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Amazon Resistant Retailers See Bright Future


amazon-logo-wallpaperTwo worlds of retail are emerging.

One group of retailers outperformed the S&P 500 by 23% over the last 22 months, while a second group lagged badly behind, beating the S&P by a mere 9% during a period of rapid escalation of retail stock prices, according to work by William Blair & Co. analysts.

The crucial difference: the first group is Amazon Resistant. This is based on product overlap and price comparison with Amazon, and on the relative convenience of shopping at the retailer – is rated as having below-average risk of losing market share to Amazon. This group includes Walgreens, Cabela’s and T.J. Maxx.

The second group has above-average risk of losing market share to Amazon and includes Best Buy, Vitamin Shoppe and Sears. For them the future is a bit murky.

Amazon’s amazing sales growth is obviously coming at the expense of other retailers. Identifying which ones – and which ones have credible defenses to Amazon – is crucial to making wise decisions about retail stocks, or in the case of wholesalers – which ones to give credit to.

In Cabela’s case they have built one of retail’s most sophisticated  customer-tracking and analytics programs in the industry.

As a result, Cabela’s sales at its 44 stores average $370 per square foot, while the typical big-box sporting goods store averages closer to $200 per square foot. Five smaller, so-called “next generation” Cabela’s stores— which range between 80,000 and 100,000 square feet—topped $500 per square foot in sales in 2012.

All this data creates one of the best flows of information on someone who is involved in camping or hunting. They may live in remote Wyoming, but Cabela’s knows precisely how much they spend on an annualized basis. Their data gives them the precision to locate stores like no one in the industry.

And that’s how retailers become Amazon resistant. Using data and analytics to mirror customers interests and amplify convenience. Pretty smart.

Thanks to Jeff Bailey, a Y Charts contributor, for specific data used in this article.

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