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Recommendation types in Elevate

Different recommendation types behave differently depending on ranking, stock availability, personalization, and merchandising rules. This article explains how recommendation types interact with Elevate’s ranking and recommendation logic.

Use the table below to understand the behaviour of each recommendation type before adding it to a Recommendation List. Each column describes a specific characteristic that may affect how results appear on your site.

Recommendation type Includes out-of-stock products Affected by missing image Affected by Exposure strategy Affected by Boost / Bury Fill up slots Soft deduplication
Top products Yes* Yes* Yes Yes Yes Yes
Personal No Yes Yes Partially Yes Yes
Alternatives No Yes Yes Partially No Yes
Upsell No Yes No Partially Yes** Yes
Cart No Yes Yes Partially Yes Yes
Style with No Yes No No No No
Favorites No Yes Yes Partially Yes Yes
Newest products Yes* Yes* No No Yes No
More from series Yes* Yes* Yes Partially No Yes
Recently viewed Yes No No No No No
Add-to-cart recs. No Yes No Partially No Yes

* Out-of-stock and missing-image products are included but demoted according to the Out of Stock and Bury Missing Image settings in the Elevate application.

** Upsell can return an empty result if no in-stock products exist within the same gender and age groups, although this is very rare.

Partially under Boost / Bury means the algorithm is influenced, but other strong signals, such as personal affinity, may limit the visible effect. Both Boost / Bury and Exposure strategy affect the same algorithms because both work by adjusting a product’s entity score.

Fill up slots means the recommendation type will almost always have products to display within any applied filters.

Soft deduplication means Elevate attempts to reduce repeated products across recommendation lists where possible.

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