using image processing (face and object detection), and chatbot-enabled CMS workflow (natural language processing and speech-to-text).

Auto-Tag Your Digital Content

Organizations invest millions of dollars in staff, software, platforms and more, all in an effort to create valuable content. But historically they haven’t been able to fully tap into the potential of that existing content. Imagine being able to unlock that potential in the hundreds of thousands of web pages, blog posts, case studies and other digital content you have by making them easily searchable and sortable.

Off-the-shelf AI/ML tools can help you enrich your content and make it more accessible. For example, content authors usually spend a great deal of time combing through previous posts and existing taxonomy to ensure the tags they apply to a content item are accurate and in line with the current content structure. Furthermore, with the natural churn that occurs in most businesses and organizations, this experience and knowledge can often get lost as employees leave.

Businesses can train AI/ML on their unique, niche taxonomy by having it sift through thousands of your content items to gain contextual knowledge. It can then auto-tag future posts with a higher accuracy rate, allowing your authoring team to focus on creating more content. With better taxonomy, you can serve up more relevant content to your audiences when they are visiting your websites or other digital properties, further helping to enhance their user journey and customer experience.

An AI/ML investment like this will pay for itself as it continues to learn over time and become a storehouse of institutional knowledge.

Unlock the Value of Your Media Library

If you and your team works with a lot of rich media and a complex media library, then you recognize the need for image auto-tagging. Sorting through thousands of images to find the perfect one to enhance your content can be extremely cumbersome and time-consuming.

The standard image-processing capabilities in today’s AI/ML technologies make it possible to analyze an image and identify colors, objects, people and even their emotional state, gender and estimated age. The right images matched to the right content or campaign can make all the difference in catching your audiences’ attention and increasing engagement.

Let’s take an A/B test that you might want to run on a new promotion, or a personalized hero component on your home page. By nature of their purpose, these kinds of marketing automation tactics require plenty of content variations (including the involved images) to be effective. Now scale this example to cover all the promotions you might be running at any given time or all the personalized components across your site. Identifying the necessary images to serve up across them can become extremely tedious, creating a bottleneck to rolling out new campaigns.

Using an AI/ML-enabled CMS and media library makes finding the perfect images a much quicker process. You can filter images by the different criteria noted above and find what you’re looking for in no time.

Using Chatbots to Streamline Publishing from Any Device

Natural language processing (NLP) has enabled the leader in search engines, Google, to serve up contextual results based on your location and previous search history. It’s now possible to tap into this technology to enhance your CMS and increase the efficiency of your internal operations.

Any mention of voice applications likely conjures up thoughts of Alexa or Siri. However, it’s possible to embed the processing power of this functionality into your CMS, in the form of a modified chatbot, to serve as a concierge for your workflow activities.

You can then use your smartphone to publish an item, for example, simply by talking to the CMS. With mobile-friendly options, you can publish content or move it through workflow on the go, whether you’re at a conference or on a subway commuting to work.

The Value of AI/ML for Businesses

AI and ML are poised to revolutionize content marketing operations. By investing in these powerful technologies, you can expect to free up people’s valuable time, allowing them to focus on more strategic work. At some point soon, the conversation will stop revolving around whether you should use these technologies and will be about whether you were an early or late-adopter and what the resulting impact is to your business.

Since machine learning at its core is about learning, the sooner you can embed it into your internal process, the more time the technology will have to become proficient in your specific business operations. Additionally, your team will gain expertise on how best to use the tools to enhance their productivity and can use the time saved to invest in better marketing strategies, putting you at a great advantage over your competitors.

An often-overlooked side benefit is an increase in employee engagement, who will feel like they are contributing to exciting, innovative, higher-value work, rather than performing routine, repetitive daily tasks. An investment in AI/ML for content marketing operations has the potential to pay for itself many times over, essentially making adoption of the technology a win on many fronts.

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Some call it the core of the martech stack, others simply an important component. Where ever it sits in your stack, your web content management system will go through some major changes in the next few years. And most of them are related to artificial intelligence (AI).

It’s a favourite topic among marketers but mainly because they still aren’t sure how AI will improve the way they interact and convert customers.

Figuring out where AI is needed most

Ready or not, AI is here, and it’s slowly working its way into web content management. I spoke with Jan Haderka, CTO of Magnolia CMS, about the ways his team is leveraging AI to help Magnolia customers create better digital experiences.

Haderka said he’s been watching the hype curve for AI for a while and at Magnolia, they are always trying to understand where new trends (like AI and IoT) fit in the CMS. He talked about the time they built an IoT game with a partner and a client. When using public transportation, you would search for beacons. A global scoreboard let you see how you were doing and people could win prizes and have fun.

They look at AI similarly, trying to find ways to incorporate it and improve experiences. Haderka acknowledged that as a smaller vendor in the CMS space they can’t do everything, so they have to be smart about the changes they make, where things can lead and what it means for their audience.

Magnolia CMS is an open CMS. Serving as a hub, it takes data in from many sources, transforms it, combines it with other data and pushes it out to many channels. Haderka had to figure out how AI would help with this model.

Oh, the things we can do with AI

Image tagging was one way. You can upload an image and get suggestions for tags. Take it a step further and then use AI to relate that image with content residing in Magnolia and provide “related” or “recommended” content to the content author/editor. He talked about a demo they did where they were mining content for tags and sentiment as it was being written and providing insights on how that content would be perceived. It’s about helping Magnolia customers build a better experience for their customers.

Personalization is another key reason to leverage AI in the CMS. The manual approach of defining audiences and creating separate content and journeys for each audience in the web experience is often either too simplistic to make a difference or too complex to manage and scale. Plus, a person doesn’t necessarily fit into only one audience or segment, or they move in and out of a segment depending on different attributes (such as time of year). AI resolves this problem by automating much of the work.

Haderka said you can use AI and machine learning to automatically analyze how audiences are interacting with content and provide feedback on the performance of those interactions. It can help you understand if your audiences are working or if there are different segments or smaller groups you should focus on to deliver improved personalization and recommendations. It’s here that Haderka believes CMS vendors like Magnolia need to focus their efforts going forward.

It’s not just about one AI – but multiple AIs purpose-trained for specific tasks. This is why content management systems need to support an open architecture that enables them to integrate and plug in different types of AI at different places in the CMS to analyze content and provide the needed functionality.

Another area where AI benefits the CMS is with testing. You can feed analytics back into the CMS, and the AI can analyze the data to adjust experiences automatically. So, for example, if a certain audience is not reacting as expected to a certain personalization approach, the CMS can automatically change what that audience is seeing. In this case, the AI is continually testing and observing and improving the experience.

Integration, iteration key to successful AI

Your Web CMS may not have all these capabilities built in. Like Magnolia, you may need to integrate with many tools, connect them and feed the parameters to the AI, training it to work a certain way. It does take work. As Haderka said, the mechanisms are there to improve the system, but it’s still more work than training humans to analyze and make changes. In both cases, however, it takes time.

A key benefit of AI is that you can have multiple versions; one running live while you are training another one. So you always have some level of personalization working at any time. As Haderka pointed out, the frameworks are continually improving.

As for the CMS industry overall, Haderka said it’s a great time. He said AI is forcing customers to innovate. The biggest problem with innovation is that you will fail a lot before you succeed. But by allowing you to fail fast, you can cover the cost of the trials and get to success faster.

My take

Every web content management system will have some AI built-in in the next few years. It will revolve around improving the experience either by refining audiences or improving personalization.

But should everyone be leveraging AI and personalizing experiences? Is it more a B2C thing? Not so much said Haderka. It’s about the different types and sizes of your audiences. The more segmented your audience is, the more differences there are in terms of needs and demands. The bigger your audience is the more work required to personalize the experience.

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