Voyado's solution proved that you simply can’t beat the speed and relevance delivered through the use of AI technology.
Jens Malmqvist
Store Optimisation Manager, Dustin
Voyado acquiries Apptus - because two are better than one |
Find out moreProduct recommendations
Voyado Elevate Recommendations make shoppers more likely to complete their purchase, contributing to cross-sell and up-sell. Recommendations are provided in real-time and products are suggested based on the collective interest as well as the unique visitor’s history.
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Personalised product recommendations in real-time
Real-time recommendations suggest products based on the collective interest of all your site visitors as well as the unique visitor’s history.
Personal recommendations are based on what the current visitor has clicked or bought, on what other customers have bought, and on items currently in the cart or that were previously abandoned.
Boosting cross-sell and upsell
To increase the average order value, the recommendations feed the e-commerce site with both alternatives as well as supplementary product recommendations
The recommendations capability can be used omnichannel, for example in Email recommendations.
What our customers say
The solution allows us to maintain an e-commerce site offering great customer experience, where it is easy for customers to find the products or inspiration they need.
Rickard Lyko
CEO and Owner, Lyko
Our site ran like clockwork throughout Black Friday with 100% availability. We are very pleased that we took the decision to take the leap to Voyado Cloud!
Mikael Olander
CEO, Bygghemma group
I said to my team, let’s see what the performance looks like after a year, does it still have this growth or is it flat? We saw that in September that we were 30% up again compared to September last year!
Thomas Fehn
CIO & CDO, Brødrene Dahl
Inspire with the best-selling products
These recommendations display real-time popular and trending products. They are suitable on the start page to welcome visitors, on category pages to show popular products for the specific category and on the No Results page.
Recommendations based on customer
Recommendations based on customer are site-wide personalised recommendations based on individual behaviour such as products the visitor has seen or bought. You can use them on the start page to make the visitor feel more “at home” and on the No Results page.
Give abandoned products another chance
These are customer-based recommendations of products from the customer’s abandoned cart. The system remembers the visitor's previous intentions and gives these products a new chance.
Remind about viewed products
Recently viewed products are another type of customer-based recommendations that work as a reminder of previously viewed items and allow the customer to return to products after viewing similar ones.
Promote supplementary items
Inspiration from people with similar tastes is one of the main drivers for purchases. Recommendations based on those who bought also bought can be used on product detail pages.
Inspire with alternative and supplementary products
Recommendations based on product is a more advanced variant that uses visitors’ behaviour from the whole site to select product recommendations. Both alternative and supplementary product recommendations are provided.
Increase the cart value
There is a golden opportunity to recommend products based on the items in a visitor’s cart. These recommendations are used for both cross-sell and up-sell, and to push the order value above a certain limit by recommending products that will pass the threshold value.
Benefit from visitors with similar tastes
Shoppers often search for items that go well together. Inspire them by offering products that other people bought after looking at the same product.
Let visitors benefit from crowd wisdom
You can inspire and benefit visitors looking at a specific product by using recommendations based on products that other people found after viewing the same product.
Recommendations based on favourites
A customer adding an item to their favourite list says a lot! Take advantage of this information and give your customers personalised product recommendations based on their favourites.
