Transforming customer postal address into spatial address for demographic analysis: A case of non-contractual customers in Seberang Perai, Pulau Pinang of Malaysia - Bohari, Abdul Manaf; Rainis, Ruslan; Marimuthu, Malliga (2011)
Postal address is one of important data that potentially used for trace, capture and used together with customer demographic, such as location, residential, income level, education level, transportation, and so on.The customer postal address is a touch point to analyzing demographic where it is vital important to the business, especially to prospecting their profitable customer.From literature review survey, the business has been used survey intensively as main sources for gathering demographic infomation about customer, including non-contractual customer, also called non-database customer.However, some problem will rise during joins used of home postal address, specifically, refers to un-match problems between home postal address of non-contractual customer (from the survey) with spatial data address (road and street data). These un-match problems may create un-accurate value in analyzing customer demographic background when current location, of customer takes into account. The objective of the paper is to discuss some issues regarding un-match between home postal address of non-contractual customer and spatial address.Secondly, this study will introduce a procedure on how to solve these problems where at the end results on 100 percents match between these two data.The method of this study is by using iThoughMap as an application for transforming customer postal address into spatial address.To operating this work, data survey of non-contracting customer will use as a source of home postal address, while road and street data were obtained from government agency.This study will be applied specifically on the location of Seberang Perai, Pulau Pinang in Malaysia.One of result indicates that perfect match between postal address with spatial address bas produced when hundred percent match has resulted.At the end, suggestion will be recommended for future research on how improvising the accuracy, timeliness, and precision of information regarding non- contracting customer by utilizes spatial and non-spatial data.