Cannibalism and Complementary Effects in Retail

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

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

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

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

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?

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

Growing retail sales takes intelligence. Keeping close account of how sales are tracking against norms can provide critical insights and help define better sales…