Cannibalism and Complementary Effects in Retail
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Two types of statistical models that are well known in machine learning are Discriminative models and Generative models. Discriminative models […]
Novelty Detection: Finding New Classes of Anomalies in Complex Processes
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Detecting new classes of anomalies when monitoring a high-dimensional data space is known as novelty detection. This is a special […]
Know This: Demand Patterns vs. Purchasing Patterns in Retail
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There’s a lot of jargon swirling around the retail technology industry, and differentiating terms for the uninitiated can be more […]
The Challenges of Time-Series Forecasting in Retail
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While demand forecasts are never perfect, they are an absolute necessity for most retailers. Good forecasting helps to ensure that […]
Aggregated Market Basket Analysis and Tricky Analytics
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In one of my previous blogs, I addressed the question on how granular the analyzed data in retail analytics should be. There is a tangible cost resulting from..
Retail Analytics – How Granular Should You Get?
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With the emergence of big data technologies and the availability of new data sources, one of the main questions concerning analytics is …
How Conventional Sales Benchmarking Fails Retail Analytics
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Growing retail sales takes intelligence. Keeping close account of how sales are tracking against norms can provide critical insights and help define better sales…