In current merchandising strategies, we often focus on popularity or sales volumes. This works in many cases, but it doesn't account for returns.

A product that sells frequently but is returned just as often damages:

• profitability,
• logistical efficiency,
• and sustainability.

By linking return data through Returnless, we can actively influence these products within the ranking for the first time.

How does it work?

Example:

• Product A: 100 sold, 60 returned → Net sales: 40
• Product B: 80 sold, 5 returned → Net sales: 75

Current situation: product A is shown higher because it was sold more often. New situation: based on return percentage, product B gets priority.

Before you begin

For now, this is a manual process. In time this will be automated.

• Select a running period, for example the past 30 days
• Returnless data should be available for the selected period
• Event Tag data should be available for the selected period

Step-by-step plan

1. Collect sales data via Tweakwise
2. Retrieve return data via Returnless
3. Calculate return percentage and use it

1. Collect sales data

Implement Tweakwise Event Tag, see Event Tag introduction on your platform.

2. Retrieve return data

In Returnless, run an export from the returned items for the selected period. See Returnless → Export.

3. Calculate return percentage & use it

By combining sales data and return data, we can calculate a return percentage per product.

The result of this combination should be stored somewhere Tweakwise can import it and imported:

• Create a standard attribute ext-returnpercentage.
• Create an attribute import for this created attribute.
• Start the attribute import.

The ext-returnpercentage can now be used in your merchandising formulas.

Future

In the future, we're going to automate this process. Until then this is a manual step.