A New Marketer’s Guide To Hyper Personalization

Personalization helps in improving customer relationships. In fact, over 70% of marketers claim that personalization has a ‘strong’ or ‘extreme’ impact on overall customer relationships. That said, only 22% of customers are satisfied with the level of personalization they get from brands. 

As a result, marketers no longer focus on simple personalization such as adding a first name to emails. These tactics are no longer enough. Today, consumers are expecting a higher level of personalization, also known as hyper personalization. 

For new marketers, this article shares everything you need to know about hyper personalization and how to get started. 

Hyper Personalization: What Is It?

Hyper personalization refers to the process of using customers’ behavioral data and real-time data extracted from multiple touchpoints and channels to create an extremely customized marketing strategy. 

With hyper personalization, brands can tailor their services, products, and advertising efforts to each customer for maximum conversion potential and relevance. It’s important to do research to see and emulate examples of popular brands with the most successful hyper personalization campaigns.

Personalization Vs. Hyper Personalization: What’s The Difference?

In general, hyper personalization is a step further to personalization. Hyper personalization marketing uses advanced technologies such as machine learning, artificial intelligence (AI) and Internet of Things (IoT) enabled devices to deliver more customized and relevant experiences and offers to each user. 

Man Using a Hyper Personalization System by Pressing a Button on Futuristic Interface. Business Concept

With traditional personalization, marketers advertise using customers’ names, purchase histories, and locations. However, with hyper personalization marketing, marketers also consider purchasing, browsing, and other real-time behavioral data to zero in on what a customer really wants or needs.

Thus, hyper personalization is more complex, involved, and useful than traditional personalization efforts since it goes beyond the basic customer data. 

For instance, a swimwear shop may advertise its bikinis to consumers who bought similar ones the year prior. With hyper personalization, the shop could promote the same bikinis with optimized ads based on the payment method, the exact purchase time and location, social media activity, coupons used and so much more. 

With this extra data, hyper personalized campaigns become more relevant and have better chances to generate leads. 

The Benefits Of Hyper Personalization

Since it’s a level-up form of traditional personalization, hyper personalization offers double or even triple the benefits. Some of the wonderful benefits of using hyper personalized marketing campaigns include:

  • Higher click-through rates (CTR), conversion rates, and return on investment (ROI)
  • Increased revenues and profits
  • Smoother customer journeys and enhanced overall experience 
  • Reduced customer churn and improved customer lifetime value
  • Better consumer engagement
  • Advantage against competitors

4 Steps To Developing A Hyper Personalization Strategy

So, how do you develop a hyper personalized marketing campaign? Follow these four steps:

1. Collect As Much Data As Possible

The first step in developing a hyper personalized strategy is to start collecting relevant data about your consumers. And in terms of hyper personalization marketing, there’s no such thing as collecting too much data. In general, you need to collect both qualitative and quantitative data

Qualitative data relates to a consumer’s feelings and motivations. You can collect this type of data by using product reviews, online surveys, and questionnaires. You can also buy consumer data sets from 3rd party data providers to fill gaps in your data. 

Meanwhile, quantitative data refers to any information about how an individual interacts with your business—from website activity to social media contacts to personal and transaction data.

Some of this data can be collected in real-time, while other information can be taken from historical data sources. This data can help create a clearer picture of a consumer’s relationship with your business. 

2. Segment Customers

Once you have all the data you need, you can segment your customers. Unlike traditional personalization, hyper personalization requires you to create the smallest grouping possible. Using the data you collected, you can segment your customers using data points such as:

  • Location
  • Brand interaction history
  • Satisfaction ratings
  • Average spend
  • Demographic data
  • Purchase history

Of course, there are more types of customer segmentation you can use, depending on your business type. 

3. Design Targeted Journeys

After completing the segmentation, you need to create targeted journeys for each segment. Map out the journey of a typical customer in each segment on their way to a purchase. This data can help inform where personalized interventions are possible to push customers toward a purchase or other conversion activity. 

In general, using an AI-powered hyper personalization marketing platform can determine those intervention points as well as determine which channels to use or actions to do at any given time. 

4. Define Measurement Methods And Key Performance Indicators (KPIs)

The whole point of a hyper personalization marketing campaign is to improve your sales and revenues. Thus, it’s important to measure your efforts’ impact and determine if they’re actually working. 

You need to define KPIs for your campaign before putting them into action. Also, make sure to set up methods on how to measure your progress against these KPIs. 


While personalized service was the norm for years, changing customer demands have pushed marketers to move into hyper personalization. 

When done effectively, hyper personalized marketing campaigns can be a win-win for companies and customers. They allow your brand to create more meaningful relationships and improve overall customer experience. 

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