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March 20, 2020 No Comments

Featured article by Simona Rich, Independent Technology Author


Personalization Engine is a technology that interacts with individual customers to enhance business revenue. It collects data of the customer from outside sources and creates a unique user experience. It creates digital channels to interact with customers to deliver business-related offers, schemes and tries to befriend with the customer, which in turn increases the business profits.

For a business to grow and gain profit, customer feedback and recommendations are very important. Personalization engines play an important role in gaining business insights.

For example, if a person sitting in a cold-weather browses for restaurants they will see the restaurants with more hot beverages and food, whereas a college student might see jobs related videos while browsing through the internet. This is what the personalization engine does, every user gets to see different things according to their interests.

To achieve such kind of personalized user experience, various methods like A/B testing, batch analysis, etc is done. 

Important factors regarding personalization engines:

- As personalization engines run on certain rules and regulations they must possess the ability to learn.
- It should be self-tuned and further enhance the user experience.
- It must consist of Artificial Intelligence (AI) and machine learning.
- It delivers content relevant to the user.
- A/B testing
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Customer Data Platform (CDP) is a software that combines all sorts of available data about the customer and creates a unique profile of the customer. The data collected from multiple sources is then forwarded to other business corporate for further use and benefit for the business. CDP makes the work of a marketer simple by organizing all the data of different customers and then submitting it to the marketer for further work. It is used to prepare a customer database.

CDP collects the data from multiple sources, analyzes it and makes it accessible to marketers.

Features of Customer data platform:

- It is a unified customer data
- It is persistent
- It has real-time capability
- It is a packaged system
- It has rule-based segments
- The customer data platform offers A/B testing methods
- It offers recommendation of products
- It delivers customer-related content
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The data collected by the CDP’s can be broadly divided into four types:

Identification data:

This is a basic type of data that acts as a foundation of customer details. This includes information like name, location, occupation, phone, email, etc of the customer.

Illustrative data: 

To get a complete picture of the customer, this type of descriptive data is collected. It includes career, hobbies, family, etc information.

Behavioral data:

 This type of data includes information about how is the customer related to the brand in terms of business. It may contain information about transactions (amount spent, the timing of purchase or return), customer service (issue details, date), emails (responses, email opening), etc.

Contextual data: 

This includes information like, how did the customer get to know about the brand or product? How much do they want to rate the brand based on their experience? What content they didn’t find useful on the website? How can the company improve user experience?

A brand or company should select the customer data platform suitable for their brand/company. The criteria to select a customer data platform are:

- Geography: Different customer data platforms have different privacy, security standards.
- Integration: Different customer data platforms support different platforms.
- Agreement: Different CDPs supports different platforms, some are suitable for mobile phones whereas some are not.
- Data improvement: customer data platforms should be capable of collecting data from different sources.


Customer data platforms aim at optimizing the offers and messages to customers from the marketing team by analyzing or making a customer database. Not only the marketers but experience teams, can customer support also benefit from CDP. The customer data platform helps various managing teams involved in a business to create more accurate sessions, better user environment, build specific segments of the user, etc.

Personalization Engines targets individual customers and tracks their activity to help the brands improve their customer experience. Personalization engines are a means to provide user data to the brands so that they can select the type of content, messages, offers to deliver to the user.

CDP enables POS (Point Of Sale) integration, which means that both the customer’s related information and stock related information are stored at one place which is taken care of by Enterprise Resource Planning (ERP). Let us understand this by an example, suppose a customer A buys something from a store and the transaction is successful. Now every time the customer A visits the store and pays for it, they will complete a POS (Point Of Sale). Whereas, personalization engines don’t offer POS integration.

CDP offers a complete view of the customer’s activity and provides every detail of it. In other words, it provides complete information about the customer. It’s not the same in personalization engines. It doesn’t provide a 360-degree user view. But advanced personalization engines do provide dynamic information about the customer.

CDP’s are more concerned about the data storage but supports unstructured data storage. It does not allow any repetition of data or it removes the data which is no longer needed. Whereas personalization engines allow duplication of data. CDP’s have a data cleansing process, unlike personalization engines because they deal with big data or unstructured data. To organize and analyze big data, data cleansing is needed.

Personalization engines as the name itself indicate, tend to provide more personalized user experience than a customer data platform. A personalization engine is mostly used to enhance the web experience for users.

Unlike personalization engines, CDP’s do not offer artificial intelligence (AI) and machine learning (ML). And this is an advantage of personalization engines as most of the customer demands are met by advanced personalization engines because they possess artificial intelligence and machine learning. 

CDP’s can handle big data and can analyze unstructured data which makes the process of extracting useful data easier.



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