Between 30% and 250% in conversion driven by recommendations.
Between 50% and 300% in CTR driven by recommendations.
Our technology is designed to ensure maximum scalability. On average, 95% of our requests are served in under 40 milliseconds.
Between 100% and 400% in average time on site.
There is no cost-per-click nor set up fee. We only charge a small fee when we get you a sale.
RecoMind integrates seamless with popular e-commerces platforms like Shopify, WooComerce, Magento, BigCommerce, etc. With other retailers, we typically make the integration in less than two weeks.
This recommender helps retailers to display the products that a user is more likely to buy.
This solution works very well on a personalized home page or newsletter.
It estimates the recommended products based on the user shopping history, using machine learning.
This recommender has the objective to increase the chance of users to buy, when they are on a product page.
In addition to considering the shopping history of the user, the recommender takes into account the current product to estimate which products to recommend.
This recommender is designed to facilitate cross-selling and cart expansion.
It is typically displayed in the shopping cart page, just before check out.
The scenario analyzes the cross-selling behavior of the retail and produces a recommendation adapted to the the current user.
This recommender provides an alternative to avoid losing a sale. It works well for down-selling and out-of-stock alternatives.
The scenario can be used in email marketing for retargeting, in an out-of-stock page or displayed in the check out page.
It provides substituting products based on similar price, brand, features or visual appearance.
We are 100% focused on customer success, so we only get paid if we get you a sale. Our solution is actually free for you.
There is no CPC, or set up fee. We just charge a small fee for every product we help you to sell.
This is how it works: we connect a tracking pixel to every product we recommend, at the end of the month, we will send you an invoice for the products that users have bought using RecoMind.
We helped US-based company AutoIntel to improve their automotive recommendation platform. With a dataset of 34 million users interacting with 1600 different car models and options and around 8 billion positive and negative interactions, we explored how different recommender algorithms can analyze customer behavior, increase customer engagement and drive sales.
A large consultancy in the US wanted to recommend training courses to their employees. With 25000 employees and around 62000 courses, our team tested a suite of 6 different text-based recommenders until find the most appropriate for the customer's dataset. We obtained a boost in employee engagement and course conversion.
A large retailer in the UK wanted to provide alternatives when a user was looking for a product that was out of stock. The recommended alternatives generated by our team had into account the visual appearance of the product and the past buying history of the user. We improved customer engagement, click-through rate and conversion rate.