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RichRelevance

Recommendation Placement Best Practices

Optimize Recommendation Placement to Maximize Conversion

Having recommendations visible at each step of the shopping process-from the homepage through to purchase confirmation-fuels personalized navigation and helps to build a continuous personalization experience. Integrations with site-wide recommendation placement see significant incremental revenue when compared to lighter implementations (recommendations limited to a few pages).

Placement Best Practices

Because recommendations generate greater ROI than other nonnavigation elements, prioritize placements accordingly, moving less profitable elements down if necessary.

  • Be flexible with your format. Recommendation sets can be vertical or horizontal in orientation to accommodate multiple placements. Verticals can be tucked under navigation menus, and horizontals can be easily placed under product descriptions.
  • Each recommendation set should display at least three products (except custom product pairing recommendations, which usually display two or more products).
  • At least one recommendation set should be placed above the fold. This initially viewable information encourages shoppers to scroll through the rest of the page where additional sets can be found.

Optimal Number of Recommendation Sets by Page Type

Number of Recommendation Sets Page Type
3

Product Detail

Cart

Add to Cart

2+

Home Page

Category

Purchase Confirmation

1+ Search Results

Why Use Multiple Recommendation Sets on a Page?

  • Broaden your appeal to a wide range of customers, improving the likelihood that customers will find what they are looking for.
  • Increase your ability to accomplish a variety of business objectives such as up-sell, cross-sell, replenishment, custom
  • pairing, etc.
  • Significantly increase the probability of conversion.
  • Provide additional opportunities for the RichRelevance. personalization engine to learn what strategies perform the best on individual pages, so we can continually deliver optimized recommendations.