What is hyper-personalization ?


By 6 October 2022 No Comments

Nowadays, marketing can seem complicated as it is more and more competitive. However, thanks to data, strategies and methods can be implemented to better satisfy and retain customers. 

Among those methods, there is hyper-personalization. And that’s what we’re going to talk to you about today. 


What is hyper-personalization? 


Hyper-personalization can be simply defined as the evolution of personalization. It allows companies to approach their users as individuals instead of parts of a segment, thus offering them a refined experience, satisfying and retaining them more easily. 

According to Syte, hyper-personalization is done by collecting data on a large scale, analyzing it, and using the conclusions to create automation, allowing real-time refining of the user’s experience. All of this is done with the help of AI and machine learning, with the end goal being offering a premium service, increasing the checkout value per customer, and earning the latter’s loyalty. 

Let’s take the example of a clothing brand. This brand can use a hyper-personalization strategy to make more pertinent offers to its clients, transitioning from recommendations by segment or tribe to unique, individualized propositions based on multiple factors such as sex, age, interests, purchase history and use cases. 

We can also use Netflix as an example. As GetResponse describes, the streaming giant use hyper-personalization to adapt the poster of the show or the movie they recommend, putting one where an actor the user likes is shown.  


The method of hyper-personalization 


To set up hyper-personalization in an organization, you have to start by collecting data on a large scale. That includes internal data on the user’s and their interactions with the organization, but also external data collected on other websites and on social media (especially useful in ecommerce). That can represent petas of data for large platforms. That’s the first challenge. 

Once the data is collected, the more exciting parts come: the analysis and the hyper-personalization itself. 

You have to analyze the collected data, and determine which elements allow you to set up hyper-personalized actions to improve drastically your user’s experience. To do that, you have to combine multiple skills and multiple technologies like data visualization, but also artificial intelligence to identify trends and make predictions to make better decisions. 

Next step: the hyper-personalization (finally), the time to automate the actions that must be taken according to the factors determined as triggering. That’s when machine learning can help simplify, speed up and improve the process. 

To implement this type of procedure, data mesh can be a powerful asset. It unifies access to data which is often locked in a silo through unique data products. 

But how can you face that much collected data without losing control of your budget and/or slowing down your dashboards? That’s when we enter the scene. The Indexima solution allows you to streamline the access to your data, thanks to our AI algorithms which automate the creation of data marts or materialized views. These simplified processes aim to automate your data pipeline and make you save on computing. Let’s improve your hyper-personalization strategy and make your data analytics team’s life easier! 

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