Product Recommendation add-on

A successful product recommendations strategy combines three elements:

  • Collecting the right shopper and product data to show shoppers the most relevant products.
  • Delivering the most suitable recommendation type for the shopper’s stage in the purchase journey.
  • Fine-tuning recommendations to meet your business needs.

The APSIS One Product Recommendation add-on is a self-service tool with an easy-to-use wizard which allows users to create real-time Product Recommendations for Email and Web. Once the snippet is placed and the Product Recommendation is set, it can be edited through the Product Recommendation tool. Example: Filter it to trend flip flops during summer.

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Your Product Recommendations asset will be populated with products that reflect the behaviour of your website visitors. That behaviour is your asset's logic. To learn more about the Product Recommendations Asset Logic, click here.


 

 

  How to use the events


People like you buy: It’s based on the fact that people who’ve had similar preferences in the past will tend to like similar things in the future. These recommendations derive from actual behaviour and don’t rely on machines understanding the exact nature of each product. By including a header such as ‘People like you buy…’, users also appeal to consumers’ desire to follow the wisdom of the crowd and feel part of a tribe. This is a great general-purpose recommendation type for use on many different types of web pages from the homepage to the product detail page and in emails. It helps shoppers at the research stage of the buying journey, where they might not know exactly what they’re looking for.


Purchased Together: Shoppers are reminded of accessories and complementary items that they might have forgotten when they filled their cart. This is an ideal recommendation to increase order value at the checkout, after the cart page. It’s also a great way to add value to post-purchase emails, by showing shoppers the products that they are likely to want and need directly after their original purchase.


After viewing this, people bought: Similarly to “People like you buy…”, this type of recommendation leverages the fact that people who share a preference for one product are likely to agree on other products too. It anticipates the products that are most likely to lead to a conversion. This lets users show a larger amount of their product inventory to web browsers. Shoppers get to see popular items that they might not have thought about when they made their initial search.


The use of social proof: This recommends products that are trending with other shoppers. These are:

  • People frequently browsed
  • People frequently carted
  • People frequently purchased - bestsellers

When making a purchase decision, consumers prefer to follow the wisdom of the crowd and choose similar products to their peers. Users can add popularity messaging to increase urgency and reinforce the idea that these items are generating a buzz with fellow shoppers. These suggestions can work well for shoppers whose preferences users don’t yet know. Since these products are popular with existing shoppers, there’s a fair chance that they will appeal to new shoppers too. Labelling products as ‘trending’ or ‘most popular’ boosts the power of social proof recommendations.


You frequently browsed: This type of recommendation is particularly effective because it reminds shoppers about products that they are already interested in, but haven’t carted yet. This is a great way to engage busy shoppers who might have been distracted before carting their favourite product. It also harnesses the power of familiarity – shoppers tend to prefer products they have seen multiple times. Users can use this recommendation type on the homepage and in personalized marketing emails to target frequent browsers who haven’t yet made a purchase.


You frequently carted: As already mentioned, shoppers are more inclined to purchase a product they are already familiar with that has been under their radar for a while. Like “You frequently browsed”, this type of recommendation is particularly effective because it reminds shoppers about products that they are already interested in, have carted, but haven’t completed the purchase yet. Users can use this opportunity to retarget their shoppers by including a “call to action” button on a reminder e-mail, bringing them to the website. Offering discounts, help, and links to Q&A through “Your frequently carted” e-mails and adding this information on the website are common retargeting practices.


You frequently purchased: You can add filters to show products from the same category of products the shopper frequently purchased from your shop. If they like one product from the category there is a big chance they would like to try out similar products.

 

What if you the Profile does not contain enough data to select the products to be displayed as a recommendation?

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For this, we have Fallbacks. They can complete the recommendation in case there is not enough data for all the assets defined. The primary fallback source will be the first to be considered when in need of more products for your asset, due to your primary logic not having enough data. The secondary fallback source is considered whenever the primary fallback still can't provide the data needed to fill the Product Recommendations asset. Read more about how to use Fallbacks here.

 


 

About the PR Pixel

To use the APSIS One Product Recommendation add-on, despite having the APSIS One Tracking Script installed, you will need to have our Ecom pixel installed in your webshop. This pixel is a sort of insurance policy for the script. It makes sure that we always capture the email address for the purchase and can attribute back your ecommerce revenue.

It is only implemented on the “Thank you” page for purchase. The APSIS consultancy team is responsible for installing your user's unique script via Backoffice.

Have in mind that the Product Recommendation Pixel is NOT the same as the APSIS One Tracking Script.

 


 

Wanna see it in action?

Book a demo or submit a request to try APSIS One!

 

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