A Personalization engine extracts data from individual customer accounts and keeps tabs on unidentified customer responses. All the data captured by personalization engines are used to enhance the overall customer experience. It maps out customer behavior, geographic location, data alterations, and even understanding the individual needs. 

A Personalization Engine uses Artificial intelligence in the form of machine learning to understand unique user profiles. It also performs data visualization, for catering to the consumer’s requirements. 

Personalized marketing is a use case for the collection of individual customers with the use of automation technology for improved user experience, increasing brand loyalty among customers, and generating higher revenue. 

Personalized marketing driven by artificially intelligent consumer-behavior algorithms, which leads to effective customer relationships and business communication systems. The customers are more plausible towards the brands that completely serve their needs by understanding what the consumer requires.  

Personalized Marketing has turned out to be more efficient than traditional advertising. In traditional marketing, more resources and costing are included with advertisements that usually don’t interest the consumers. However, personalization engines generate targeted ads as per the consumers.  

Some Applications of Personalized Marketing   

  • Targeting Ads

These involve particularly targeted ads for a uniquely specified customer as per the behavior and need. Thus, generating further interest of the consumer with related products or services. 

  • Personalized Messaging

Personalized messaging involves the gathering of user-related data. Concerning the targeted consumer regarding behavior, geographic location preferred content, and search history. All the information gather gets used to formulated personalized messages for the consumers. 

  • Product Recommendations

Many a time, after checking out from our shopping carts at online portals, we see recommendations for products or services. Recommending personalized engines involve redirecting consumers towards a similar product to buy and making comparisons among the products. 

  • Dynamic Websites

These involve rapidly changing websites as per the user preferences. The content shown on the website interface dynamically changes as per the user, involving the content which is most applicable for the user. 

Difference between Targeting and Personalization 

A targeting system is identified as a marketing solution used by a marketer. Whereas Personalization is about customer needs and consumer behavior.  

Marketer’s use targeting for mapping out the market and their customers. However, personalization engines work upon customer preferences with the use of machine learning.  

Personalization engines use a micro approach, which involves studying the individual user behavior for catering towards its needs. On the other hand, marketers use targeting as a macro approach and segment the customers in large chunks.  

The machine learning approaches are relatively swift and ferocious to use, as it takes very little human effort and works autonomously on, saving time as well as resources. A personalized engine also works on creating a personal experience with the consumers from an individual approach. It congregates all the details of the consumers, hence, understanding their requirements and interests. This helps in generating the most relevant content required by the user.  

Overall, Business becomes much easier when we understand the need of the consumers, at the individual levels. Personalized Marketing uses such techniques involving the understanding of the customer’s behavior and interests which establishes a relationship with the customers.