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titleNew Name: Marketing Cloud Personalization

Interaction Studio (formerly Evergage) is now known as Marketing Cloud Personalization. The new name reflects our mission and vision for innovation in Salesforce Marketing Cloud. We wish we could snap our fingers to update the name everywhere, but you can expect to see the previous name in various places until we replace it.

With Variations, you can modify the returned results such that end users will see a larger breadth of items. For example, you can configure a variation force a recipe to show at most two items from the same primary category. This means if a visitor was very affine to the "hats" category, instead of seeing just hats, they would see only the two most relevant hats and a variety of other items from different categories.

titleThis Article Explains

This article provides an overview of the process for adding variations at the recipe-level.  Also, please refer to related articles for information on creating recipes, and adding ingredientsexclusions and boosters.

titleSections in this Article

Table of Contents

Create a Variation

  1. Create a new recipe or edit an existing recipe
  2. On the Variations tab, click Add a variation to select the variation from the drop down; scroll to see all options


    You may add only one randomized and one dimensional variation per recipe.

  3. Adjust configurations for the variation as needed
  4. Click  to delete a variation
  5. Click SAVE to save your recipe

    Your recipe must have a unique name and at least one ingredient before you can save it

Variation Descriptions and Configurations

DimensionalVaried such that a limit is set on the number of items with the same primary tags or categories which can be returned in recommendations. The primary category or tag is taken to be the first one in the list on products, articles or blogs. This exclusion can only be used with products, articles and blogs.
  • Item Type - Categories or a tag type. Choose which dimension to vary.
  • Item Limit - The maximum number of items that share the primary category or tag. This value can be at most one half the number of maximum recommendations returned in the dataset.
RandomizedVaried such that the results are randomized for each user. All other recipe rules still apply, and boosted recommendations will generally still show up first.
  • Randomization Time Period - The time period in which the same user would get consistent recs. Available options are:
    • One Second
    • One Minute
    • One Hour
    • One Day
    • One Week
    • One Month