IBM Forecasts ‘Early Christmas’ in U.S. Consumer Electronics and Appliance Sales
Powerful analytics point to growing importance of “Black Friday” and “Cyber Monday”
ARMONK, N.Y. (October 21, 2010) – Holiday sales of consumer electronics and appliances in U.S. retail stores are expected to get an early start this year, with consumers spending a larger-than-usual share in November, according to an analytics-based forecast produced by IBM (NYSE: IBM). The findings have important ramifications for retailers preparing for their most important season of the year.
Proven to be accurate to 99 percent, the forecast relies on 19 years of historical data and sophisticated analytics software developed by IBM to analyze both long-term trends and seasonal peaks. IBM consultants use these predictive techniques to help clients improve performance by addressing complex issues of supply and demand. These techniques also aid clients in planning product mix and new store locations.
According to the forecast, sales of consumer electronics and appliances are predicted to total $10.164 billion this November, representing a four percent increase over November 2009. Consumer electronics is expected to total $8.688 billion with appliances coming in at $1.476 billion.
In December, sales of consumer electronics and appliances are predicted to total $13.800 billion, representing a four percent increase over December 2009. The December 2010 forecast breaks down as follows: $12.197 billion for consumer electronics and $1.603 billion for appliances.
Especially important is the forecast’s analysis of the change in sales from month to month, a strong predictor of relative strength. This year, the sales momentum going from October into November is expected to be much stronger than in previous years, while the momentum from November to December is forecast to be weaker than in the past.
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(Graph: http://www.newscom.com/cgi-bin/prnh/20101021/NY86146 )
“The forecast indicates that retailers should be ready for a robust Black Friday and Cyber Monday,” said Global Business Services partner and IBM retail analytics leader Michael Haydock, referring to the Friday and Monday following Thanksgiving. “Retailers that staff up and stock up for November and invest in advertising are likely to have a substantial advantage in the marketplace.”
Following is the month-to-month breakdown of the November/December forecast for consumer electronics and appliances (numbers in billions):
Retail electronics and appliances
| November | December | 2-month total | ||
| 2008 (actual) | $10.129 | $13.639 | $23.768 | |
| 2009 (actual) | $9.754 | $13.252 | $23.006 | |
| 2010 (forecast) | $10.164 | $13.800 | $23.964 | |
Following is the month-to-month breakdown for consumer electronics only (numbers in billions):
Retail electronics
| November | December | 2-month total | ||
| 2008 (actual) | $8.671 | $12.041 | $20.712 | |
| 2009 (actual) | $8.289 | $11.687 | $19.976 | |
| 2010 (forecast) | $8.688 | $12.197 | $20.885 | |
Following is the month-to-month breakdown for appliances only (numbers in billions):
Retail appliances
| November | December | 2-month total | ||
| 2008 (actual) | $1.458 | $1.598 | $3.056 | |
| 2009 (actual) | $1.465 | $1.565 | $3.030 | |
| 2010 (forecast) | $1.476 | $1.603 | $3.079 | |
Haydock noted that disposable income, as reported by the U.S. Commerce Department is on the rise, as is the household savings rate, perhaps indicating pent-up consumer demand.
In producing the forecast, IBM uses economic data gathered by the U.S. Census Bureau. The data is derived from a survey of retail store establishments engaged in electronics and appliances as their major line of business. These store establishments are a representative sample and are not inclusive of all industry activity in this category. Products include TVs, cell phones, personal computers and tablet computers, radios and stereos, refrigerators, dishwashers, ovens, and other devices.
For more information, visit www.ibm.com/gbs/bao.
| Contact: | John Buscemi | |
| IBM | ||
| 914-766-2607 | ||
| jbuscemi@us.ibm.com | ||
Source: IBM
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