Throughout this chapter, you have been building visualizations to provide insight into the operational performance of our e-commerce website. It can also be useful to understand the customers' views and the factors that might drive them to the website. This type of information is traditionally most useful for product or marketing folks. However, it can also be useful to gain an understanding around whether an item is increasing in popularity and if this could ultimately lead to additional customers and heavier load on the site.
In this recipe, you will write a Splunk search to calculate the average amount of money spent, split out by product category. You will then graphically present this data using a bar chart on a new Product Monitoring dashboard.
To step through this recipe, you will need a running Splunk Enterprise server, with the sample data loaded from Chapter 1, Play Time – Getting Data In. You should be familiar...