A national retail chain wants its digital transformation to rely less on intuition and more on data. Which situation best shows how data can simultaneously improve decision-making and generate new business value for the company?
Refactoring the e-commerce platform into microservices so new features can be released faster
Archiving product images to a lower-cost Cloud Storage class to cut long-term storage expenses
Lifting and shifting on-premises virtual machines to Compute Engine to reduce maintenance overhead
Mining point-of-sale records to find customer buying patterns, then delivering personalized offers that raise sales and enable paid vendor promotions
Deriving insights from customer purchase data allows the retailer to move from assumption-based marketing to evidence-based actions. By detecting buying patterns, the company can decide which promotions will resonate with each shopper, increasing conversion rates. The same insight can be packaged as a paid, vendor-sponsored promotion program, creating an additional revenue stream. The other choices focus on cost savings or engineering efficiency rather than turning data into insights that directly drive decisions and new value.
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What is data mining in the context of retail?
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What are paid vendor promotions, and how can they generate new business value?
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Why is evidence-based decision-making better than intuition in retail?
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What is data mining in the context of retail?
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How does personalized marketing impact sales?
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What are vendor-sponsored promotions, and how do they generate revenue?
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