Algorithmic adjustments refer to the changes made to computer algorithms to improve their performance or accuracy. These adjustments can involve tweaking the rules or parameters that guide how the algorithm processes data. For example, a social media platform might adjust its recommendation algorithm to show users more relevant content based on their recent interactions. These adjustments are essential in various fields, such as machine learning and data analysis, where algorithms learn from data over time. By refining these algorithms, companies can enhance user experience, increase efficiency, and make better predictions, ultimately leading to more effective outcomes in areas like marketing and customer service.