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The Rise of Content Intelligence in the AI Era

Speed & Personalization has become a cornerstone of marketing. Every marketer knows that without it, your chances of capturing a customer’s attention – and their dollars – are significantly reduced. But, personalization done well is not simply a matter of referring to someone by name in an email – marketers also must take into account that person’s preferences, their habits, and the context in order to craft a holistic experience that will pique a user’s interest.

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To put it simply: effective personalization requires effective content intelligence – understanding how content is being used and how it is performing across regions, channels, and campaigns. By utilizing AI and machine learning, along with graph technologies,  brands will be better equipped to identify the stories (digital assets) that will resonate with each consumer, and therefore better able to build lasting connections and drive engagement.

Work smarter, not harder

At its core, content intelligence is a very simple concept: it’s the insights that enable you to produce better content, and to leverage that content more effectively to connect with customers. All too often, brands are spending tens of millions of dollars to produce content  they then try to shoehorn in to match with user preferences. Instead, marketers need to think about how they can take what they know about the customer to craft content that is truly aligned with their interests.

The key to doing so effectively lies in data. After all, the only way to know what appeals to a person is to see what has connected with them in the past – and what hasn’t. But it’s not enough to know that Person A has connected with an ad using one particular asset while Person B preferred another. How well an ad performs is dependent on more than just the creative – how and when it’s being delivered also plays a vital role in determining a user’s response. At the same time, marketers need help getting to these insights – and that’s where the use of artificial intelligence comes in.

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AI: four ways to get ahead

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Without artificial intelligence and machine learning, content intelligence would be impossible to achieve. Advanced AI capabilities are what enable marketers to deliver personalized content at scale. There are four areas where AI provides significant value: content identification, content creation, media buying and content optimization.

On the face of it, content identification may seem like a fairly minor function. But as any marketer will tell you, without a proper system for image tagging, finding the perfect asset is a near-herculean task. Advanced AI can auto-tag images and videos, thus making them easier to find and organize. This allows marketers to spend less time on the administrative side, and  build out and execute campaigns quicker.

When it comes to content creation, AI offers several important benefits. First, as with content identification, it can be used to automate tedious, grunt-level work – thus freeing creatives up to do the job they signed up for in the first place. Secondly, it can be used to make predictions about which types of content will perform better for a particular audience or individual, which in turn gives marketers a better sense of the types of messaging and assets they should employ. These same predictive abilities are especially valuable for media buying, as by analyzing consumer data, AI-powered models are capable of making forecasts about which ad placements will lead to the greatest return.

But it’s personalization where AI really shows its power. AI enables marketers to go beyond A/B testing, and instead model near infinite variations to see which will perform best amongst various audience segments. Itt gives marketers the ability to deliver campaigns that take into account an individual’s likes, dislikes, habits, and so on, and can be automatically adjusted in near-real time to optimize performance – in other words, the ability to deliver campaigns that are truly personalized, and truly intelligent.

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A better way to tell stories

The question that brands have to answer is, how do you identify those storytelling beats that will elicit that deeper response? Equally importantly, how can you structure your content creation and delivery system to ensure that those stories remain front and center throughout the entire marketing process?

Marketers now have access to technology that will enable them to understand their customers better than before. But those insights have to be top-of-mind throughout the whole storytelling lifecycle – or else you’re just deciding which of your existing assets will work best in a given situation, and not crafting content that is aligned with the customer themselves.

Brands have to think beyond the asset. The asset is important, yes, but it’s just one aspect of the storytelling lifecycle. A person chooses to engage with an ad not because they like how it looks, but because it tells a story that connects with them on a more personal level. Without content intelligence, brands will always be one step behind.

[To share your insights with us, please write to sghosh@martechseries.com]

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