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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, digital commerce, and service and support.

• Algonomy Digital Experience Personalization
  4.3

  82 Reviews

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, semantic and visual), merchandising (automation, configuration and curation of business rules) and product recommendations. These applications also provide catalog navigation (including SEO keyword automation and guided selling assistants). Personalization, optimization and analytics capabilities should also be available. Platforms are deployed as SaaS. They provide administrative tooling to enable digital commerce roles (merchandisers, content managers and search specialists) to support customer experiences via no-code. With the emergence of generative AI, conversational search and guided selling assistants are now appearing. Search and product discovery applications can provide the digital customer journey from landing on a website or app to finding the correct product and adding to basket. Search results can be highly visual, using engaging layouts and multimedia. Content other than product information, such as educational information, compliance materials, customer reviews and related news may also be included in search results to engage customers and further support buying decisions.

• Algonomy Digital Experience Personalization
  3.5

  2 Reviews