Smarter green nudging leads to reduced product returns
Precision-targeting with causal machine learning maximises effectiveness of nudging and prevents backfiring.
What unsustainable behavior needs to change:
There are two kinds of returns one can make while online shopping: ‘Real returns’ (where the customer genuinely intended to keep the purchased item), and ‘opportunistic returns’ (where the customer orders several options of the same product, with the intent to return at least one item back (e.g., same shirt in two different sizes)). However convenient these return-options may be, the rate at which one frequents these options can be costly for the environment. Every return means using more fossil fuels on transportation and waste management, as well as emitting more greenhouse gas emissions.
To better understand how to prevent such behaviours while, the authors tested a website feature aiming to target informational, awareness and norm barriers. Additionally, While the team also wanted to tap into the power of green nudging, green nudges have previously evoked varied effects on different customer segments; with some even backfiring and leading to increased undesired behaviour and smaller profits for online retailers. So, to reduce this unintended risk and increase the website’s effectiveness, the experiment needed a prediction mechanism that would help identify which customers are best targeted by a digital green nudge.
The Green Nudge:
Using a large German fashion retailer’s website as their testing ground, the authors targeted specific customers to demonstrate the effectiveness of their nudge. Upon checking out, the basket page had an informational prompt showing the environmental costs of returns. It was shown not just once, but again as a reminder after check-out, with a prompt asking how committed the customer is to reducing returns – using a 5-point Likert scale.
The decision algorithm, which identified which customer segments to target, was trained using the retailer’s basket data, digital footprints (e.g., IP locations, browser), and publicly available aggregate data.
The result: The smart green nudge targeted 95% of customers, resulting in a 3.8% decrease in product returns compared to a baseline ’naïve‘ nudge and a 6.7% decrease compared to no nudge at all. This led to significant environmental and financial savings for both the business sector and society as a whole.
Are you aware of any other nudges that help to reduce online shopping returns?? Feel free to get in touch: hello@green-nudges.com
From Diana Chiang, a Behavioural Insights Specialist at Social Change, a B-corp certified marketing agency. The ‘Smart Green Nudge’ for reducing online product returns, was developed through a collaboration of independent consultants and researchers from Goethe University and the University of Mannheim; with backgrounds in economics, human-machine interaction, and data science from the Leibniz Institute for Sustainable Architecture for Finance in Europe.
