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COVID-19 has led to accelerated digitization in almost every industry across the world. Over the past year, corporate marketers have focused on adapting their technology stacks to this rapid digitization. According to the CDP Institute, the number of CDP deployments has seen a sharp increase in 2020 compared to the previous year. Over 29% of survey respondents said they have already deployed a CDP. And 22% of them said they plan to start deployment within the next 12 months.

Therefore, as interest in CDPs continues to grow among marketers, doubts and questions have been raised about CDPs and personalization engines. This article aims to explain how a customer data platform and a personalization engine are different from each other.

What is a customer data platform?

cdp vs customization engine

The CDP Institute defines a customer data platform as: « Packaged software that creates a unified, persistent client database that is accessible to other systems.« 

A CDP can aggregate and unify first, second, and third-tier user data from disparate sources in a central location. Data is unified for each individual user, allowing marketers to have a single or 360-degree view of the user. Marketers can then pull valuable insights from the unified view and understand the needs and wants of each user. Based on the information, they can target users with personalized messages and offers through various marketing channels connected to CDP.

What is a personalization engine?

A Personalization Engine (PE) uses information from a user’s behavioral data as well as data from other similar users to provide a personalized experience for the user. The information provided to the user is contextually relevant and corresponds to their needs and preferences.

Personalization engines work by resolving user identities across all channels and devices. They then use advanced algorithms based on AI and machine learning to predict what exactly users need. This is done by analyzing their propensity to click, purchase history, propensity to buy, etc. The more data these engines are able to access and analyze, the more accurate the predictions will be.

CDP vs personalization engine

  • Marketers use a CDP to create user segments that fall under desired categories, then orchestrate personalization. When it comes to PEs, marketers can design and implement unique personalized journeys at the individual user level.

  • CDPs are ideal for integrating into legacy and advanced technology stacks. This allows marketers to synchronize and unify data from these systems and enrich unified user profiles. Personalization engines have basic integration capabilities and do not have seamless and easy integration features like CDP.

  • With a CDP, the main goal is to unify customer data and create the perfect single customer view. Of course, it facilitates real-time 1: 1 personalization by allowing marketers to connect unlimited marketing channels to it. For a PE, the primary goal is to provide a unique and satisfying personalized user experience across multiple channels. Due to their advanced AI algorithms, they are really good at predicting user behavior and achieving real-time 1: 1 engagement with every user.

In conclusion

Both CDPs and PEs are powerful tools that have improved data-driven marketing and transformed the customer experience for businesses. The main strength of a CDP is its ability to aggregate and unify data and the main strength of a PE is that it offers true personalization to users according to their expectations using AI and machine learning.

For best results, marketers can integrate a personalization engine with a CDP. In this way, enriched user data is transmitted from the CDP to the PE. And the PE can use the data to orchestrate a satisfying and unique personalized experience for every user across all channels. This integration is very beneficial as marketers can make better business decisions and tailor their campaigns to be more targeted and focused on each user.

By Bijoy KB | Marketing Manager at Lemnisk

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