Optimizely is an AI platform for creating and optimizing digital experiences. It is aimed at marketing and digital teams, and its own wording also refers to experience-makers, marketers, customer experience users, and agent experience users. The page says it helps teams create content fast, test and personalize experiences, and prove business impact.
Three named products anchor the platform. Agentic CMS is described as helping users publish faster and keep a site performing its best automatically. Agentic Experimentation is for continuously testing, personalizing, and optimizing, with a stated focus on proving impact. Agent Platform automates tasks, removes bottlenecks, and scales work without adding headcount. The page also says Optimizely can monitor, measure, and optimize how content is used by large language models, and it presents this as part of an “Agent Experience.”
Optimizely says the platform integrates with existing tools and “slots straight into your existing stack.” It is presented as a single platform with “three paths to growth,” and the page includes links for products, plans and pricing, roadmap, integrations, partners, services, resources, developers, and support. The page does not spell out pricing or licensing terms in the main text, but it does surface a Plans & pricing area in the site navigation. The site also says the platform is trusted by more than 10,000 brands, naming Nike, Zoom, Salesforce, Alaska Airlines, Visa, Admiral, and Santander.
In the Content optimisation space, Optimizely takes a focused approach. It helps marketing and digital teams efficiently create, test, and optimize digital experiences to improve business outcomes. It is built as a B2B product for marketing teams. Optimizely is paid. It ships for the web.
Optimizely builds and maintains Optimizely. Among its 5 catalogued features are A/B testing, personalization, and AI content creation. The interface is available in 4 languages, including German, English, and Norwegian. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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