Behavioral targeting

Increase the conversion rate, average order value and turnover of your website or e-shop thanks to a recommendation system driven by advanced artificial intelligence.

Fulfill customers’ expectations

If you can offer the customer the right goods at the right time, you get his interest and increase the likelihood of entering into a transaction with him. The right recommendation works just as well in-store as on the internet. Our Intelligent Recommendation System is like an experienced salesman who already discerns in the doorway what the customer needs and what more they can sell to him.

Advantages of Intelligent recommendation

  1. Increase in the conversion ratio (number of orders / number of visits to the site)
  2. Increase in the average order value due to the larger number of different products per order
  3. Improvement in the convenience of shopping (easier navigation and goods required)
  4. Widening of the range of recommended goods (not only the best-selling, but goods intended for a narrow target group as well)

How does it work?

The majority of today's e-shops, although they do recommend goods, they approach recommendation wrongly, because they rely on simple statistics or even manual control. They do not offer the customer goods that interests him, but rather the best-selling products, which according to studies, leads to a reduction in the conversion ratio.

Our system is based on an analysis of actual behavior and the needs of users, their segmentation and personalized recommendation of goods.

  1. Collection and cultivation of data - historical traffic statistics, orders, data on goods and our recommended external data sources.
  2. Analysis of historical data - we seek and learn to recognize patterns of user behavior in the data (hence, the often used term behavioral targeting) using machine learning. At the same time, we analyze the goods, their similarities and prices.
  3. Placing the recommendation on the web - immediately after completion of the analysis, artificial intelligence will recommend products based on the type of customer behavior.
  4. Continuous updates and improving recommendations based on new data - the system constantly adapts to changes and trends in the case of involvement of external sources, for example it takes into account the weather or an offer of the competition.

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