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Custom Recommendation Presets let you define complementary products through category pairs instead of leaning on statistical models. Once you say Category A should recommend items from Category B, every product in Category A gets paired with the item from Category B most often purchased alongside it. You can also layer on similarity parameters — price, manufacturer, or any other product attribute. Maestra Platform offers two variations, both created the same way.

Custom Recommendation Preset

Category-based pairings for a specific product.

Custom Post-purchase Recommendation Preset

Category-based pairings applied to each item in a customer’s most recent order.

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Custom Recommendation Preset

Lets you set complementary products based on category relationships, for a specific item. Once you specify that Category A should recommend items from Category B, each product in Category A gets paired with the item from Category B most often purchased alongside it. Higher-priced items get more recommendations; lower-priced items get fewer.
  • Best used on product detail pages.
  • Works for identified and anonymous customers.
  • Available through the API (recommendation widget) and email.
Good to know:
  • Refresh: once a day.
  • Limit: up to 5 instances per project.
  • Segment: can be limited to a product segment.
  • Auto-filters: checks the product’s area; product external systems match by default.

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Custom Post-purchase Recommendation Preset

This preset only generates recommendations for customers with activity in the last 90 days. Everyone else will see recommendations calculated earlier (if the preset is more than 90 days old) — or no recommendations at all.
The Custom Recommendation Preset applied to each product in the customer’s most recently updated order, with recommendation volume proportional to price. Recalculates in real time based on the customer’s orders.
  • Best used for “Thanks for your order” and “Next purchase suggestion” flows.
  • Identified customers only.
  • Available through the API (recommendation widget) and email.
Good to know:
  • Refresh: real time.
  • Limit: up to 1 instance per project.
  • Auto-filters: checks the product’s area and brand (multi-brand projects); excludes items the customer has already bought.

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How to set it up

1

Open Product recommendations

Go to Content → Product recommendations and click Add mechanic.
2

Choose the preset

Pick Custom Recommendation Preset or Custom Post-purchase Recommendation Preset.
3

Name the preset

Enter a name and click Continue.
4

Configure general settings

  • Recommend for products — the scheduled segment recommendations are built for (optional).
  • Recommend from — the scheduled segment recommendations are drawn from (optional).
  • Recommend only from the same external system — enabled by default; can be turned off.
You can also configure Manufacturer exclusions in the corresponding block.
5

Set up category mapping

Select the category to map, then configure pairs and the number of recommended products per pair.When you specify that products from Category B should be recommended for Category A, each product in Category A is matched with the product from Category B that’s most often purchased together with it.
6

Specify mapping settings

Mapping settings define how recommendations are sorted in the output. If Price is listed first and Manufacturer second, products matching both rank higher — and then are sorted by popularity in orders and views.Select the checkbox in the Exact match block to require an exact match on a field. For example, tick “Color” and only blue products will be recommended for blue products.
The more fields you select, the fewer recommendations you’ll get. Too many constraints can leave you with none at all.
  • Primary category — the category closest to the product.
7

Launch the preset

Activate it. The Product recommendations page shows the preset’s status and the timestamp of its last update.