Why You Should Use Hyper-Personalization in Content Marketing

When thinking about artificial intelligence (AI), content marketing probably isn’t exactly the first industry that comes to mind, but it stands to greatly benefit from this exciting new technology. A rapidly increasing interest in AI has contributed to its adoption in many industries, including digital marketing.

In a recent State of Marketing report, Salesforce found that digital marketers are embracing the AI revolution: 51% of them said they used AI in their campaigns in some capacity, and 27% more planned to do the same.

Marketing Leaders who use AI

Why You Should Use AI in Marketing

Clearly, digital marketing is undergoing an AI revolution, but why is this new technology being adopted so quickly?

While digital marketers have different reasons for using AI in their campaigns, one of the most important ones is personalization. According to the aforementioned Salesforce report, marketers already using AI have stated it’s helping them deliver more targeted campaigns and smarter personalization.

Without a doubt, personalization is one of the most important parts of a well-performing marketing strategy. A compilation of personalization stats from Campaign Monitor stated the following:

  • Campaigns that provide a personalized experience generate an average increase of 20% in sales.
  • Segmented campaigns produce and increase in revenue of up to 760%.
  • Emails that are personalized beyond the recipient’s name deliver transaction rates that are 6 times higher.

However, it isn’t exactly easy to get personalization right and take advantage of these benefits. In fact, 68% of marketers say that data-driven personalization is “the most difficult online tactic to execute.”

Most difficult tactics to execute in digital marketing strategy

Source: 2019 Digital Marketing Strategies Survey by Ascend2

Another study completed by Forrester found that 40% of digital marketers even struggled with traditional personalization!

AI may be exactly the right tool for helping digital marketers ease the implementation of data-driven personalization. Earlier, experts practiced traditional personalization in content marketing and developed more advanced ways to customize a buyer journey, including content marketing personas.

The main idea behind a content marketing persona is creating a composite sketch of ideal customer-based validated features—rather than assumptions—that would inform a content strategy to drive productive customer engagement.

Content personas (aka customer profiles) typically include this information about customers: age, income, workplace, position, personal and professional goals, family status, and interests.

A UX content strategist at The Word Point stated, “Personas also include such advanced factors as content language. English isn’t the only language out there, and might not be the only one spoken by your customers. So content planning should be adjusted accordingly, to meet their preferences.”

In 2018, content personas weren’t as effective as businesses needed them to be, so an upgrade is now required.

Hyper-Personalization in Marketing

Now you can personalize content through a vast amount of user signals and details that are analyzed and applied by intelligent machines—not just through profiles, personas, and data that customers provide when they sign up for your newsletter.

In other words, a new level of personalization now exists. And ironically, since it’s powered by AI, it can help digital marketers create “more human” content and build more authentic relationships with customers and prospects.

The Difference between Personalization and Hyper-Personalization

Still not quite understanding what hyper-personalization is? Clarifying the difference between these two strategies will help:

Personalization is the practice of incorporating personal and transactional customer information (such as the name, purchasing behavior, and workplace) into the communication between a business and a customer.

Meanwhile, hyper-personalization takes this practice one step further, and uses behavioral and real-time customer data to produce highly contextual and relevant communication with the customer.

For example, this email from Hubspot contains a recipient’s name in the subject line and the text, and clearly describes the benefits of the service to them. To ensure relevance, the offer is based on the data the recipient gave via the business’ website. So it’s certainly a good example of personalization.

HubSpot Email

The email was even sent by a real person, which is another great technique to improve open and click-through rates.

Hyper-personalization is even more sophisticated than this example. Let’s look at this great example by WebEngage:
We suppose that a prospect uses your brand’s official app to find brown leather boots. However, the search takes them about 10 minutes before they give up and close the app without purchasing anything.

An analysis of this activity by this specific prospect reveals the following key points:

  • The search and purchase history for your footwear brand.
  • The time of year for the maximum number of purchases.
  • An analysis of the purchasing behavior of discounted products.
  • An analysis of the maximum engagement of push notifications generated by the app.

A hyper-personalized campaign would use these valuable points to improve the communication with that specific prospect. For example, it would generate an in-app push notification, an email or even create a retargeting ad about a quick sale on your brand’s brown leather boots on a Thursday between 5 and 8 pm (the times when the prospect most frequently uses the app).

So let’s now summarize how a hyper-personalized content paradigm is different:

Hyper-Personalization Provides More Vivid Context to Content

If you have digital marketing experience, chances are that you’ve heard the saying “content is king.” Yes, content is extremely important, but it can be useless if it doesn’t have any context.

As described above, hyper-personalization can solve this problem by algorithmically analyzing certain factors, such as customer demographics, location, the time of the most frequent purchases, and preferences in communicating with businesses. AI processes these results and provides marketers with a better picture of how to communicate with customers.

In other words, hyper-personalization helps content marketers become more proactive about communicating with their target customers because their content will be much more contextually relevant.

Hyper-Personalization Uses Real-Time Insights

Hyper-personalization creates truly dynamic content that personalization cannot currently deliver.

For example, this type of content is produced when a customer or lead clicks the call-to-action button on your landing page/app/email. It pulls the latest data about the user and produces personalized output to maximize the chances of conversion.

Hyper-Personalization Takes Personalization to a Whole New Level

Customers demand more sophisticated personalization from companies. For example, a recent study by Selligent Marketing Cloud found that 74% of consumers said they expected businesses to “treat me as an individual, not as a member of some segment like ‘millennials’ or ‘suburban mothers.’”

When the company adjusted the results to only include US-based consumers, the percentage was even higher (77%).

Traditional personalization practices clearly cannot meet these needs. Hyper-personalization delivers a much more effective and efficient algorithmic data analysis, so it enables marketers to hyper-personalize content through a wider range of customer-related factors.

As a result, it would be much easier to build meaningful individual relationships that consider the unique interests and preferences of customers.

How to Prepare for Hyper-Personalization

If the information you’ve read so far suggested that your business might not be ready to deliver hyper-personalized experiences to your customers, don’t worry. Very few companies are.

To ensure your brand can take advantage of this innovative practice and speak with each customer on a 1:1 level, you need to know how to prepare.

1. Know Your Customers.

Before you begin, you always need to remember the true standard for hyper-personalization is one-on-one interactions with your target customers. Treat each prospect or customer as an individual, not a segment (such as the aforementioned “millennials” or “suburban moms”).

Why? This kind of approach ensures that when the moment to make an offer comes, you’ll be ready when the moment to make an offer comes—because you’ve anticipated it by analyzing lots of data and gaining deep customer insight.

2. Improve Your Methods for Data Collection and Analysis.

To get a good understanding of your customers’ needs, you have to have as much data as possible. So gather data through your website, mobile app, and social media account to understand their motivations, interests, and issues, and the ways they engage with your brand.

But this time, don’t rely on mentions and hashtags. Instead, use sophisticated AI tools such as image recognition (a tool that allows you to understand the content of an image) and sentiment analysis (an algorithm that is designed to analyze the sentiment of social media content).

These tools will greatly improve the quality of your data collection and analysis methods, and will give you more insights into customer opinions and needs.

3. Use Customer Journey Analytics.

Customer data platform is a relatively new type of SaaS that plays a critical role in hyper-personalizing services by providing a unified viewpoint about the customer. It’s rapidly becoming popular among digital marketers, because it improves a business’ understanding of their target customer and helps execute and optimize hyper-personalized journeys.

customer journey data

Source: Email Vendor Selection

Here are some of the most important features businesses can use in customer data platforms:

  • Data segmentation
  • Data collection and storage
  • Data enrichment
  • Reporting
  • Data auctioning

Moreover, it’s different from customer relationship management (CRM) and other customer data systems.

This table compares customer data platforms (CDPs) with data warehouse, data management platform (DMP) and customer relationship management (CRM) systems.

comparison of CDPs with DMP and CRM systems

Simply put, customer data platforms will be the tools that fuel hyper-personalization with data, so using them will become musts for online businesses.

4. Engage a Customer with the Right Message at the Right Moment.

The last step in the hyper-personalization process is also the most important: initiating customer engagement at the right time, based on what he or she is currently interested in. In other words, you should hyper-personalize customer interactions and create deeper customer loyalty.

For example, Starbucks has made tremendous progress in hyper-personalization. In 2008, the company made a somewhat unexpected decision to invest in its own cross-channel marketing technology, instead of buying more online advertising. It has completed many projects since this initiative began, but the most well-known is the My Starbucks Reward Program.

Starbucks Rewards

Image Source: Starbucks

This loyalty program places a special emphasis on personal communication with customers, both online and in-store. Here are the most important perks of the program:

  • It offers personalized value in the form of local recommendations.
  • It allows users to pay via the app, so neither a cash or card is required.
  • No sign-in is required.
  • It gives loyalty points to anyone who pays via the app.
  • It provides news about the latest offers from the brand.

In other words, this app is a goldmine of data about customer preferences and behavior, which AI could turn into precious insights. For example, by analyzing orders, payment preferences, frequently visited locations, and the customer lifetime value, the brand can hyper-personalize just about every aspect of the interaction with its customers.

So that’s what Starbucks is doing. No wonder Fortune named it the world’s fifth most admired company.

As Starbucks continues to adopt AI-powered analysis tools, the My Starbucks Rewards Program sets a new standard of hyper-personalization.


Content marketing and personalization are here to stay, so getting ready for hyper-personalization is something you absolutely have to do to make sure your online business stays relevant and competitive.

Let’s summarize the main benefits of using AI in hyper-personalization:

  • Increased performance

AI makes it possible to collect and process vast amounts of data and other time-consuming tasks.

  • A unified view of your target customers

An analysis of collected data will improve your understanding of your customers and will create more relevant and personalized offers.

  • A more personalized experience overall

As you already know, most customers prefer personalized experiences so AI will give you the knowledge you need to provide your target customer with the strongest one possible.

Dale Carnegie once said something very relevant to content marketing: “A person’s name is to him or her the sweetest and most important sound in any language.” Hopefully, this article was a good introduction to hyper-personalization in content marketing and gave you the information you need to start preparing your business for the upcoming AI revolution.

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