THE IMPACT OF RECOMMENDATION ALGORITHMS ON CONSUMER BEHAVIOR IN E-COMMERCE

UDC 339.16
DOI: 10.36871/ek.up.p.r.2025.06.01.027

Authors

Madina S. Shakhbazova,
Beslan R. Alaudinov,
Chechen State University named after A. A. Kadyrov

Abstract

Personal recommendation algorithms restructure the customer’s usual path: they dramatically reduce the time needed to find a product, stimulate the growth of the average receipt, and strengthen the habit of returning to the site quickly. This article examines exactly how these algorithms change the habits and expectations of online shoppers. Special attention is also paid to psychological triggers – the effect of social proof, a decrease in cognitive costs and an increase in the effect of “loss of lost profits.”

Keywords

e-commerce, personalized recommendations, customer behavior, recommendation systems, conversion, personalization, analytics, algorithms