<?xml version="1.0" encoding="UTF-8"?>
<article_metadata generated_at="2026-09-03T22:30:27+00:00">
  <journal>
    <title>Journal of Business and Retail Management Research</title>
    <acronym>JBRMR</acronym>
    <issn_print></issn_print>
    <issn_online>2056-6271</issn_online>
    <doi_prefix>https://doi.org/10.24052/JBRMR/</doi_prefix>
  </journal>
  <article>
    <id>199</id>
    <title>Behavioural segmentation using store scanner data in retailing: Exploration and exploitation in frequently purchased consumer goods markets</title>
    <abstract>Consumers treat and react to promotions diversely in terms of their promotion proneness and variety seeking tendency. This paper investigates 589 consumers with 169678 transaction records in the US salt-snack market ranging from year 4 to year 7 in IRI Market Dataset for exploring how their purchase behaviours evolve in the consumer life cycle. A set of algorithms is presented to process store scanner data for measuring consumersâ€™ promotion proneness and variety seeking tendency, which are then used for conducting clustering analysis. Four types of purchase behaviours including â€œPromotion averseâ€, â€œBargain huntersâ€, â€œOpportunistic explorersâ€, and â€œOpportunistic exploitersâ€ are identified and assigned accordingly for each consumer in each year. Even though consumersâ€™ purchase behaviours will dynamically and freely shift within or among those four behavioural segments over time, two clear behavioural evolvement patterns can be identified statistically in the consumer life cycle. In the US salt-snack market, some consumers who are initially not sensitive to promotions will gradually evolve to take advantage of promotion to try alternatives for extending their market knowledge. Some explorersâ€™ promotion proneness will gradually increase and outweigh their variety seeking tendency over time, thus, those opportunistic explorers become inclined to buy any brands on promotion. In contrast, consumers who initially prefer to buy their familiar brands will become m</abstract>
    <doi></doi>
    <url>https://jbrmr.com/details&amp;cid=199</url>
    <pdf_url>https://jbrmr.com/cdn/article_file/i-22_c-199.pdf</pdf_url>
    <volume>Volume 10</volume>
    <issue>Issue 1</issue>
    <issue_id>22</issue_id>
    <issue_published_month>2015-10-01</issue_published_month>
    <published_date>2015-11-04</published_date>
    <online_first_status>no</online_first_status>
    <online_first_date></online_first_date>
    <history>
      <received></received>
      <revised></revised>
      <accepted></accepted>
    </history>
    <keywords>
      <keyword>Consumer behavioural evolvement</keyword>
      <keyword>behavioural segmentation</keyword>
      <keyword>promotion</keyword>
      <keyword>exploration and exploitation</keyword>
      <keyword>retailing</keyword>
      <keyword>store scanner data.</keyword>
    </keywords>
    <declarations>
      <funding></funding>
      <conflict_of_interest></conflict_of_interest>
      <data_availability></data_availability>
      <author_contributions></author_contributions>
    </declarations>
    <publication_notice>
      <type>none</type>
      <text></text>
    </publication_notice>
    <metrics>
      <views>595369</views>
      <downloads>71</downloads>
      <citations>0</citations>
    </metrics>
    <authors>
      <author>
        <name>Cheng Luo</name>
        <organization>Manchester Business School, University of Manchester</organization>
        <country></country>
      </author>
      <author>
        <name>Oscar de Bruijn</name>
        <organization>Manchester Business School, University of Manchester</organization>
        <country></country>
      </author>
      <author>
        <name>Yu-Wang Chen</name>
        <organization>Manchester Business School, University of Manchester</organization>
        <country></country>
      </author>
    </authors>
    <supplementary_materials/>
  </article>
</article_metadata>
