April 18, 2013, 9:39 AM

A larger average order size helps Overstock boost Q1 revenue

Sales increase nearly 19% to $312 million, the web-only retailer says.

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Sales increased 18.9% year over year in the first quarter for Overstock.com Inc. The web-only mass merchant reported today that revenue reached nearly $312.0 million, up from $262.4 million in the first quarter of 2012.

A 21% increase in average order size, to about $153 from $126, boosted Q1 revenue, Overstock says. It also said there was a “small decrease” in the number of customer orders.

Overstock is No. 27 in the Internet Retailer Top 500 Guide. Its CEO, Patrick Byrne, recently returned to his job after taking a medical leave of absence.

For the quarter ended March 31, Overstock also reported:

• Gross profit of $58.9 million, up from 24% from $47.5 million in the first quarter of 2012.  “The increase in gross profit was primarily due to higher revenue and a shift in product sales mix into higher-margin home and garden products, and lower warehousing costs, partially offset by higher freight costs,” Overstock said today when reporting its financial results.

• Net income of nearly $7.7 million, up 185.2% from $2.7 million for the same period last year.

• Sales and marketing expenses of $18.7 million, up 29% from nearly $14.5 million last year. Most of the increase stems from more spending on search marketing, Overstock says, as more of its revenue is originating from that channel.

• Technology expenses of nearly $18.2 million, up 16.7% from $15.6 million. Overstock says most of the increase comes from a jump in unspecified “staff-related costs.”

• General and administrative expenses of nearly $15.1 million, up 2% from $14.8 million.

Company officials during a Thursday conference call attributed the Q1 gains to a variety of factors. Among them are better online marketing, improved recommendations for shoppers visiting the e-commerce site and the use of data to craft more lucrative pricing on items. “Real time big data is driving all kinds of things,” Byrne said, using a term that refers to analyzing the vast amounts of data collected online about consumers and shopping.

 

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