What is an Outlier?
An outlier is a data point significantly different from other data points in a dataset. In e-commerce, an outlier might be a transaction much larger or smaller than the typical transaction size or a customer with a significantly different purchasing behavior pattern than other customers.
Significance of Outlier in E-commerce
Outliers can significantly impact the results of data analysis. Depending on the context, outliers may represent unusual but important events that can provide insight into customer behavior or business performance.
Outliers can also result from errors or inaccuracies in the data, and including them in the analysis can lead to misleading or skewed results.
Prerequisites for Using Outlier in E-commerce
There are a few prerequisites for using outlier analysis in e-commerce:
- Data: Outlier analysis requires a dataset to be analyzed. In the context of e-commerce, this might include customer purchase data, website traffic data, or other data relevant to the business.
- Goals: It is important to clearly understand the purposes of the outlier analysis and how the results will be used. This can guide the selection of the appropriate data and methodology and ensure that the research is relevant and useful to the business.
- Data quality: Outlier analysis is only as good as the quality of the data being analyzed. It is crucial to ensure that the information is accurate and complete before attempting to identify and analyze outliers.
Use Case With Outlier
Suppose an e-commerce company discovers a high-value customer making a large purchase (AU$10,000) by identifying an outlier. They can use this information to target similar customers and increase revenue by adjusting pricing, inventory, and promotion strategies.