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Temperature, Snowfall Key Factors; New York, NY (-9%), Chicago, IL (-7%), and Detroit, MI (-7%) Among Those With Greatest Regional Decline
Washington, D.C. (PRWEB) February 13, 2014
Applied Predictive Technologies (APT) today announced an analysis of retail sales across the United States for the month of January using data from the APT Index. The APT Index shows a -1.6% decrease in nationwide retail sales during January 2014, compared to the same month last year. The decrease was driven by fewer transactions, as fewer people went shopping in the cold and snowy weather.
The APT Index includes a subset of APTs $2 trillion in sales data, or $1 of every $5 of US retail sales. The Index aggregates data from sales registers at over 50,000+ locations across the US to show how year-over-year performance changes for same store sales in the physical channel for retail. Unlike other sources, which use consumer survey data, the APT Index is based on reported sales data, allowing APT to make statistically significant observations about sales trends. As a result, the APT Index provides the most definitive and accurate retail sales analysis available.
January Retail Sales by APT Index numbers:
The big picture
At a more granular level, the APT Index shows that areas with certain characteristics were impacted more in January. Among these characteristics, the magnitude of the temperature change and snowfall change had the largest impact.
Impact of the temperature change on retail sales
Impact of the change in snowfall on retail sales
Metro areas most affected
The Top 25 metro areas where retail sales were hit the hardest in January included New York, NY (-9.0%), Chicago, IL (-7.1%), and Detroit, MI (-6.7%). The APT Index also includes data on other areas around the country.
[All figures are a year-over-year, same-store comparison between January 1st through January 31st, 2014 and the same dates in 2013.]
Anthony Bruce, CEO of APT, said, We found the extreme temperatures of the polar vortex period and overall cold and snowy weather throughout January resulted in a decrease in the months sales compared to last year. These weather factors are beyond anyones control, but by using predictive analysis, retailers can learn from such impact and use controllable actions, such as promotions or operational changes, to plan for the future.
Bruce added, Using the APT Index, we can provide the industrys most definitive retail comps data for major weather events, at the macro level as well as for each local market. The APT Index shows how small changes in factors like the weather can dramatically impact store comps. The APT Index is one of the most robust and accurate ways for retailers to answer questions, such as: What should any given stores performance be, based on how nearby stores are doing? How can we determine if some stores are really over- or under-performing, or if their performance is due to whats happening in their local area? How do we perform compared to surrounding stores when we run a national ad campaign? We are seeing a lot of excitement among retailers in using the APT Index to answer these and other mission critical questions.
For more information, visit: http://www.predictivetechnologies.com.
APT is the worlds largest purely cloud-based predictive analytics software company. APTs Test & Learn software is revolutionizing the way Global 2000 companies harness their Big Data to accurately measure the profit impact of pricing, marketing, merchandising, operations, and capital initiatives, tailoring investments in these areas to maximize ROI. APTs client portfolio includes Walmart, Staples, Lowes, SunTrust, Hilton Hotels, and others. APT has offices in Washington, D.C., San Francisco, London, Taipei, and Tokyo. Visit http://www.predictivetechnologies.com to learn more.
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