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Published: September 7, 2012

 
 

Online Retailers, Shipping Fees, and the Bottom Line

How the interplay between delivery charges and product prices maximizes profits.

Title: Pricing for Shipping Services of Online Retailers: Analytical and Empirical Approaches (Subscription or fee required)

Authors: Yuliang Yao (Lehigh University) and Jie Zhang (University of Texas at Arlington)

Publisher: Decision Support Systems, vol. 53, no. 2

Date Published: May 2012

Internet retailers strategically manipulate their base and shipping prices, as well as the delivery options they offer to customers, to maximize profits and gain a competitive advantage, this paper finds.

Online retailers that offer free shipping tend to charge higher base prices for their products, for example, showing that free shipping is often used as a loss leader to attract more customers at higher profit margins. Meanwhile, retailers with a record of delivering their merchandise on time also charge higher base prices but impose lower shipping fees compared with companies that have a poor delivery history. And by adjusting shipping times within a variety of delivery options, some reliably punctual retailers increase their fees for quick delivery service — even as they continue to charge more for their products.

Strategically allocating the total price between the product and its shipping fees is an effective marketing strategy that Internet retailers use to attract customers in an increasingly competitive environment, the authors write. This study is one of the first to explore how companies develop this tactic to improve their viability and profitability.

When delivering merchandise, retailers can (1) offer free shipping by subsidizing the cost themselves, (2) share some of the cost with customers, or (3) turn a profit by charging shipping fees in excess of the actual delivery cost. Because shipping fees are considered the main reason that online consumers cancel their purchases and abandon their virtual shopping carts, charging the appropriate amount is an important mechanism for online retailers to use to attract shoppers and differentiate themselves, the authors write.

For example, leading online retailers such as Amazon and Buy.com have instituted a free-shipping policy with a minimum order amount, as have Walmart and eBay. In contrast, the now-defunct CDnow.com tried to make money through delivery. The company charged US$3 for the first item shipped and $1 for each additional product, which yielded a profit margin of about 15 to 20 percent, similar to what the sale of a CD would bring. Others, such as the accessories clearinghouse Ashford.com, charge precisely the cost of shipping in an attempt to gain customers’ allegiance and trust.

To understand how companies devise the best approach, the authors first developed an analytical model that measured the effects of purchase prices, shipping options, and on-time delivery on the relationship between Internet retailers and consumers. Then they validated the results of the model with an empirical analysis of data collected from Internet vendors selling products from two popular categories: digital cameras and video games.

The authors examined a week’s worth of data from 2005 for the two categories, with digital cameras representing high-end products and video games representing the low end. They looked at the 10 best-selling products in both categories at the time, as ranked by CNET, and tracked 80 Internet retailers that carried them in the United States.

From the retailers’ websites, the authors collected information on base prices, delivery options (including shipping price and estimated time of arrival), and the availability of free shipping, as well as such control variables as whether the retailers also operated physical stores.

The authors gauged the retailers’ probability of achieving on-time delivery by using customer ratings at BizRate.com. The rating on arrival time reflects the companies’ ability to fulfill orders capably in terms of order processing, product handling, and inventory maintenance.

The authors clustered the most extreme companies into two groups: “good” Internet retailers, which had the highest on-time probability, and “bad” ones, which had the lowest. The average rating of on-time probability for good retailers, on a scale of one to 10, was 8.97, significantly higher than that of the bad retailers, 7.98.

 
 
 
 
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