Gartner defines personalization engines as technology that enables marketing professionals to identify, set up, conduct and measure the optimum experience for an individual based on knowledge about them, their intent and context. Personalization engines apply context about individual users and their circumstances to select, tailor and deliver messaging such as content, offers and other interactions through various digital channels in support of three use cases: Marketing: Delivering the right message to the right audience and in the right context (i.e., tone, timing and channel) to maximize marketing and advertising performance. It involves behavioral inference, segmentation, testing, targeting and optimization of marketing campaign content, messaging and engagements across marketing and communication channels. Digital commerce: Tailoring content, offers, recommendations and experiences across digital sales channels. It includes personalized site search and navigation and customized content across homepages, category landing pages and product detail pages, with the goal of increasing conversion and delivering online revenue growth. Service and support: Using customer insight, journey context and user feedback (i.e., surveys and stated intent) to customize online and offline experiences across business functions to reduce customer effort or increase customer satisfaction and advocacy.
Gartner defines Search and Product Discovery as applications that augment digital commerce solutions to facilitate navigation, filtering, comparisons, and ultimately selection of products. They provide search (keyword, natural language and visual), merchandising (automation, configuration, and curation of business rules to make a product discoverable based on business needs), product recommendations, catalog navigation (and SEO keyword automation), personalization and analytics capabilities through SaaS to enable customers (B2C and B2B) to transact. They also enable providers (merchandisers, content managers, and search specialists) to support customer experiences. With the emergence of generative AI, conversational search interfaces are now appearing. Search and Product Discovery applications use product data to facilitate navigation, filtering, comparisons and ultimately product selection. Search results can be highly visual, using engaging layouts and multimedia. Content other than product information, such as educational information, compliance materials and related news may also be included in search results to engage customers and further support buying decisions.