Based on research by Sri Beldona, PhD, Jeffery P. Radghieri, PhD, and Herbert Remidez, PhD
Sustainable products and practices are at the forefront of current business and community discussions. A growing number of organizations are focusing efforts on providing sustainably sourced and created items to their consumers. As such, companies need to understand the demand patterns of their customers.
Changes to manufacturing and design often go hand-in-hand with price increases, which are typically passed on to consumers. This study looked at the patterns associated with customers’ willingness to pay (WTP) premium prices for sustainable products in the grocery industry, specifically with regards to the quality of the product in question. Additionally, this study demonstrated the inadequacy of traditional methods for understanding customer values, and provided an alternative.
As expected, the results showed that WTP decreased as product price increased, since some customers are more price-sensitive than others. Notably, the study found a significant increase in customers’ WTP with the knowledge that renewable energy was used by the product manufacturer.
Key Points
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Customers are often willing to pay a premium for sustainably produced items, even if it means a sacrifice of quality.
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Marketers need to be specific about what specific aspect of the product is sustainable in order to boost value to customers.
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Using machine learning models to understand customer value shows promise as an alternative to typical market research methods.
Why This Matters
Despite a perceived loss in quality, customers who valued sustainable purchases demonstrated WTP. With this information, marketers can gain traction with sustainably-minded customers, without sacrificing profitability.
Additionally, marketers can use the information in this study to know which specific aspects of product sustainability are of the highest importance to consumers. A product simply being branded as sustainable is likely not going to increase WTP on its own, but specificity about how the product is sustainable (such as manufacturing with renewable energy) may boost its value to a customer.
The decision forest technique used by this study provided more valuable, detailed insight into customer values than traditional research methods, and is accessible to small and medium sized businesses. Analyzing factors of customer WTP using open-access machine learning tools can be a much more affordable—and possibly more effective—alternative for marketers in growing businesses.
Based upon the following peer-reviewed manuscript: Beldona, S., Radighieri, J. & Remidez, H. (2021) Sustainable values and willingness to pay: an analysis of an analytical technique. Journal of Global Business Advancement, 14(2), 216-239.