Hyper-personalization in Email Marketing: An Overview by Our Experts

Hyper-personalization is not just advanced personalization but a deeper commitment to customers made possible by a combination of data and technology. Hyper-personalization isn’t about invading privacy—it’s about building genuine, human connections with your audience.

Let’s first understand in detail how personalization and hyper-personalization differ. Where personalization uses elementary data such as first names and purchase history, hyper-personalization leverages a rich pool of data (past purchases, browsing behavior, demographics, preferences) and AI to create laser-focused messaging that resonates deeply.

As far as email marketing is concerned, hyper-personalization is about crafting experiences so tailored to the individual recipient that they know the emails were written just for them. 

But what does all this entail? How can you leverage hyper-personalization to serve your customers and grow your business? 

In fact, why should you bother about “hyper” personalization when personalization seems to be doing the job just fine?  

Just to keep up with your competition? Maybe to mouth the shibboleth while spitballing with a potential client? 

Let’s start with that and continue in the following order: 

• Why should you care about hyper-personalization?
  
• How to hyper-personalize email campaigns?
  
• Tips on hyper-personalization in email marketing
• A/B testing & multivariate testing
  
• A word on multilingual email campaigns
  
• 6 tools to get started with hyper-personalization

Why should you care about hyper-personalization?

To begin with, check out these numbers:

• Hyper-personalization has led to a considerable increase in business results for 86% of companies. (Source: Evergage)
  
• 90% of customers find highly-tailored campaigns very appealing. (Source: Deloitte)
  
• 78% of customers are more likely to repurchase from a brand that sends them tailored content. (Source: McKinsey)

The difference between personalization and hyper-personalization is not just a difference in degree but also in kind. It’s a wholly different way of connecting with your customers, and it’s data that makes this possible. 

Consider, for example, an online clothing retailer. Below is a table comparing a personalized campaign and a hyper-personalized campaign.

	Personalized campaign	Hyper-personalized campaign
Data used	Basic demographic data (age, gender, location), general purchase history (categories), browsing behavior, etc.	Detailed purchase history (specific items, sizes, colors), real-time browsing behavior (no. of items viewed, time spent, cart abandonment), stylistic preferences, time of day, location-based weather data, type of device, social media activity, etc.
Approach	Broad targeting, general product recommendations	Highly granular targeting, highly specific, contextual recommendations
Individualization	Limited to segment-level	Creates a unique experience for each customer via dynamic content
Technology	Basic CRM data	AI, ML, Big Data, predictive analytics

Let’s say a customer, Martha, receives a promotional email at 8 AM on Monday. The email features a blue linen dress which she viewed multiple times on Sunday last. Apart from that, the email also suggests a matching cardigan because the local weather forecast anticipates a sharp temperature drop in the evening. To complete the ensemble, the email recommends a pair of shoes that are typically bought with that dress but is currently low in stock. 

So no, not just to keep ahead of your competition, but your customers as well. Clearly, hyper-personalization is effective. 

And we can vouch for it ourselves. Hyper-personalization was part of our email marketing program with Wag!, a pet wellness service provider based in the U.S. Feel free to check out the Wag! case study. 

How to hyper-personalize email campaigns?

Data collection, analysis, and problem-solving underlie a hyper-personalized campaign, as illustrated in the following conceptual framework. 

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Let’s explore the framework in some detail, starting with data collection. 

1. Collect customer data

Start by collecting customer data such as:

• Name, gender
  
• Time, season, customer location
  
• Marital status
  
• Occupation/profession
  
• Device type
  
• Products previously viewed or purchased
  
• Time spent on website and app
  
• Price point

It’s not an exhaustive list, mind you. But it shows the possibilities. 

But how do you collect customer data? dotCMS recommends the following three methods:

1. Social listening: Educate yourself about your target audience from their engagement with social media platforms such as Facebook, X, Reddit threads, YouTube, TikTok, Instagram, etc.
   
2. Attribute analysis: Attribute analysis is the process of identifying and analyzing shared attributes, such as interests, values, opinions, etc., between individuals in your customer base. Use these attributes/data points to tailor the customer experience.
   
3. Behavioral segmentation and event sequence analysis: Collect data about your customer while they’re buying a product. This can include whether or not the customer used a coupon, average purchase time, device type, etc. Leverage these data points to simplify the shopping experience.
   

“The leading brands in e-commerce and SaaS are using extremely advanced levels of personalization. This is made possible because of the granular data they’re collecting from customers and prospects at various stages of the buying cycle,” says Ryan Turner, founder of Ecommerce Intelligence.

Critically, while collecting customer data, you need to beware of a host of data privacy issues. If you’re not collecting data responsibly,  you risk incurring reputational damage, loss of customer trust, or even class-action lawsuits, at worst. So while collecting data, you’ll want to:

• Obtain implicit and explicit consent while communicating, in unambiguous terms, the purpose of data collection and how you mean to use it. Make sure to provide unchecked boxes for opt-in.
  
• Only collect the data you’re going to use. Avoid requesting unnecessary information.
  
• Implement robust security measures, from encrypting data to using secure servers and databases. Limit access to customer data and update the security software on a regular basis.
  
• Formulate a transparent privacy policy, ensure that customers can easily access it, and communicate any and every policy update to your audience.
  
• Stay updated on relevant privacy regulations like GDPR, CAN-SPAM, and CCPA. Include a clear, prominent unsubscribe link in every email, process all unsubscribe requests promptly, and honor such requests.
  
• Perform regular audits to maintain data accuracy at all times. Delete data that you no longer need. 

2. Perform advanced segmentation

In traditional personalization, you would segment your audience based on shared characteristics and interests. But hyper-personalization lets you create highly granular segments with the help of AI and machine learning.

Advanced segmentation is made possible by the following AI/Ml models and algorithms:

• Clustering: In email segmentation, clustering algorithms group users with similar behaviors. Hierarchical clustering, a subset of the clustering algorithm, is used to discover niche segments based on complex user behavior. Similarly, DBSCAN, or density-based spatial clustering, groups users based on highly similar behavioral patterns while isolating outliers.
  
• Predictive modeling: Using logistic regression, decision trees and random forests, and gradient boosting machines, predicting modeling anticipates churn risk, CLV, individual responses to emails, etc.
  
• Time series analysis: A time series analysis tracks and identifies patterns in user behavior over time to determine optimal send times. 

Ideally, you could never be too granular with your segmentation. But you want to care, not creep out the audience. So, advanced segments could be:

• Subscribers close to making a purchase
  
• Existing, one-time customers
  
• Low-end customers
  
• High-end customers
  
• Look-alike subscribers
  
• Customers who purchased on mobile
  
• Customers who purchased on desktop
  
• Returning customers

And so on.

The point is to anticipate customer needs. As Sunil Thomas, co-founder and executive chairman of CleverTap, says, “Granular and real-time segmentation and personalization will equip marketers to individualize experiences in lockstep with what customers value in any given moment.”

3. Create dynamic content

Tailor your email content based on subscriber data. Use dynamic content to personalize product recommendations, showcase abandoned cart items, and highlight blog posts relevant to their interests.
“Traditional personalization strategies,” dotCMS notes, “saw companies send cart abandonment emails, while a more hyper-personalized approach revolves around discussing the specific items they abandoned, offering incentives for those items, and creating limited-time offers that cater to the customer.” Below is a cool illustration of this statement. 

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4. Set up automated triggers

Set up automated emails triggered by specific actions. These feel super personal because they arrive at exactly the right moment. 

For example, here is a browse abandonment email from Marine Layer. The high-point of this email is the browse-optimized CTAs.

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5. Use location data

If you have location data (with permission, of course!), use it to personalize your emails. Local deals, store opening hours, or even weather-related product recommendations can add a nice touch.

In this email, Loisa simplifies it all with a store locator feature.

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Tips on hyper-personalization in email marketing

Hyper-personalization is not just fancy tech. Consider the following tips:

• Use a friendly and conversational tone: Write like you’re talking to a friend, not a robot.

• Keep it concise and scannable: People are busy, so get to the point quickly and use bullet points and visuals to break up the text.

• A/B test everything: Test different subject lines, content, and layouts to see what resonates best with your audience.

• Don’t be afraid to get creative: Personalization doesn’t have to be po-faced. Use humor, emojis, or even GIFs to add personality.

A/B testing and multivariate testing

Hyper-personalized email campaigns require ongoing testing. To that end, consider the following tips with respect to A/B testing:

• Subject line personalization: Test for nuance, or the extent to which subject lines are personalized. For example, “Exclusive Deals on Hiking Gear for You, [name]” vs. “Latest offers on hiking gear!”
  
• Content block variations: Test different content blocks. For example, you can show product recommendations in one version, and compare it with another showing educational resources, both based on the user’s specific interest or recent browsing behavior.
  
• Personalized offers: Test different types of personalized offers to find out whether a specific % off or a Free Shipping on all orders formula resonates with the audience. You can also test the positioning of the offer in terms of its placement in the subject line, pre-header, or above the fold, primary CTA, and so on.
  
• Send times: Remember to test various send times based on when users are most likely to open your emails. 

You should also do a multivariate analysis of hyper-personalized emails. 

Consider dynamic content carefully. Since these blocks vary from user to user, a multivariate analysis can help determine the most effective combination of design and text elements for each email. For example, in a personalized discount offer, two subscribers may receive the same email with different discount values. However, varying data lengths can disrupt the layout, making simple number changes insufficient. It’s essential to test whether both discount offers fit seamlessly within their designated spaces, especially if you’re using bold typography for emphasis.

To ensure a cohesive design, multiple variables should be tested, including font size, text length, banner dimensions, supporting subtext, etc.

But that’s just one example. Evidently, multivariate testing or MVT is more complex than A/B testing. Setting up and managing MVT can also be more resource-intensive. Some tips:

• Start with a combination of high-impact elements, such as CTA, subject lines, rather than testing everything at once.
  
• Slice out the most active portion of your email list since MVT requires a large audience to achieve statistically significant results.
  
• Run your MVT for sufficient duration to achieve statistical significance.
  
• Instead of running one big complex test, try to break it down to small, iterative tests.
  
• Go beyond surface-level analysis of test results. In fact, you can take the help of gen AI to gather strategic insights.
  

A word on multilingual email campaigns

A critical component of hyper-personalization is multilingualism. If you are a global brand, you need to set up multilingual campaigns because:

• People are more likely to engage with content presented in their native language. This can lead to higher open rates, click-through rates, and conversions.
  
• A multilingual approach shows customers you value their culture and preferences. This fosters trust and strengthens relationships.
  
• Multilingual campaigns demonstrate your commitment to inclusivity and global awareness, portraying your brand in a positive light.

“To hit the mark with audiences abroad,” says Natasha Zack, journalist and writer, “you need to not only translate your copy but localize all the content you use in your campaigns. That means you have to consider cultural differences and country specifics, paying attention to idioms, slang, wordplay, references, tone, and imagery to avoid coming off as weird, unpersuasive, intrusive, or even offensive.”

Consider the following tips for creating a successful multilingual/localized email campaign: 

• Know your audience: By means of online region-specific surveys, social media monitoring, gathering local information from white papers, market reports, published surveys, you’ll get to know your potential audience in the locality of your interest.
  
• Segment by region and language: You’ll want to group all users hailing from the same locality and speaking the same language into one segment. Suppose you’re a US-based wine brand expanding into the major wine regions in France. So you can create separate segments for subscribers from Alsace, Provence, and Rhine Valley. On a more granular level, you can segment subscribers from Alsace based on their use of a specific dialect of French. (Alsace has a history with Germanic languages.)
  
• Create localized content: As already explained, localized content is way more than translated content. Avoid online tools like Google Translate, or even AI tools, like the plague. Translation involves paying close attention to cultural nuances, else you risk embarrassing yourself. To start with, get in touch with professional translation agencies. These agencies have a vast network vetted native translators. You can also explore freelance platforms like Upwork and ProZ. Remember to verify the depth of cultural understanding the candidates possess. Beyond translation, you may want to scout for transcreation services which go beyond translation to adapt your message to evoke the targeted emotional response from the audience.
  
• Be informed about time zones and national calendars: Part of cultural education, being informed about time zones and national calendars helps you with optimizing your send times. Consider our wine brand example. An email sent out at 5 PM on April 1 from Boston will reach a Provence subscriber at close to midnight! Similarly, in the case of Christmas campaigns, you can’t send out promotional emails to the eastern regions of the world on the 25th of December since in the East, the festival is largely celebrated on January 6th.
  
• Test, test, test: Testing takes on a different meaning when it comes to localized campaigns. Now, there are the usual testing best practices which are uniform across campaigns. We’re thinking of tracking relevant email metrics, such as click-through rate, engagement rate, conversion rates, etc. But in the case of localized campaigns, the bar is higher. From linguistic and cultural nuances to technical considerations like character coding, RTL scripts, date formats, redirects to localized landing pages, everything needs to be tested. Email rendering, a beast on its own, grows extra fangs, what with the different languages and character sets. Keeping these things in mind, you’ll want to be extra vigilant while testing. We recommend setting up a dedicated window just for testing localized campaigns. Avoid testing these along with your other campaigns. 

6 tools to get started with hyper-personalization

Our experts recommend the following six tools to get started with hyper-personalization in email marketing:

1. Marketing Cloud Account Engagement
   
2. Dynamic Yield
   
3. Persado
   
4. Salesforce Einstein
   
5. Evergage
   
6. RightMessage

Let’s look at each of these in brief.

1. Marketing Cloud Account Engagement (formerly, Pardot)

Pardot, a Salesforce product, excels at understanding your accounts in-depth. It collects comprehensive data, including demographics, interactions, and engagement history. This information is then used to create highly targeted emails, such as re-engagement campaigns for inactive leads or personalized welcome messages for new customers.

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2. Dynamic Yield 

Dynamic Yield is a dynamic personalization platform that adapts to your audience’s behavior. It leverages data to craft re-engagement emails that resonate with individual preferences. For instance, if a customer abandons their cart, Dynamic Yield can send a personalized email reminding them of the forgotten items and suggesting complementary products.

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3. Persado 

Persado uses generative AI to create emotionally resonant emails. By analyzing audience data, Persado generates content that connects with readers on a deeper level. This leads to higher open and click-through rates. Moreover, Persado’s deep learning models continuously monitor email performance and make real-time adjustments for optimal results.

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4. Salesforce Einstein

Salesforce Einstein is an AI engine that analyzes your audience to identify the most effective language and tone. It creates highly personalized emails that resonate with your customers, making them feel understood and engaged. Einstein’s insights help you tailor your messaging to individual preferences and drive higher conversions.

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5. Evergage 

Evergage, now part of Salesforce Interaction Studio, offers real-time analytics across various channels. It enables you to create a “affinity graph” that visualizes detailed customer profiles. This information can be used to send personalized product recommendations, special offers, and abandoned cart reminders.

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6. Right Message

RightMessage leverages behavioral data to create personalized emails. 

By analyzing information such as website visits, reading history, and ad clicks, RightMessage tailors email content to individual preferences. The tool integrates with your email marketing platform to enable seamless personalization.

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In closing: Ditch the batch, get (hyper) personal! 

Hyper-personalization is about making every message count. It’s not just a technological improvement over traditional personalization but also about connecting with customers on their terms, from their points of view, and spontaneously mirroring their values, interests, and choices. 

Ready to take your email marketing to the next level? Contact us to explore how hyper-personalization can work for your brand. Our six-tier framework of email marketing is tried and tested for long-term success.