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Will Machine Learning Change the Landscape of Content Marketing?

If you’re in B2B marketing and HAVEN’T heard the buzz around AI-driven tools like ChatGPT, you should probably just quit your job now.


Okay, maybe that’s a little harsh. But there’s quite a bit of buzz around the block about how machine learning is set to revolutionize the industry. Is it all hype—or is there truly something to this technology?


In this post, we'll take a deep dive into how machine learning and AI are changing the landscape of content marketing and what it means for you as a marketer.


AI for more personalized, relevant content

One of the most exciting ways machine learning is impacting content marketing is through the ability to create more personalized content. By analyzing user data such as browsing history, search queries, and demographics, machine learning algorithms can understand the interests and preferences of individual users.


With this information in hand, AI can then create customized content that is tailored to each user's interests and preferences. For example, it can suggest personalized headlines, images, and calls to action based on the user's interests, making sure your content is always on point.


AI can also use natural language processing (NLP) to generate personalized emails, chatbot responses and other forms of content that adapt to the user's language and tone. This will make your audience feel like you're speaking directly to them, increasing engagement and conversions.



“The more you know about your customers, the more you can provide to them information that is increasingly useful, relevant, and persuasive.”

With machine learning, you can move away from generic content and create something truly tailored to your audience.


Customers personalize content with Salesforce AI

One example of a B2B company that's using AI for content personalization is Salesforce. Salesforce is a customer relationship management (CRM) software company that uses AI to personalize the content and experiences for their customers.


Salesforce’s Marketing Cloud Personalization, for example, uses AI for…just about everything, including:


  • Understanding customer affinities in real time to personalize experiences and increase conversion rates.

  • Saving time with AI-driven content, offers, and recommendations that shorten the path to conversion.

  • Reducing costs by understanding what’s working and what’s not with automated A/B/n testing.

  • Reducing churn and growing customer value with connected customer journeys that get smarter with every interaction.


One way you can use AI to personalize your content with Salesforce is optimizing your website experience for each customer. AI algorithms analyze customer behavior, such as pages visited, products viewed and time spent on the website, to provide personalized product recommendations and content.


Improved segmentation and targeting with machine learning and AI

But personalization is just the tip of the iceberg.


Machine learning can also help you improve your segmentation and targeting efforts. By analyzing data and identifying patterns, you can pinpoint the most effective channels, platforms, and formats for reaching your target audience.


For example, AI can analyze past campaigns and determine which platforms and channels led to the most engagement and conversions, and which ones didn't perform as well. This can help you make informed decisions about where to distribute your content and increase the chances of reaching your target audience.


“You have to have a dependency on AI to turn the data into insights at the speed it needs to turn so you can make decisions and activate in near-real time.”

With machine learning, you can stop guessing and start making more strategic decisions about your content distribution.


Adobe uses AI to help customers do better targeting

Adobe offers a great example of a company using AI for better content targeting.


One way they use AI is through Adobe Target, which uses machine learning to analyze customer data and behavior. This data is then used to segment the audience and deliver personalized content, offers and recommendations to each customer. This allows Adobe to create more relevant and engaging content for their customers, which results in better targeting and increased conversions.


Another way Adobe uses AI is through their Adobe Advertising Cloud which uses machine learning algorithms to optimize and automate the ad targeting, enabling them to reach the right customers with the right message, at the right time. This improves the targeting efforts by using data and insights to deliver the most relevant ads to the right audience.


Predictive analysis through artificial intelligence

AI can also be used for predictive analysis.


By analyzing past performance data, you can predict future trends and identify opportunities in the market before your competitors do. This gives you a major advantage in the ever-changing world of content marketing.


“The great thing about AI is that it can predict and learn in real time what the audience is going to be receptive to...[so we can] create a great value exchange between the brand and consumer in ways we weren’t able to do before.”

AI allows you to stay ahead of the curve and make strategic decisions for your content marketing strategy.


IBM offers AI-powered predictive analytics

IBM is a multinational technology company that uses AI-driven predictive analytics in their content marketing through their various Watson platform offerings, such as IBM Watson Marketing and IBM Watson Advertising.


The platforms use natural language processing and machine learning algorithms to analyze data from different sources, such as customer interactions, website analytics, and social media, to predict which types of content will perform best for whom.


IBM uses this data to create more effective content strategies, by identifying the topics and formats that resonate most with their target audience, and optimizing the distribution channels, such as social media, email campaigns, website content and advertising, to reach the right audience at the right time.


Automated content creation with AI

Despite the fact that many B2B marketers have been using AI tools to power their marketing for years, automated content creation is getting the most industry buzz. The recent rise of tools like ChatGPT, Writesonic and Jasper has marketers wondering whether they should be using AI for blog writing, email writing, copywriting…you get the idea.


Machine learning and AI tools can be used to automate the creation of certain types of content such as news summaries, product descriptions, and social media posts. This allows you to create more content in less time and free up resources for more strategic activities.


ChatGPT isn’t the only AI writing tool

While ChatGPT may be getting the lionshare of marketers’ attention, tools like Writesonic and Jasper also use AI and natural language processing (NLP) to generate automated content. They work by analyzing large amounts of data and identifying patterns in language, grammar, and style. The algorithms then use this information to generate new content that is similar in tone and style to existing content.


For example, Writesonic uses AI-powered algorithms to analyze a brand's existing content, such as website copy, blog posts, and social media updates, to understand the brand's tone, style, and messaging. It then uses this information to generate new content, such as product descriptions, social media updates, and email campaigns, that align with the brand's voice and style.


Similarly, Jasper uses natural language generation (NLG) technology to analyze data and generate automated content. The tool can generate reports, summaries, and other types of content, such as social media posts and email campaigns, by analyzing data from different sources and identifying patterns.


Both tools can save time and resources for businesses by automating the time-consuming content creation process. However, it's important to note that AI-generated content should always be reviewed and edited by humans, to ensure that it is accurate, relevant and appropriate for the target audience.


The future of content marketing

While all of these benefits of machine learning are exciting, you may be wondering if it will eventually make your job redundant. The short answer is no. Machines can automate certain tasks, but they can't replace the human touch.


They can't come up with creative ideas that will set you apart from the competition.


Or tell a unique and compelling story.


They can't form relationships with influencers or engage with your audience on social media.



“Marketing is no longer about the stuff you make but about the stories you tell.”

But will machine learning change the landscape of content marketing?


It already has.


From creating personalized content to improving targeting efforts, predictive analysis and automating content creation, B2B marketers are already using the technology to create more effective and efficient content campaigns. AI writing may be the newest guy on the content block, he’s not the first newbie (and he probably won’t be the last).


And we should probably find a way for him to fit in.



“The playing field is poised to become a lot more competitive, and businesses that don’t deploy AI and data to help them innovate in everything they do will be at a disadvantage.”

As the industry evolves, it's important to stay informed about the latest developments in AI/machine learning and how they can be applied to your content marketing strategy. By embracing this technology and finding the right balance between automation and the human touch, you can stay ahead of the curve and achieve better results for your business.


In the end, the future of content marketing belongs to those who can tell stories in a way that is human and authentic, using the technology to enhance their efforts, not replace it. As machine learning continues to advance, the opportunities for B2B content marketers are endless, and it's up to you to decide how to use it to achieve better results.



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