RecoAI. Recommendations that keep
your customers happy – and keep them
Today’s e-commerce environment is fiercely competitive. With the limitless choice available at a click of a button, your customer today might become your biggest competitor’s customer tomorrow. And every lost customer is a lost opportunity for growth. In a landscape like that, you need every advantage to stay ahead.
RecoAI is a recommendation system powered by AI – it connects customers on your website with the products they want by analyzing their real-time behavior.
Now, how can it make your business grow?
Recommendations reliably lead to increased sales – even by 35%!
A satisfied customer is a repeat customer. According to some studies, 75% of customers who made a successful purchase thanks to recommendations are twice as likely to return to your website in the future.
31% of retailers do not use recommendations at all. 90% of companies using recommendations use slow, old-fashioned recommendation systems.
We’re way ahead of our competitors.
This is what sets us apart
from other recommendation solutions:
We are much faster than other recommendation systems – our engine processes 4 times more information about customers’ real-time online activity, in a comparable time than other solutions on the market.
It’s real-time – which means it is never outdated. Our system constantly monitors the ongoing customer activity on the site and creates tailor-made recommendations delivered in just the rightmoment of the customer journey
RecoAI was designed with your customer’s privacy in mind – we do not store vast quantities of past data and rely on real-time customer behavior on your site instead.
More trust means more confidence in your products and services.
Want to see RecoAI in action?
Schedule a demo now!
A battle-tested solution
for Ministry of Health
They trusted us
These brands and institutions have trusted us in our previous venture – LogicAI:
LogicAI is a reliable partner. They’ve created a complex solution, a framework that made it possible to prepare recommendations based on our users online behaviours. After implementation, we were able to achieve CTR up to 30% higher. We see its potential in suggesting our clients what they might like and we are eager to see the further development of the product.