Editing Principal component analysis (section)

=== Market research and indexes of attitude ===
Market research has been an extensive user of PCA. It is used to develop customer satisfaction or customer loyalty scores for products, and with clustering, to develop market segments that may be targeted with advertising campaigns, in much the same way as factorial ecology will locate geographical areas with similar characteristics.<ref>{{Cite journal |last1=DeSarbo |first1=Wayne |last2=Hausmann |first2=Robert |last3=Kukitz |first3=Jeffrey |date=2007 |title=Restricted principal components analysis for marketing research |url=https://www.researchgate.net/publication/247623679 |journal=Journal of Marketing in Management |volume=2 |pages=305–328 |via=ResearchGate}}</ref>

PCA rapidly transforms large amounts of data into smaller, easier-to-digest variables that can be more rapidly and readily analyzed. In any consumer questionnaire, there are series of questions designed to elicit consumer attitudes, and principal components seek out latent variables underlying these attitudes. For example, the Oxford Internet Survey in 2013 asked 2000 people about their attitudes and beliefs, and from these analysts extracted four principal component dimensions, which they identified as 'escape', 'social networking', 'efficiency', and 'problem creating'.<ref>{{Cite book |last1=Dutton |first1=William H |url=http://oxis.oii.ox.ac.uk/wp-content/uploads/2014/11/OxIS-2013.pdf |title=Cultures of the Internet: The Internet in Britain |last2=Blank |first2=Grant |publisher=Oxford Internet Institute |year=2013 |pages=6}}</ref>

Another example from Joe Flood in 2008 extracted an attitudinal index toward housing from 28 attitude questions in a national survey of 2697 households in Australia. The first principal component represented a general attitude toward property and home ownership. The index, or the attitude questions it embodied, could be fed into a General Linear Model of tenure choice. The strongest determinant of private renting by far was the attitude index, rather than income, marital status or household type.<ref>{{Cite journal |last=Flood |first=Joe |date=2008 |title=Multinomial Analysis for Housing Careers Survey |url=https://www.academia.edu/33218811 |access-date=6 May 2022 |website=Paper to the European Network for Housing Research Conference, Dublin}}</ref>