Various types of machine learning algorithms are employed for solving different data science and business problems
Design, build and manage reproducible AI-powered solutions
Recommender models are an essential part of personalized customer offers.
As a tool, it can be used to present every customer with a relevant recommendation or to find the right buyers for specific products.
Solver Search represents a bundle of AI modules used for searching various data types and sources. Currently, there are 3 main modules in different stages of production maturity:
1. Smart Search - used for search of tabular-like data.
2. Document Search - used for search of unstructured documents in pdf format.
3. Image search - used for search of the database of images.
CLV - Customer Lifetime Value
CLV models the future customer monetary value.
The general idea is to estimate how much money can be expected from a particular client, taking into account the previous behavior and purchasing trends.
RFMT segmentation serves to divide customers into groups based on when, how often, and for how much money they buy, without information on what the content of their purchases is. Specifically, segmentation is done based on the following features, calculated for a given time period:
• recency - number of days since the last purchase
• frequency - number of purchases
• monetary_value - the total amount of money spent
• tenure - number of days since the first purchase
Learn more about
Solver AI Models