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Making Money is the Objective | Strategic Pricing Solutions

Retail is an inherently low-margin business.  (If you doubt it, just look at Amazon’s return on sales.) To survive, retailers use many tools to determine how they can sell more to customers and at higher prices.  In recent years, data science has become a much more important part of the retail toolkit.  By analyzing how customers make purchase decisions, which factors affect those decisions, and how customer selections affect profitability, retailers can make much more informed and effective merchandising choices.  Those choices include having an array of products to serve multiple segments, including the more price-sensitive buyers, and providing a simple path for each segment to find the products they want.  Those merchandising choices also mean presenting higher priced, higher value alternatives to customers.

When online retailing started, low prices were one of the primary competitive strategies of online retailers.  However, Amazon and other online retailers have learned that customers care about more than just low prices.  They value a broad portfolio of products, service, ease of use, and the ability to find what they are looking for.  The retailers also understand that product placement in their search results is similar to product placement on physical store shelves.  They can and should use a more scientific approach to making those merchandising decisions.  The fact that Amazon is using their considerable data science capability to improve their profitability should be expected.  After all, they are in business to serve customers and to make money.

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Making Money is the Objective.

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