Insight engines apply relevancy methods to describe, discover, organize and analyze data. This allows existing or synthesized information to be delivered proactively or interactively, and in the context of digital workers, customers or constituents at timely business moments. Products in this market use connectors to crawl and index content from multiple sources. They index the full range of enterprise content, from unstructured content such as word processor and video files through to structured content, such as spreadsheet files and database records. Various "pipelines" are used to preprocess content according to type, and to derive from it data that can be indexed for query, extraction and use via a range of touchpoints. Insight engines differ from search engines in terms of capabilities that enable richer indexes, more complex queries, elaborated relevancy methods, and multiple touchpoints for the delivery of data (for machines) and information (for people).
Gartner defines personalization engines as software that enables marketers to identify, deliver and measure the optimum experience for an individual customer or prospect based on their past interactions, current context and predicted intent. Personalization engines help marketers identify, select, tailor and deliver messaging such as content, offers and other interactions across customer touchpoints in support of three primary use cases: Marketing: Delivering the right message to the right audience and in the right context to maximize marketing and advertising performance. Digital commerce: Tailoring content, offers, recommendations and experiences across digital sales channels. Service and support: Customizing online and offline experiences across business functions to reduce customer effort or increase customer satisfaction and advocacy.