{"id":5138,"date":"2024-11-06T18:50:17","date_gmt":"2024-11-06T23:50:17","guid":{"rendered":"https:\/\/beomniscient.com\/?p=5138"},"modified":"2026-04-14T18:01:43","modified_gmt":"2026-04-14T22:01:43","slug":"ai-driven-personalization-content-experiences","status":"publish","type":"post","link":"https:\/\/beomniscient.com\/blog\/ai-driven-personalization-content-experiences\/","title":{"rendered":"How to Build AI-Driven Personalization for Content Experiences"},"content":{"rendered":"\n

The biggest conundrum in today\u2019s marketing world is that most companies don\u2019t know exactly what their customers want. Customers only want to interact with companies that understand their pain points and can provide them with personalized experiences.
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But here\u2019s the good news: You can now rely on artificial intelligence (AI) to tell you about your customers\u2019 wants and wishes (i.e., through the help of AI-powered social listening tools) and can leverage AI to build personalized content experiences<\/a>.<\/p>\n\n\n\n

Let\u2019s explore AI-driven content personalization, how it works, and how to personalize content experiences using AI.<\/p>\n\n\n\n

What is AI content personalization?<\/h2>\n\n\n\n

John Porrini<\/a>, the content marketing manager at Copysmith\u2014the parent company of AI-powered software like Frase (an AI-powered content optimization tool), Describely (an AI-led content creator for eCommerce businesses), and Rytr (an AI-writing assistant)\u2014says:<\/p>\n\n\n\n

\u201cTo me, AI content personalization is somewhat uncharted territory. I believe that as AI becomes more advanced, we\u2019ll reach a point when every piece of content can be hyper-personalized based on your customer data, preferences, and where you are in the buying journey.<\/em><\/p>\n\n\n\n

We\u2019re talking web pages, blog posts, social posts, ads, emails, videos, etc., all dynamically personalized to the buyer based on their data. Marketers will be sitting behind the scenes managing and tweaking these personalized AI automations that are running.<\/em><\/p>\n\n\n\n

We can already dynamically change content based on UTMs and other data points, so it\u2019s not that crazy to think that AI will be doing this at a far more personalized scale. Some of this is already starting to happen; just look at what Intercom is doing with integrating AI in the support process<\/a>.\u201d<\/em><\/p>\n\n\n\n

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Major companies like Netflix and Spotify also use AI\u2014albeit to provide hyper-personalized recommendations and not customer support. For example, Netflix provides content recommendations based on \u201cmatch score.\u201d This match score is assigned based on previous watch history and content preferences in a user\u2019s watchlist.
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In the near future, John imagines AI might not be an accessory for powerful companies like Netflix. Still, many AI-powered tools would be available to small and medium businesses so they can personalize their content experiences as well.<\/p>\n\n\n\n

Understanding how AI content personalization works<\/h2>\n\n\n\n

AI is a tool developed and refined by AI development companies<\/a> that is fed millions upon millions of data points. This user data is processed, analyzed, and summarized to deliver insights and responses tailored to individual queries. <\/p>\n\n\n\n

Organizations running a data readiness assessment<\/a> can identify gaps in their data quality, governance, and infrastructure before attempting to scale AI personalization efforts.<\/p>\n\n\n\n

For example, if we were to write a query like \u201cHow to make pesto pasta\u201d on Bing, its AI-powered tool, Co-Pilot, will immediately produce an answer based on the information it has, with no need to scroll through multiple articles and videos to find the answer you need.<\/p>\n\n\n\n

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Where AI works best for content personalization<\/h2>\n\n\n\n

The instance above is just one example. The right artificial intelligence tools<\/a> will also be adaptable and account for real-time data to provide the necessary experiences for your personalization strategy.<\/p>\n\n\n\n

For example, as John said, AI tools<\/a> will account for user demographics and customer preferences, purchase history, and past customer interactions before providing you with an answer.<\/p>\n\n\n\n

In the future, this might look like an AI chatbot<\/a> that provides an omnichannel experience, has information on your past purchases and customer support interactions, and provides answers, keeping all that data in mind. Leading tech providers are developing conversational AI for cust<\/a>o<\/a>mer support<\/a> that can seamlessly integrate this historical context into every interaction.<\/p>\n\n\n\n

Additionally, call monitoring software enhanced with AI capabilities can analyze customer conversations in real-time, identifying emotional cues and common issues that can further inform your content personalization strategy across all channels. Tools like AI voice call agents<\/a> can also support this by handling real-time interactions more efficiently.<\/p>\n\n\n\n

How to personalize content experiences using AI<\/h2>\n\n\n\n

While the way you use AI technology to personalize content preferences will differ based on the content formats you choose and your goals, here\u2019s a few guidelines you could adapt to personalize user experiences using AI.<\/p>\n\n\n\n

Understand your content marketing goals<\/h3>\n\n\n\n

The first step in the process is to identify how to use AI to achieve your marketing goals. For example, you could use AI for either of the possible scenarios:<\/p>\n\n\n\n