Recommendation is key

Recommendation is key

Why display recommendations for every genre of music when the customer is only interested in Jazz?
Global product recommendations can be relevant, but it’s important to always try to customize the customer’s experience in your store and reduce “litter”.

Green Flying Panda studies each customer’s activity information and patterns to build customized recommendations – this way, they only see what actually interests them!

Remember – customers are unique!

Custom Built Recommendation Engine

Green Flying Panda features a custom engine that allows you to customize recommendations based on any customer attributes you define

Base recommendations on customers’…

Purchase History

Place recommendations based on previous customer purchases

Specific Products

Place recommendations based on the products you specify – this option is useful to target specific products in a campaign

Current Product

Place recommendations based on the product that the customer is viewing

Levels of Recommendation

Starting from the product based on the recommendation source above (A), define how wide the extension should search to find product recommendations (B).

In other words, customers who view product A will see recommendations for product B – the following levels define how the product B will be chosen.

Directly related

Recommends product B, given that customers who bought the product A also bought the product B.

After order only

Recommends product B, given that customers who bought product A also bought product B in their next order.

In this case, product B can refer to accessories or maintenance items for product A that your customers will possibly need.

Two levels

Recommends product C, which is the most purchased product along with product B (and product B is the most purchased along with product A).

This feature widens the range of products that your customer will view and makes associations that aren’t always noticeable.

Customer attributes

Combine customer attributes to get specific and accurate recommendations!






Based on Customer’s Activity

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Products with common attributes

Lists products with the same attribute as other products viewed by the customer.

For example, if a customer sees a lot of Nokia smartphones, recommended products will include all Nokia products.

Related from last completed order

Lists all products related to products in the customer’s last completed order.

If the customer bought a smartphone, the products displayed will be the ones related to that smartphone.

Related products from all previous completed orders

Lists products related to the ones purchased in all the customer’s previous orders.

Products in shopping cart

Lists all products in the customer’s abandoned shopping cart.

Products in a category

Lists products in a specific category defined by you.

Products in customer’s wishlist

Lists products in the customer’s wishlist.

Most viewed products

Lists the most viewed products by the customer.

New products

Lists products most recently added to your store. These are the products marked “Set as new from” in your catalog.

Meta Information

In each of these recomendation options, you can customize specific values for important meta information.

Number of products

Define the number of products displayed in the recommendation widget

Sort results

Recently added
Price ascending
Price descending

Activity date

Define recommendations from and to dates so you don’t have to manually activate or remove them

If no results…

Define what attibute the extension should use if the recommendation source you choose doesn’t find results for a certain customer.

Most views

Customer’s most viewed products


Define a certain product category to display


New items in your store