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Top 1 Personalization Engines SaaS Companies $100M+ Revenue (September 2026)

As of September 2026, Latka tracks 1 personalization engines SaaS companies with $100M+ in annual revenue. They have combined revenues of $474.2M and employ 1.2K people.

Every company below sells personalization engines software to other businesses and is ranked by its most recent annual revenue. Revenue, funding, headcount and customer figures come from CEO interviews on the Latka podcast, public company filings, and Latka estimates where a company has not disclosed a number.

What Personalization Engines SaaS Companies do

Personalization engines are software tools designed to deliver customized content and experiences to users based on their individual behavior, preferences, and historical data. These engines utilize algorithms and data analytics to tailor interactions in real-time, enhancing the overall user experience. Common use cases include personalized marketing campaigns, tailored product recommendations, and customized user journeys across digital platforms. Typically, personalization engines feature capabilities such as user data collection, behavioral analysis, and integration with various marketing and customer service tools. They are primarily utilized by marketing teams, product managers, and customer experience professionals who aim to boost user engagement and conversion rates by providing targeted content and recommendations. By leveraging user data, these engines enable organizations to create more relevant and meaningful interactions with their customers.

Companies
1
Revenue
$474.2M
Funding
-
Employees
1.2K

Filters

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Top Personalization Engines SaaS Companies $100M+ Revenue

Showing 1 of 1 companies ranked by annual revenue.

1RTB House logo
RTB House

Warsaw, Poland

RTB House is a global marketing technology company that provides retargeting and programmatic advertising solutions for online businesses. The company was founded in 2012 and is headquartered in Warsaw, Poland, with offices in more than 30 countries. RTB House's proprietary technology uses deep learning algorithms to analyze user behavior and predict their purchasing intent, enabling businesses to deliver personalized and relevant ads to potential customers. The company's solutions are available for desktop and mobile devices, and its customers include e-commerce companies, travel companies, and other online businesses across a variety of industries. With a focus on innovation and data-driven solutions, RTB House is helping businesses reach their target audiences more effectively and drive better results from their digital advertising efforts.

Revenue
$474.2M
Year founded
2012
Team size
1.2K

Frequently asked questions about Personalization Engines SaaS Companies $100M+ Revenue

How many personalization engines SaaS companies with $100M+ in annual revenue are there?

Latka tracks 1 personalization engines SaaS companies with $100M+ in annual revenue. Together they generate $474.2M in annual revenue and employ 1.2K people.

Which personalization engines SaaS company with $100M+ in annual revenue is the largest?

RTB House is the largest, with $474.2M in annual revenue, founded in 2012.

How much revenue does a typical personalization engines SaaS company with $100M+ in annual revenue make?

The average personalization engines SaaS company in this list makes $474.2M a year, across 1 companies with reported revenue.

Who are the leading Personalization Engines vendors with $100M+ in annual revenue?

Ranked by annual revenue, the leaders are RTB House.

Related Marketing Software categories

All Marketing Software SaaS categoriesEvery category we track inside Marketing Software, each ranked by revenue.Browse every SaaS industryThe full A-Z of SaaS categories Latka tracks, from Personalization Engines to everything else.

Inclusion Criteria

- Must offer real-time data analysis to personalize user interactions - Should integrate with existing marketing and CRM platforms - Must provide capabilities for A/B testing and performance tracking - Should include features for user segmentation based on behavior and demographics - Not just for content delivery; must also facilitate personalized recommendations and user journey mapping