How does this work? 

NOTE: To generate personalized recommendations, we require your store to have at least 10 products, 50 orders, and 100 customers.

Recommendation Types

1. Most popular recommends products that are trending right now and are the current leading sellers. This is a frequently used recommendation type across all online merchants. Presenting the products that the majority of your customers buy is more likely to persuade visitors and customers to make a purchase.
   
2. Recently added recommends products that were newly added to the store.
   
3. Similar products recommends products that are similar to the ones that customers are currently looking at. This is an upselling technique that you can use to persuade your customers to make more relevant purchases on a regular basis. For example, If a customer purchases a polo t-shirt from one brand, we will promote polo t-shirts from other brands in your store.
   
4. Who bought this also bought recommends products based on the customers' previous or current purchases. With such a tailored approach, the customer may purchase more items and the product's value may increase. For example, if two customers A and B have similar purchase histories, this recommendation type will promote products purchased by customer A if customer B has expressed interest in a similar product.
   
5. Bought together recommends products that customers frequently purchase together. For example, if a customer purchases a phone from your store, this recommendation type will promote screen guards or back covers for that particular model because other customers have bought those items together. Because these recommendations are based on the purchases of other customers, they will become more reliable and trustworthy over time.
   

How to add the product recommendation tool to your online store?

1. From the Navigation toolbar, select Ecommerce and click the online store for which you want to add product recommendations.
2. Click Create Promotion under Promotion to create a promotional email for the first time. Click Create in the top-right corner of the page and select Promotional Email to create more promotional emails.
   
   
3. Enter the basic details for the campaign and click Next.
   
   
4. Select a template for the campaign.
   
5. Drag and drop the product recommendation component onto the content.
   
   
6. Choose the product recommendation type to promote your products.
   
   
7. Select the mailing lists and click Next.
   
8. Send your email campaign for review and choose to launch your campaign immediately or at a later time.
   

1. From the Navigation toolbar, select Campaigns and click Email Campaigns.
   
   
2. Click Create Campaign in the top-right corner.
   
3. Scroll down to the Ecommerce section, click the Create New and either select either Regular campaign or A/B test.
   
   
4. Select the store you would like to create a promotional campaign for.
   
5. Enter the basic information about the campaign and click Next.
   
   
6. Select a template for your campaign.
   
7. Drag and drop the product recommendation component onto the content.
   
   
8. Choose the product recommendation type to promote your products.
   
   
9. Choose the mailing lists to send the campaign to and click Next.
   
10. Send your email campaign for review and choose to launch your campaign immediately or at a later time.

Product Recommendation Summary 

1. From the Navigation toolbar, select Ecommerce.
   
2. Click on your online store for which you've used product recommendations.
   
3. On the Summary tab, scroll down to find Product recommendations - Summary.
   

1. Revenue generated via recommendation - This is the sum of the total revenue generated for every product selected from a recommendation panel and ultimately purchased. Revenue calculated is inclusive of shipping charges, tax, or any discount applied at purchase time.
   
2. Impressions - This is the total number of products promoted via the recommendation panel in the emails.
   
3. Clicks - This is the number of clicks made by the users on the various products recommended by the tool.
   
4. Click-through rate - This is the percentage of the users who've clicked on products recommended by the tool.