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Warwick Business School: Big data will save your ‘slot’ and make shopping greener

According to an article published on Science|Business, a new operational strategy mining big data to predict when online shoppers want their weekly food shop delivered will not only improve service for customers but boost retailers’ profits by four per cent.

Retailers who offer home deliveries are often working on very tight profit margins since the delivery operation is a significant cost driver; especially if the retailer commits to offering tight delivery time windows in an attempt to increase customer satisfaction and to keep failed delivery attempts to a minimum. Accordingly, they are constantly on the look-out for ways to make deliveries more efficient and greener.  

 
New research by academics from Warwick Business School, Lancaster University Management School and the University of Southampton have devised a new analytic approach that helps retailers to decide when to incentivise customers - by, for example, lowering delivery fees -  in which area and in which time slots all in real time. This will make the future delivery operation more efficient and therefore greener as delivery vans will use less fuel.
 
The new approach was tested using real shopping data from a major e-grocer in the UK over a period of six months and generated a four per cent increase in profits on average in a simulation study, outperforming traditional delivery pricing policies.
 
According to the Institute for Grocery Distribution, online shopping sales of food and groceries are set to increase by 126 per cent over the next five years, taking sales up to £14.6 billion. As tablet and smartphone usage becomes more widespread, shopping online has become quicker and easier and the speed of delivery has become critical in the online fulfilment race.
 
The group of researchers, which includes Arne Strauss, Assistant Professor of Operational Research at Warwick Business School, propose an analytic approach that will predict when people want their shopping delivered depending on what delivery prices (or incentives such as discounts or loyalty points) are being quoted for different delivery time slots. It takes into account accepted orders to date as well as orders that are still expected to come in.
 
Dr Strauss said: “Traditionally online retailers would collect orders including delivery time requests until a certain cut-off time and plan their delivery schedule accordingly. Therefore, maximising profits is a problem because the final set of orders for a given delivery day are not known until shortly beforehand, yet decisions on the pricing of delivery time ‘slots’ have to be made in advance based on an estimate.

 

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