OnVoard Product Recommender

พัฒนาโดย OnVoard

Frequently Bought Together, Also Bought, Recently Viewed

Product Recommendations as a Revenue Engine

Majority of ecommerce visitors go to an online store without knowing what they want to buy beforehand. As a merchant, you can add product recommendations to suggest, guide, and convert these visitors into customers.

For users that are already buying, product recommendations can help boost average order value (AOV) with cross-sell recommendations like "Frequently Bought Together" and "Customers Who Bought This Also Bought".

Why choose OnVoard Product Recommender

1) Meta Labels
The number one differentiation is that our product recommendations come with an option to display meta labels. Meta labels like "25% of customers bought this together" serves as social proofs to convince customers WHY they should add the product to cart. Meta labels can be customized according to each recommendation logic and make product recommendations more compelling .

2) 14 Types of Product Recommendations

Gain access to our rich library of product recommendations. With a single subscription, you gain instant access to over 14 recommendation logics for all product recommendations use cases. Each recommendation logic can be easily set up in a plug-and-play manner.

Below are types of product recommendations that we provide.

Frequently Bought Together
Also Bought
Similar Items
Recently Viewed
Handpicked Items
Best Selling
Trending
Selling Fast
Selling Out Soon
New Arrivals
Discounted Items
Top Rated
Recently Sold
Recently Reviewed

Other Key Features

Style Editor: Customize product recommendations based on your store design.
Auto Placement: Automatically install product recommendations widget to your site without code modifications.
Filtering: Use filters to exclude products based on rating, num reviews, inventory quantity, tags, etc.
Revenue Tracking: Identify assisted revenue generated from product recommendations.
Analytics: View analytics for each recommender to identify top-performing product recommendations.

Demo Store

Go to Demo Store and see live demo on how product recommender works.

How to Get Started?