eprintid: 673
rev_number: 18
eprint_status: archive
userid: 14
dir: disk0/00/00/06/73
datestamp: 2014-12-05 14:50:16
lastmod: 2015-05-29 20:18:15
status_changed: 2014-12-05 14:50:16
type: report
metadata_visibility: show
item_issues_count: 0
creators_name: Caravenna, L.
creators_name: Dewynne, J.
creators_name: Farmer, C.
creators_name: Jones, O.
creators_name: Lund, C. O.
creators_name: Melnik, S.
creators_name: Pawlowska, B.
creators_name: Wilson, E.
corp_creators: Tim Butler
title: Customer Focused Price Optimisation
ispublished: pub
subjects: food
subjects: retail
subjects: decision
subjects: data
studygroups: ESGI100
companyname: Tesco
full_text_status: public
abstract: Tesco want to better understand how to set online prices for their general merchandise (i.e. not groceries or clothes) in the UK. Because customers can easily compare prices from different retailers we expect they will be very sensitive to price, so it is important to get it right. There are four aspects of the problem.
• Forecasting: Estimating the customer demand as a function of the price chosen (especially hard for products with no sales history or infrequent sales).
• Objective function: What exactly should Tesco aim to optimise? Sales volume? Profit? Profit margin? Conversion rates?
• Optimisation: How to choose prices for many related products to optimise the chosen objective function.
• Evalution: How to demonstrate that the chosen prices are optimal, especially to people without a mathematical background.
Aggregate sales data was provided for about 400 products over about 2 years so that quantitive approaches could be tested. For some products competitors’ prices were also provided.
date: 2014
citation:   Caravenna, L. and Dewynne, J. and Farmer, C. and Jones, O. and Lund, C. O. and Melnik, S. and Pawlowska, B. and Wilson, E.  (2014) Customer Focused Price Optimisation.  [Study Group Report]     
document_url: http://miis.maths.ox.ac.uk/miis/673/1/studyGroupReport.pdf