Personalization engines allow companies to personalize marketing, sales and other aspects of customer experience to optimize a company's relationship with each customer. If we take a website as an example, the layout, use of colors, messages on the page, promotions and products showcased on the page can be personalized to increase sales.
Since the 90s, it became clear that companies have the necessary capacity and technology to go beyond the traditional segmentation approaches that segmented customers into a few buckets. Today, companies universally aim to serve each customer with a customized approach designed to optimize the company's relationship with the customer.
Personalization pays off. For example, personalized recommendations account for 74% content watched on Netflix according to McKinsey&Company.
Personalization solutions typically leverage machine learning algorithms such as collaborative filtering which relies on the choices of similar individuals. Due to constraints of specific personalization applications such as scarcity of feedback, time sensitivity, managing a dynamic catalogue and a dynamic user base, companies test different approaches in this field including multi-armed bandits and other new approaches
To be effective, personalization solutions need to have access to data on the experiments performed and their results so they can improve based on the available data. To achieve this, personalization solutions integrate with analytics software as well as software that manages interaction with customers.
Personalization is also called individualization, one-to-one (1-1) marketing or segment of one. Personalization engines are also called personalization systems or personalization software
Compare Personalization Engines
AIMultiple is data driven. Evaluate 32 products based on comprehensive, transparent and objective AIMultiple scores. For any of our scores, click the icon to learn how it is calculated based on objective data.
Qubit Pro's enterprise-grade data processing and open ecosystem allow personalization to solve some of the biggest marketing and business challenges. Bring together multiple data sources in real-time to create contextual and relevant 1:1 personalizations.
Evergage's real-time personalization and customer data platform (CDP) enables companies to leverage behavioral analytics and machine learning
Optimizely is the world's leading experimentation platform, empowering marketing and product teams to test, learn and deploy winning digital experiences
Monetate Intelligent Personalization Engine
Monetate is the world's most trusted experience optimization and 1-to-1 personalization platform.
Sailthru Experience Center
Sailthru is the first truly proactive marketing automation platform designed to optimize the digital experience for individual customers and for brand revenue
Searches with brand name
These are the number of queries on search engines which include the brand name of the product. Compared to other product based solutions, personalization engine is less concentrated in terms of top 3 companies' share of search queries. Top 3 companies receive 64% (15% less than average) of search queries in this area.
Personalization engine is a less concentrated than average solution category in terms of web traffic. Top 3 companies receive 72% (5% less than average solution category) of the online visitors on personalization engine company websites.
Number of Employees
Median number of employees that provide personalization engine is 110 which is 47
more than the median number of employees for the average solution category.
In most cases, companies need at least 10 employees to serve other businesses with a proven tech product or service. 26 companies (22 less than average solution category) with >10 employees are offering personalization engine. Top 3 products are developed by companies with a total of 501-1,000 employees. However, all of these top 3 companies have multiple products so only a portion of this workforce is actually working on these top 3 products.