Skip to main content

Top Selling Mobile Phone Handsets in U.S.

The Strategy Analytics ProductTRAX program released its Q3 list of top selling consumer handsets in the U.S. market. Motorola, with its RAZR and KRZR, and LG, collectively accounted for seven of the top best selling consumer handsets.

"Overall the average retail price paid for these top ten handsets was 19 percent higher than the market average; and we continue to see strong upgrade dynamics continue to supplement U.S. market growth," stated Barry Gilbert, Vice President of the ProductTRAX services at Strategy Analytics.

"Motorola, however, despite selling four of the top ten models in Q3, realized an ASP of only $80, nearly 40 percent lower than the group average."

"3G devices accounted for 55 percent of these top selling device volumes. That share will continue to grow during Q4," states Chris Ambrosio, a Director in the Wireless Practice at Strategy Analytics.

"While the iPhone gets the headlines, the Sync from Samsung and the Chocolate from LG quietly stole the show in the category of iconic, 3G feature phones. Samsung, in particular, is well-positioned to dominate 3G sales during the critical Q4 holiday season."

U.S. Q3 2007, Best Selling Consumer Handsets include:

Motorola RAZR V3; Motorola RAZR V3m; LG VX8300; Apple iPhone; LG Chocolate VX8550/8500; Motorola MOTOKRZR K1m; Samsung SGH-A707; LG VX5300; Sanyo Katana II; Motorola V323i/V325i.

Popular posts from this blog

The AI Application Integration Challenge

Artificial intelligence (AI) has rapidly become the defining force in business technology development, but integrating AI into applications remains a formidable challenge. According to a recent Gartner survey, 77 percent of engineering leaders identify AI integration in apps as a major hurdle for their organizations. As demand for AI-powered solutions accelerates across every industry, understanding the tools, the barriers, and the opportunities is essential for business and technology leaders seeking to evolve. The Gartner survey highlights a key trend: while AI’s potential is widely recognized, the path to useful integration is anything but straightforward. IT leaders cite complexities in embedding AI models into existing software, managing data pipelines, ensuring security, and maintaining compliance as persistent obstacles. These challenges are compounded by a shortage of skilled AI engineers and the rapid evolution of AI technologies, which can outpace organizational readiness and...