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 are used for modeling the dependence of unobserved target variable y on observed variables x. In particular, these models aim to estimate the conditional probability P(y|x) for the target variable given the observed variables. Thus, […]
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 case of anomaly detection that can be extremely important in many real-world applications. Some examples for novelties are: a new class of customers that behave differently from others yet share common properties; a new manufacturing […]
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 than a little confusing, especially when you’re deciding on a solution to keep your business competitive. In this short article, we’ll be focusing on the two most popular terms that refer to wildly different services–‘consumer […]
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 retailers can supply the right product at the right time and location, maintain adequate inventory levels while avoiding stock-outs, reduce the chance of obsolete inventory, and improve price and promotion management. Many of the traditional […]
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…
