Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.
As the pressure of intensifying competition mounts, retailers and restaurateurs are looking to reduce costs across the supply chain while boosting customer loyalty. And with consumer influence now stronger than ever, businesses that fail to respond to the demand for improved products and services will feel the impact on their sales figures. Central to this is the pervasiveness of the social, mobile, analytics and cloud (SMAC) era that is redefining traditional retail models that place the consumer at centre-stage.
I fondly remember watching as a child “The Roadrunner Show” cartoon series where the coyote (Wile E. Coyote) was devising elaborate schemes to try and catch the roadrunner. Although his schemes appeared to be clever and creative (to a six year old at least), he always failed. So, in one of the episodes he ordered a giant mainframe type super computer (this was the 1950s after all) to apply “data science” to devise a more effective scheme. This time his prey was Bugs Bunny.
Machine learning is a subfield of data science that involves the use of algorithms and computing systems capable of learning on their own from new data as it becomes available, identifying patterns and automatically adapting to predict or anticipate future outcomes with an increasing degree of accuracy. For marketers, what this means is the ability to predict customer behaviour and make relevant and personalised offers on the fly to acquire, retain or grow your most profitable customers.
Traditionally, the first quarter of any calendar year sees a dilution of both collection and recovery yields given the overspend that occurs over the December holiday season. Therefore, optimal strategies and operational execution are key to mitigating the effects of the first quarter ‘hangover’.