Recording and understanding the behaviour of customers is paramount and a key factor influencing the success of any retail business. This paper reports the initial stages of an EPSRC funded research project, which presents a new methodological approach to analysing in-store customer behaviour with a view to optimising space and store performance. Using existing in-store CCTV cameras from a major clothing discount retailer, consumers are tracked to detect patterns of behaviour. Analysis of these ''realtime'' data exhibited flaws in the arrangement of customer service facilities, and insight into the problems associated with merchandise return policies. Understanding these customer processes and movement patterns thus helped the retail collaborator maximise the performance of the store.

Abstract:The aim of this research work is to establish what level of numeric colour difference between two digital images is visually acceptable by average human observers on a calibrated monitor under a fixed set of viewing conditions. A visual ordinal category method is introduced and a description of the experimental design is provided. Results based on over 4000 visual and numeric comparisons are reported. All results are analysed by statistical methods. The correlation between visual assessments and numerical assessments are found by means of the Pearson product moment coefficient. Overall colorimetry accuracy and metamerism are discussed.· A very high level of correlation is found to exist between the visual ordinal categories assigned by observers and the equivalent numeric (~E CMC 2: I) colour difference. Individual observers, within the group of 20 observers tested, were found to be consistent in their ordinal categories. However, some observers were consistently severe in their judgement and others significantly more lenient.