# Everything You Need to Know About Hyper-Personalized Email Marketing

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## Table of contents

- What is hyper-personalization in email marketing?
- How is hyper-personalization different from personalization?
- 5 reasons to hyper-personalize email marketing
- 5 examples of hyper-personalization in emails
- How can you hyper-personalize your emails?
- Final takeaway

In this digital marketing era, consumers' inboxes are flooded with marketing emails. Email marketers understand the need for and have actively adopted personalized email marketing strategies to provide personalized experiences to different kinds of target consumers.

  

With the advancement of technology and the introduction of AI and machine learning, marketers have indulged in **hyper-personalized email marketing**, which goes beyond the old trend of sending emails that address recipients by name in the subject line and email. In this article, we will explore the various avenues that hyper-personalization opens up for email marketers and how you can hop on the trend.

## What is hyper-personalization in email marketing?

Hyper-personalization in email marketing is an advanced form of personalized email marketing that leverages [artificial intelligence (AI)](https://www.mailmodo.com/guides/ai-in-marketing/) and advanced data analytics to analyze real-time and historical customer data to deliver extremely personalized [advertising](https://www.mailmodo.com/guides/email-advertising/), offers, products and services to individual users.

  
Let’s take Amazon, for instance. It has access to a lot of data on every website user, including but not limited to products liked, products viewed, items in the shopping cart and purchase history, in addition to all the other basic details like name, age, gender and location. Their product recommendation engine uses customer data to analyze and predict the kind of products that a customer would like. If you have previously searched for a particular product, you will find a [product recommendation email](https://www.mailmodo.com/guides/product-recommendation-emails/) with products that would be very closely related to the kind of product you had searched for on their website.





## How is hyper-personalization different from personalization?

The major difference between traditional personalization and hyper-personalization is that personalization tends to [segment its audience](https://www.mailmodo.com/guides/audience-segmentation/) into broad categories using basic details like age, gender, location, etc. and caters to each segment as a whole. This can still include addressing recipients by their names in the communications.

  

On the contrary, hyper-personalization attempts to build individual customer profiles to understand their preferences. This includes collecting and using vast amounts of historical and real-time data beyond what the customers have already provided, like browsing history, purchasing history, current location, likes and comments on social media and more. Hyper-personalization uses advanced data analytics and artificial intelligence to offer ultra-personalized customer experiences.

|Personalization|Hyper-personalization  |
|--|--|
|Customer data is used to gain basic insights and provide tailored experiences|Customer data is highly analyzed to gain deeper insights, understand better and predict future behavior|
|Can provide generic product recommendations|Unique and user-specific product recommendations|
|Segments customers into broad demographic categories|Utilizes micro-segmentation for individual treatment of customer|
|Can offer content based on customer’s past behavior|Can predict customer’s future behavior and needs and provide content accordingly|

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<p> <strong>💡 Related guide:</strong> <a href="https://www.mailmodo.com/guides/email-personalization/">An Email Personalization Guide to Strengthen Customer Relationship</a></p>

  

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## 5 reasons to hyper-personalize email marketing

Personalized email marketing provided marketers with growth and an increase in the conversion and engagement rates of email campaigns. With hyper-personalized email marketing, it leveled up. Marketers saw even better results and a much better ROI. Below, we give you a few reasons for considering hyper-personalization email marketing.

### 1. Better understanding of customers
    

Hyper-personalization needs collecting vast amounts of customer-specific data and analyzing this data to understand individual customers on a deeper level. This helps brands and marketers to better understand the likes, dislikes, preferences and interests of their customers.

  

>At Yeespy, hyper-personalization is a key aspect of our email marketing strategy. We believe in delivering highly relevant and tailored content to our users based on their preferences, behaviors, and interactions with our app. <br>
>One way we achieve hyper-personalization is by leveraging the data we collect from our users' monitoring activities. For instance, if a user frequently monitors their child's online activity, we use this information to send them targeted emails with helpful tips on digital safety for kids. By addressing their specific concerns and interests, we aim to provide valuable insights that resonate with our users and enhance their monitoring experience. <br>
> -[Nathan Clark](https://www.linkedin.com/in/nathan-clark-1a20b627a/), Co-Founder, [Gate2AI Inc.](https://www.gate2ai.com/)

  
  
  

### 2. Better audience targeting
    

Marketers use highly specific customer data to target specific customers interested in the services or products. This helps them focus their efforts on more specific segments and also develop better strategies for those specific segments.

  

### 3. Better customer experience
    

As the content sent to the customers are specific to them, the customers find more value in the content of the emails sent to them. These emails have lesser chances of being considered or looked upin as spam. As the emails contain information that serve their specific needs, it affects the [customer experience](https://www.mailmodo.com/guides/customer-experience/) positively.

  

### 4. Better chances of success
    

As the content is more relevant and meaningful to the customers, recipients are more likely to engage with it. When they receive emails that cater to their specific interests and preferences, they are more likely to open and interact with the content resulting in increased engagement rates. This also impacts the conversion rate of the email campaigns heavily.

  

### 5. Ability to predict
    

The use of advanced algorithms, AI and predictive analytics allows marketers to provide customers with the kind of content that is the best for them and presents them with the right options. They offer the right content at the right time.

  

## 5 examples of hyper-personalization in emails

Take a look at these great examples of hyper-personalization in emails and use them in your future email campaigns.

### 1. Product recommendation emails
    

The collected comprehensive behavioral data and consumers' browsing history can be analyzed to predict future choices. Based on these insights, product recommendation emails can contain a curated list of items with a higher chance of being bought by the recipient.

  

>We use hyper-personalization in our emails to recommend products. When we see users spending a lot of time on a product page, we group them together. We have a template for each group. This includes recommendations. We also add a few tips and benefits to the product. This helps us provide more value to our customers. Each email addresses the customers by their first name. We've seen a high conversion rate for these emails, and they've been a success. <br>
> -[Brian Hardesty](https://www.linkedin.com/in/brian-hardesty-90a5527/), Owner, [On Display Signs](https://www.ondisplaysigns.com/).

### 2. Customized offer emails
    

Hyper-personalization also allows for customer-specific offers. These offers can be based on the browsing history, purchase history, location of the user, etc. So, people who might have shown interest in books or shoes can be sent offers on books or shoes respectively.

### 3. Birthday emails
    

Another example of hyper-personalization is birthday emails. Brands can target customers on their birthday or anniversary and offer them customer-specific offers, discounts and special gifts. This would also need brands to analyze the kinds of products individual customers are interested in and offer them a curated list of products chosen specifically for them, as discussed in the previous point.

### 4. Loyalty program emails
    

Brands can also send hyper-personalized emails to their members, which may contain their loyalty points, updated in real-time. These emails can also contain options for redemptions of these points by buying products. These product recommendations can be specific to each member’s loyalty points and the member’s behavior and browsing history.

### 5. Dynamic email content
    

Dynamic email content uses real-time data to provide individual customers with highly relevant email copies. The content of the email changes based on the recipient of the email. Take a look at the below email.

  

Hey {first name},
We saw you noticing {product name} on our website, but you left it behind. Do you have any questions?
Here’s some motivation: 20% discount if you order it today.

  

This shows how the email uses the customer’s browsing data to track which product he was looking at and sends an email mentioning the specific product. A similar example is the <a href="https://reallygoodemails.com/" rel="nofollow">Really Good Emails’</a> newsletter, where they personalize the image to the recipient’s name.

## How can you hyper-personalize your emails?

Creating a hyper-personalized email campaign involves a few extra steps than a personalized email campaign.

  

### 1. Collect data
    

The kind of data you collect sets hyper-personalized email campaigns apart from personalized campaigns. The amount of data you collect determines the amount of personalization that you can do in your emails.

  

You can collect customer data from various sources like social media, customer surveys, purchase history, website interaction, etc. You can collect psychographic data that will tell you about their interests, activities, attitudes and values and behavioral data that will tell you about their online activities, purchase habits, brand preferences, social media interactions, etc.

  

You can use a [customer data platform (CDP)](https://www.mailmodo.com/guides/customer-data-platform/) to do that for you. For example, <a href="https://segment.com/" rel="nofollow">Segment</a> is a CDP tool that collects data from several points, processes the collected data to form unified customer profiles and deploys that data to other tools.

  

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<p> <strong>💡 Related guide:</strong> <a href="https://www.mailmodo.com/guides/email-form/">How to Use Interactive Email Forms to Collect More Responses</a></p>

  

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### 2. Analyze the data
    

The collected data will only be useful if you can get insights from it. While analyzing the basic customer details is simpler, analyzing comprehensive data like customer behavior and interests is not possible for humans.

  

These data can be analyzed using artificial intelligence to output valuable customer insights like the kind of products they would like, the artists they prefer to listen to, the kind of songs they listen to and so on.

  

Before an AI model is able to analyze your data you need to train it. This will need you to clean the data that you’ve collected which means removing duplicates, handling missing values and structuring your data to make it suitable for analysis.

  

The next step involves feature engineering where you create meaningful attributes from the data collected like past purchase frquency, sentiment analysis, etc. You can then move on to choose the model you want to use based on their individual strengths . You can then split your data into training, validation, and test sets, ensuring that the training data is labeled with the correct outcomes you want the model to learn.

  

Then you can train your AI model. As your model learns from this data, it begins to recognize underlying patterns and relationships. You also need to evaluate the performance if any tweaks need to made or not.

  

AI models also allow for predictive analytics, which helps predict future customer behavior and can be used to deliver a hyper-personalized customer experience that is predicted to resonate better with individual customers.

  
  

### 3. Feed data into your emails
    

Once you have collected and processed all this data, you need to make use of this data. To do that, you must import all of the information and insights that you have gathered to your email service provider. This allows you to use the various attributes that your AI model has given you as output.

Mailmodo offers integrations which allow you to import analyzed data to be used in your email campaigns. For instance, you can use the Segment integration that allows you to export your data into Mailmodo very easily. You can follow the support page for a [step by step guide](https://support.mailmodo.com/categories/958988-958988-segment-io-cdp) on how to initiate it. Once the data is imported, you can use it in your email campaigns.

  

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<p> <strong>💡 Related guide:</strong> <a href="https://www.mailmodo.com/guides/dynamic-email-content/">Everything You Need to Know About Dynamic Email Content</a></p>

  

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### 4. Automate your emails
    

You can set up automated email campaigns triggered by specific customer actions or time-based events. This automation will allow for the automatic sending of emails without you having to monitor things all the time. It also prevents missing opportunities.

  

Again, Mailmodo allows you to create customer journeys where you can [automate email campaigns](https://www.mailmodo.com/guides/email-automation/) based on custom triggers. For instance, you can have an email sent to a customer who added a product to the cart but left without completing the purchase. You can have an email template designed to be sent to the customer that would have not just the name of the recipient but also the name of the product that he had added to the cart.

  

## Final takeaway

In the age of personalization, when consumers seek a personalized experience, hyper-personalization is the right choice for email marketers. It gives you an edge over the competition and gives your customers the customer experience they deserve. It increases the engagement and [conversion rates](https://www.mailmodo.com/guides/email-conversion-rate/) of your email campaigns.

## Frequently Asked Questions

### What is hyper-personalization in Email?

Hyper-personalization is an advanced marketing strategy that tailors content, product recommendations and communications based on the specific user’s interests, preferences, behavior, and more.

### How to do hyper-personalized email marketing?

You can do hyper-personalized email marketing by analyzing browsing history, offering dynamic content, using predictive analytics, AI and machine learning algorithms, and more.

### How is hyper-personalization different from traditional personalization?

While traditional personalization uses basic details like name, age, gender and demographics for customer segmentation, hyper-personalization uses AI and deep learning algorithms to analyze real-time customer data like browsing history, purchase history and preferences to build a unique customer profile.

### What is the impact of hyper-personalization?

Hyper-personalization leads to a better customer experience by offering the recipients more relevant content that is curated specifically for them. Marketers, on the other hand, get better engagement rates and a better ROI.

### Name an email service provider that I can use to send out personalized emails.

Mailmodo is an all-in-one email marketing platform that allows you design and send interactive emails which can have dynamic content and even allows features for personalization.

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**Author: Mashkoor Alam**

Mashkoor has always been passionate about writing. He used to write short stories on his blog before he started writing for SaaS companies years back. He aspires to have a book under his name.

