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Overview

Product recommendations predict and display products your contacts might be interested in purchasing. 

Ometria has 7 recommendation engines for use in your campaigns. 

For product recommendation criteria, rules, edge cases and product data requirements, see Product recommendations overview.

This page explains how to create or edit a product recommendation engine.

Once you've worked through these steps, you might want to read: Add a product recommendation block to a template.

Recommendation engine types

There are seven (7) different recommendation engines.

Some engines are designed for use in broadcast campaigns, others for automation campaigns, as indicated below.

IconEngine descriptionType
Top products - Recommends the best-selling product (by units sold).
Choose to recommend the best-selling products in the past 7, 14 or 28 days.
No context recommendation engines
These can be generated for any contact, without needing to know which products they have interacted with.
We recommend that you use these engines for broadcast campaigns
Latest products - Recommends the products most recently added to your online store.
Similar products - Recommends products most similar to the products the contact has interacted with.
For automation campaigns, the type of interaction depends on the triggering event.
E.g. If the trigger is an order, then the recommendations are based on the product purchased. If the trigger is a visit to a webpage, the recommendations are based on the products viewed.
Product based recommendation engines
These can be used where a contact has interacted with a product/set of products, e.g. abandoned basket or ordered.
These are known as context products.
We do not recommend these engines for broadcast campaigns, as they require data from the contact in order to generate useful recommendations.
Bought this, bought that - AKA 'product up-sell'.
Recommends the most commonly purchased products by customers that purchased any of the context products.
Viewed this, bought that - AKA 'product cross-sell'.
Recommends the most commonly purchased products by other customers in the same session that they viewed any of the context products.

Recently viewed - Recommends products that the contact has viewed in the past 7, 14 or 28 days.
These recommendations display in order of most recent.
Profile based recommendation engines
These are best when the contact receiving the campaign is known.
They generate recommendations based on the contact's behavioural history (products they've purchased or viewed).
Personalised - Recommends products with attributes the contact has shown most interest in ( by viewing or purchasing a product with those attributes).

Create or edit a product recommendation

From the Product Recommendations screen, select CREATE NEW.

The 'NEW RECOMMENDATION INSTANCE' screen displays:

Enter a ‘Recommendation name’, then select a recommendation engine.


Note: If you are using these recommendations in a broadcast campaign, we recommend only using ‘Top Products’ and ‘Latest Products’. 

This is because these are ‘no context recommendation engines’, meaning that no interaction data is required from the contact to generate recommendations. 

Broadcast campaigns typically send to a broader group of contacts who may not have interacted with your brand in some time.


Next, configure the parameters of your product recommendations:

FieldDescription
Time period*Set a time period for the engine to search for products:
  • 7 days
  • 14 days
  • 28 days
Fallback modelThis is used in the event that the primary model (i.e. the recommendation engine you selected) cannot provide recommendations.
We recommend selecting either 'Top products' or 'Latest products', as these should always produce results.
Restrict to category/attributeUsed to restrict recommendations by attribute or category.
Select a category from the dropdown, then select your attributes.
The recommended products may have ANY of the selected attributes (not necessarily ALL of them).
Note: Be aware that the restrictions you set here will not apply to the fallback model you selected (if any).
Restrict to price rangeSet a 'from' and 'to' price so that the contact will only receive the products within that range.
Product blacklistClick and select any products you wish to blacklist from this recommendation.
These products will not be recommended to your contacts.
Attribute blacklistClick and select any categories or attributes you wish to blacklist from this recommendation.Products with these attributes will not be recommended to your contacts.
Default storeRestrict the products recommended to those available in a specified store.
Remove products that have been previously purchasedSelect this to disregard recommendations already purchased by the contact.

* This parameter is only available for 'Top products' and 'Recently viewed'.

Select SAVE to finalise. 


Recommendation preview

Once you are happy with your chosen recommendation engine and the parameters, you can select PREVIEW to see how the recommendations look to recipients.

The preview options are slightly different depending on which type of recommendation engine you are using (no context, product based or profile based).

No context recommendation preview

Select the relevant store (or ‘any store’ for all available products) and hit PREVIEW.

The results display in the RECOMMENDATION PREVIEW window:

Close the preview and make further amendments or select SAVE to finalise.

Product based recommendation preview

Select as many products as you like from the ‘Choose product’ field, then choose your store (if necessary) and hit PREVIEW.

The results display in the ‘Recommendation preview window’:

Close the preview and make further amendments or select SAVE to finalise.

Profile based recommendation preview

Choose your store (if necessary) and enter a contact’s email address to test, then hit PREVIEW.

The results display in the ‘Recommendation preview window’:

Close the preview and make further amendments or select SAVE to finalise.