Explain "time series analysis" in business analytics.

Time series analysis is a statistical technique used in business analytics that focuses on evaluating data points collected at specific intervals over time. This method allows analysts to identify trends, patterns, and seasonal variations within data, enabling more informed decision-making and forecasting.

For instance, businesses can utilize time series analysis to track sales data month by month, revealing trends such as seasonal spikes in certain products. This insight helps companies to adjust their inventory and marketing strategies accordingly. Additionally, by analyzing the historical performance of various metrics, organizations can make predictions about future performance, which is crucial for strategic planning.

The other options refer to different analytical approaches. Evaluating retail performance focuses more on performance metrics rather than the temporal analysis characteristic of time series. Similarly, analyzing customer demographics is more about segmenting the customer base instead of examining changes over time, and measuring employee performance metrics, while potentially time-related, does not encapsulate the broader methodology and objectives of time series analysis as well as option B does.