customers are now more likely to do their shopping on large platforms such as Allegro and Amazon rather than smaller company websites – it’s more convenient for them
on the e-commerce market, it is increasingly difficult to break into the awareness of potential buyers, and this means burned-out budgets for advertising
lack of knowledge about customers’ needs and shopping habits means you can’t effectively personalise your offering, and this is directly related to lower sales and abandoned baskets
unfamiliarity with new technologies inhibits the development of many companies in the e-commerce industry
+10% in newsletter GMV
9% CTR on the webpage
+ 3% CR on the webpage
increase in revenues
while reducing the amount of resources needed
performance in ranking the type of ad in 7 different languages from 7 different countries
profit increase thanks to the reduction of costs of displaying advertisements on unprofitable websites
For seven years we have been creating recommendation systems and teaching our artificial intelligence how to optimise digital campaigns.
Our clients include both large companies, such as Polkomtel, Gemius and RTB House, as well as smaller innovative startups.
During those seven years, we have increased the profits of our clients by even several dozen percent.
We specialise in solutions for the e-commerce industry as well as recommendation and predictive systems.
We combine academic titles with practical knowledge. Our team has been awarded many times and is supported through scientific and business grants.
During the first conversation, we learn about the challenges your company is facing. We try to collect as much information as possible. On the basis of that, we propose dedicated solutions corresponding to the defined needs. Each of our solutions is different. We also specialise in problems that require the use of complex algorithms where standard methods fall short.
We are practically always able to optimise some of the processes in the company based on the data received. If the assumed goal is not achieved, we propose an alternative solution that will be profitable anyway.
After providing the data, it takes an average of 2–3 weeks to build a prototype model and perform simulations in laboratory conditions. As a rule, it is up to the client how quickly the A / B tests can be run under real conditions.
We can always come to an arrangement with the client depending on their budget. Thanks to the scalability of our solutions, the investment in the project is able to pay for itself in a few weeks to several months after its implementation – we know this from experience.
We are in the process of the so-called Fourth Industrial Revolution, during which companies using the latest AI achievements gain the advantage. It is worth going this route in order to retain existing customers and gain new ones. The trend of customer outflow towards large platforms such as Allegro or Amazon is becoming more and more prevalent.