Marketplace Order Returns

The Marketplace Orders Returns dashboard will help you understand the volumes and values of online orders that are returned after purchase. Along with the trends of how many returns are made, and the values of them you will see how each reason for return is affecting your returns - and you will see the trends for each of your shipping locations. This data can help you understand not only how purchase returns affect your profits, it can also help you find opportunities for training and operational adjustments.

Your analysis starts with a couple of basic Key Performance Indicators (KPIs), and how those KPIs are allocated by reason for return. If your operation includes pre-owned items, you will also see the KPIs allocated by New and PreOwned condition.

It is important to note that the data considered begins with the date on the heading panel of the dashboard, under Earliest Transaction Date.  This means that your trends and filtered data will start with the transactions on this date. Also to note is that this dashboard is based on Order Date and since the order process updates over time, you will see the current status of the orders as the data is updated each day.

You will see a link to this document in the top of the dashboard, under the heading Dashboard Help. 

KPIs

The KPIs are simply the number of orders and value of orders, as filtered by the date range and a number of other characteristics available in the filter pane to the right. This will give you a quick glance at the volumes you are analyzing and allow you to change the filters to understand the impact each has on the KPIs. The allocation is shown in the graphics so you can get a quick idea, for example, of the percentage of orders returned for a specific reason, and the corresponding value of those orders. Each of the graphics can be used as a dashboard filter, simply click on the section that interests you and the rest of the dashboard will filter to that selection.

Graphic Displays

For each of the graphics, keep in mind that you can filter the dashboard to focus on specific locations, adjustment categories & reasons, and the date range. You may want to look at the performance of certain shipping locations, for example, and understand their level of returns - or you may have instituted operational changes and want to understand if the changes impacted the level of returns in a positive way. Understanding why your customer are returning purchases can lead you to changes that positively impact your profits and increase customer satisfaction at the same time.

The first two trend graphics will show you the volumes and values of purchases returned, by reason for return. Here you can see which reasons are more or less prominent as an overall comparison, and how they are trending over time. If a particular reason is dominating, it might cause the rest of the graphic to be difficult to analyze since the values are relatively small - you can click on the legend below the graphic to toggle each reason on & off, this will bring the graphic into sharper focus.

The next set of trend graphics will show you how the volumes and values are trending over time. Here, instead of breaking by the return reasons you can compare the trends on volume vs value on the same graphic. Where are the trends similar and where do they vary? Using the filters to narrow the focus on the return reasons, or the shipping locations, you can start finding opportunities for improvements. Below the trend graphics you will find a column chart that shows, by shipping location, how the returns by reason compare. Here again, if one particular reason dominates the graphic, consider using the filters to exclude that reason to see the others come into sharper focus.

The data tables at the bottom allow fields to be added or removed from the pivot tables. Right click in the header or rows to add or remove fields from the table. By adding or removing fields you can see your data at a high level or with the detail you need for your analysis. 

Any data tables can be quickly exported to a spreadsheet for further analysis. Do this by clicking on the 3 dots at the top right corner of the widget, choose Download and export an image or file.  The recommended file type for a spreadsheet is CSV.