OnVoard: Product Recommender

About OnVoard: Product Recommender

Built by OnVoard

Email :

Description

Frequently Bought Together, Recently Viewed

14 Recommendation Logics - Plenty of product recommendation options to help you showcase related products.
Product Upsell - Use logic like frequently bought together for product upsell and boost average order value.
Social Proof Personalization - Generate more sales by adding social proofs to personalize product recommendations.

Why choose OnVoard Product Recommendation
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.

Below are some examples:
- Frequently Bought Together: 25% of customers bought this together
- Also Bought: 7.6X more likely to buy
- Selling Out Soon: 3 units left
- New Arrivals: Added 5 hours ago
- Recently Sold: Last Sold 3 hours ago
- Recently Viewed: Last Viewed 5 mins ago

2) 14 Types of Product Recommendations
Gain access to our rich library of product recommendations. Each personalized recommendations 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

Pros

Provides a comprehensive set of 14 recommendation logics, allowing for diverse and personalized product recommendations
Enhances sales through product upsell features like 'Frequently Bought Together' to boost average order value
Integrates social proof personalization to increase sales, with meta labels like '25% of customers bought this together' to encourage purchases
User-friendly setup with easy plug-and-play functionality for personalized recommendations
Includes meta labels that provide additional information and create urgency, such as 'Selling Out Soon' and 'New Arrivals'

Cons

Potential reliance on meta labels may not work effectively if customer data or purchase behaviors are not accurately tracked
The effectiveness of recommendations may vary depending on the industry and specific customer demographics
Some users may find the multitude of recommendation types overwhelming if not clearly organized in the backend
If integration with existing systems is complex, initial setup might be time-consuming for some users

Rating And Reviews

Cvlaikos

May 01, 2024 on Wix

good

Dpotzn

Dec 10, 2023 on Wix

50/50It does work and helps increase revenue, however it significantly slows down your website leading to lost sales (we've been contacted by a few frustrated customers who've given up). We're still evaluating whether...