Large discounts on sites like Groupon hurt sales

Large discounts on sites like Groupon hurt the sales of small to medium-sized businesses, according to research from Rotterdam School of Management, Erasmus University (RSM).

This is because, for less well-known merchants, discounts are often considered a signal of low quality.

The researchers monitored the hourly sales of 19,978 product and service deals listed on in 172 cities in the US and Canada. They found that a one percent increase in a deal’s discount decreases sales by 0.035–0.256 percent. If a merchant offers a 10 percent discount, the sales decline by 0.63–4.60 percent which is between $42–$275 in revenue.

Zike Cao, lead researcher and assistant professor in business information management at RSM said: “One-sixth of Americans aged 12 or above register for at least one daily deal service, like Groupon or LivingSocial. Surprisingly, we found that the site’s large discounts don’t improve the sales of listed products. This is especially prominent among credence goods, such as medical treatments and car repairs, because it’s difficult for consumers to know the true value of these services. The consumer reasons that if the product or service is good, it doesn’t need a large discount.”

Bringing in positive third-party reviews from Facebook or Yelp can lower sales even further.

Cao continued: “Positive reviews combined with large discounts make things worse. They reduce sales. We think people become suspicious if a product or service with many positive reviews is still offered with a large discount.

“If businesses want to use daily deal platforms to attract new customers, they should give reasonable discounts, but not very large ones. It’s also a good idea to use a flexible discount rate, whereby all customers get higher discounts when more sales are made. So, people who purchased the deal early, get some of their money back later if certain sales thresholds are reached. And finally, don’t display third-party reviews if you offer a large discount.”

The research was carried out with Kai Lung Hui and Hong Xu of the Hong Kong University of Science and Technology and was published in July 2018.