Login



Personalized Product Recommendations for Website

Product Recommendations that captivate your customers

Predict the next purchases of your visitors

Show website visitors relevant product recommendations based on artificial intelligence algorithms. The AI algorithms will select the products your customers will want to buy.

Increase purchase probability

Recommendations will be displayed on the website and app based on user behavior and preferences. It is real-time personalization. Show products that are more likely to engage the buyer at the moment.

Increase average check

Offer products often bought together to increase the average check and maintain customer loyalty. Users find such AI recommendations useful and willingly interact with them.

Keep the visitor on the website

Heat visitor activity on your website by showing personalized offers based on the persons’ behavioral data: website activity over a certain period of time, viewed items, response to campaigns, average check. Keep in mind that retaining a customer is more cost-effective than acquiring a new one.

Configure recommendation settings without developers

You can build a recommendation strategy on your own. Set recommendation display conditions, hierarchy, and placement in a few clicks without developers or code editing.
Our Case Studies
Custom
Custom AI solution helped a photo editor increase the income by 17%
With the customer base growing, RetouchMe faced an increase in the churn rate. To avoid attrition, they had to focus on high-value customer retention. Our AI solution helped identify potential VIP customers with 99% accuracy and eventually increase VIP customers by 35 % and the quarterly income by 17%.
Custom
Case: Custom AI solution helped a photo editor increase the income by 17%
Case: Custom AI solution helped a photo editor increase the income by 17%
Case: Custom AI solution helped a photo editor increase the income by 17%
Omnichannel
Omnichannel workflows helped an online retailer recover 92% of abandoned carts
An online jewellery retailer 925.ua wanted to encourage more cart abandoners to complete a purchase. With automated omnichannel workflows, they managed to use emails and web pushes within one abandoned cart strategy, and drove back 92% more shoppers to the online store.
Omnichannel
Case: Omnichannel workflows helped an online retailer recover 92% of abandoend carts
Case: Omnichannel workflows helped an online retailer recover 92% of abandoend carts
Case: Omnichannel workflows helped an online retailer recover 92% of abandoend carts
Triggers
Optimization of triggers for an eCommerce stimulated revenue growth by 44%
A cosmetics brand Aromateque wanted to generate more transactions using promotional campaigns. With behaviour-based triggers, they automated their promo emails which resulted in customer lifetime value increase and revenue growth by 44%.
Triggers
Case: Optimization of triggers for an eCommerce stimulated revenue growth by 44%
Case: Optimization of triggers for an eCommerce stimulated revenue growth by 44%
Case: Optimization of triggers for an eCommerce stimulated revenue growth by 44%
Artificial intelligence algorithms will pick the best combination of product recommendations
The recommender system collects and analyzes customer data, such as last purchases, viewed products, and items added to the cart. Machine learning helps constantly increase the relevance of displayed goods and optimize ineffective compilations from the previous product recommendations.
Simple web tracking setting
Set website tracking in 3 steps
Install on your website a web tracking script generated by the platform that collects user data in real time. Use this data for segmentation and personalization to test hypotheses and find out which type of customer recommendations works best.
Tracking script for the site
Flexible recommendation settings
Create personalized recommendations for each client
You can set different conditions for recommendation display on different website pages:
  • previously browsed products;
  • most popular products in the category;
  • most popular products on the website by order or views;
  • items that are often bought with those the visitor is interested in;
  • recommendations based items that have been added to the cart, etc.
Select a page for recommendations
Use ready modules
Add ready modules to each website page
Select the placement for your recommendations, and our script will do the rest. All you need to do is to choose the page for product recommender blocks (main, category page, product page, cart, 404 page) and their type:
✓ Also bought;
✓ You may also like;
✓ Popular on the website;
✓ Bestsellers;
✓ Similar products;
✓ Personal recommendations.
Product Modules
Manage recommendation display on your own
Thanks to flexible settings, your product recommendations will be even more accurate. You can apply filters to the product categories that should not be shown together, or set the conditions for display of the recommended product category in specific product cards.
Product offer segmentation
Testimonials

Every day 3,500 customers get more online sales with Yespo automated industry-specific campaigns

NPS based on 2361 customer votes
8.5 out of 10
Personalize everything: channels, website, app, pop-ups, promo codes
Using the customer data platform send personalized recommendations in the way that is the most convenient for your subscriber
Advanced Segmentation makes it equally possible to use contact data in dynamic content for:
Adding a block with the best offers
Any Questions?
We’re always happy to help!
Discount services
Schedule a Call
Fill in the form, and our specialists will call you back as soon as possible.
Discount services
Chat Support
We’re waiting for your questions!
Discount services
Email
Contact the support team