%0 Journal Article %1 gahlod2024impact %A Gahlod, Devashish Sonewane | Om Chopkar | Sumit Yadav | Tejas Burade | Prof. Rutika %D 2024 %J INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT %K Algorithm Collaborative Content-based Customer E-commerce Personalization Recommendation Sales algorithms, engagement, filtering, learning optimization, recommendations, satisfaction, systems, techniques %N 5 %P 607-615 %T Impact of Personalization Algorithms on Beverage Selling Website %U https://www.ijtsrd.com/other-scientific-research-area/other/69423/impact-of-personalization-algorithms-on-beverage-selling-website/devashish-sonewane %V 8 %X The impact of personalization algorithms on beverage selling websites is a crucial aspect of e commerce, as it can significantly increase engagement and sales. Personalization and recommendation algorithms play a vital role in enhancing the online shopping experience, making it more tailored to individual customers preferences. This topic explores the effects of personalization algorithms on online beverage stores, focusing on collaborative filtering and content based recommendations. Collaborative filtering involves gathering individuals with similar interests or characteristics and providing their feedback to users in the same cluster for reference. This approach satisfies customers mentality of referring to others opinions before making decisions. On the other hand, content based recommendations suggest similar items or content that the user has previously searched for, viewed, purchased, or rated positively. The use of learning techniques in recommendation systems can improve the accuracy and scalability of these algorithms. By enhancing personalization algorithms, online beverage stores can increase customer satisfaction, loyalty, and sales. This topic aims to investigate the impact of personalization algorithms on beverage selling websites and explore the potential of collaborative filtering and content based recommendations in enhancing the online shopping experience. Devashish Sonewane | Om Chopkar | Sumit Yadav | Tejas Burade | Prof. Rutika Gahlod "Impact of Personalization Algorithms on Beverage Selling Website" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-5 , October 2024, URL: https://www.ijtsrd.com/papers/ijtsrd69423.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/69423/impact-of-personalization-algorithms-on-beverage-selling-website/devashish-sonewane

@article{gahlod2024impact, abstract = {The impact of personalization algorithms on beverage selling websites is a crucial aspect of e commerce, as it can significantly increase engagement and sales. Personalization and recommendation algorithms play a vital role in enhancing the online shopping experience, making it more tailored to individual customers preferences. This topic explores the effects of personalization algorithms on online beverage stores, focusing on collaborative filtering and content based recommendations. Collaborative filtering involves gathering individuals with similar interests or characteristics and providing their feedback to users in the same cluster for reference. This approach satisfies customers mentality of referring to others opinions before making decisions. On the other hand, content based recommendations suggest similar items or content that the user has previously searched for, viewed, purchased, or rated positively. The use of learning techniques in recommendation systems can improve the accuracy and scalability of these algorithms. By enhancing personalization algorithms, online beverage stores can increase customer satisfaction, loyalty, and sales. This topic aims to investigate the impact of personalization algorithms on beverage selling websites and explore the potential of collaborative filtering and content based recommendations in enhancing the online shopping experience. Devashish Sonewane | Om Chopkar | Sumit Yadav | Tejas Burade | Prof. Rutika Gahlod "Impact of Personalization Algorithms on Beverage Selling Website" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-5 , October 2024, URL: https://www.ijtsrd.com/papers/ijtsrd69423.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/69423/impact-of-personalization-algorithms-on-beverage-selling-website/devashish-sonewane }, added-at = {2025-01-01T11:54:24.000+0100}, author = {Gahlod, Devashish Sonewane | Om Chopkar | Sumit Yadav | Tejas Burade | Prof. Rutika}, biburl = {https://www.bibsonomy.org/bibtex/2ecebb39b68fd06491f57dec9fd0fe9bd/ijtsrd}, interhash = {0199d44d0e869363cea2719b6a39585a}, intrahash = {ecebb39b68fd06491f57dec9fd0fe9bd}, issn = {2456-6470}, journal = {INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT}, keywords = {Algorithm Collaborative Content-based Customer E-commerce Personalization Recommendation Sales algorithms, engagement, filtering, learning optimization, recommendations, satisfaction, systems, techniques}, language = {english}, month = oct, number = 5, pages = {607-615}, timestamp = {2025-01-01T11:54:24.000+0100}, title = {Impact of Personalization Algorithms on Beverage Selling Website }, url = {https://www.ijtsrd.com/other-scientific-research-area/other/69423/impact-of-personalization-algorithms-on-beverage-selling-website/devashish-sonewane}, volume = 8, year = 2024 }