Glossary
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This article provides a comprehensive list of terms used throughout the platform. If you identify any missing terms, please email us at .
Automated and personalised product suggestions based on variable-based algorithms. There are two types of recommendations:
Recommendations on website
Recommendations by mail
The strategic organisation and display of products on a website’s category pages.
The process of linking tools such as CMS, analytics, or marketing automation platforms to the AB Tasty Recommendations & Merchandising platform to retrieve data and configure recommendations and merchandising settings.
Pre-set or customisable formulas used to determine the types of products recommended to users based on variables.
All individuals who navigate to the website.
Visitors who are shown the personalisation experience on the website.
Individuals who both see and interact with the personalisation experience.
Pre-set or customisable areas on the website where personalisation experiences are displayed. These placements define the variables that algorithms can use.
Pre-defined or customisable elements that enable the retrieval of information to be used in algorithms for configuring experiences.
Criteria applied to algorithm parameters to refine the displayed product results. Filters use properties and operators and can be dynamic when based on variables.
Special criteria applied to adjust algorithm results based on specific conditions. Exceptions use a “when” clause to define triggers and apply specific filtered algorithms.
A feature that randomises the order of products shown in experiences, ensuring users see a varied selection with each visit.
Products explicitly promoted or prioritised in recommendations and merchandising configurations. Highlighted products are always displayed at the forefront of results.
A tool that lets users view and interact with a recommendation or merchandising setup before it is published.
A set of protocols and tools that enable integration and data exchange between AB Tasty Recommendations & Merchandising and other platforms.
A feature that provides detailed performance metrics for personalisation experiences, including clicks, revenue impact, and user engagement.