The research discovers customer benefit markets and marketing rules (association rules) via the Fuzzy c-means (FCM) algorithm and data mining technologies. However, the research objective is to discover fuzzy & crisp customer rules for enhancing marketing systems.  Data mining technologies are employed on discovering knowledge of consumers. The application will be a trend for marketing strategy. For a long-run retailer, their transaction records may have a large-scale database which contains customer shopping records. Hence, for understanding customer shopping intentions, in that respect, many international businesses discover customer knowledge from their POS (point of sales) systems with big data (customer-shopping records) by the data mining technologies. In data mining technologies, fuzzy theory and apriori algorithm can be used in analyzing various enterprises for business analytics. In the fuzzy clustering field, an observation can be assigned into two or many clusters (Manski, 1990). In contrast to the fuzzy clustering, the crisp clustering algorithm assigns an observation into a certain cluster for the purpose of market segmentation (Kotler et. al., 2016). Therefore, as mentioned above, an observation may be assigned into more than one cluster in fuzzy clustering (Russell and Lodwick, 1999, Chiang, 2011). This study employed the fuzzy clustering algorithm to obtain the solution of this problem. The research proposes a data mining approach to find association rules with fuzzy clustering. As to the research methods, this work uses a fuzzy clustering algorithm and market basket analysis to process the collected data. The approach of this study can be employed in e-business marketing systems or online CRM (customer relationship management) system. In coffee markets, the brewed coffee is one of the top 10 sales products around the world. BBC Travel (2014) pointed out that Taipei city is one of the top six coffee cities in the world. Hence, there were about 448 cups of brewed coffee purchased per person/year around the world in 2008. However, in Taiwan, there were about 80 cups of brewed coffee purchased in 2008. That is, the sales percentage of brewed coffee of Taiwan is approximately 17.865%  f the sales value of the world (Taiwan Coffee Association, 2008). However, according to the Ministry of Finance, Taiwan, ROC (2017), there were about 124 cups (person/year) of brewed coffee purchased in 2016. For the consumption of cups of brewed coffee in Taiwan, the growth rate was 55% from 2008 to 2016. As table 1.1 shows, the growth rates of all types of imported coffee beans in Taiwan were increasing from 2008 to 2011 and decreasing from 2012 to 2013. In 2014, the rate was increased. In accordance with mentioned above, the growth rates of the brewed coffee shoppers have grown up from 2013 to 2016 in Taiwan. In conclude, the industry of coffee shops is a very fast-growing industry in Taiwan. Nowadays, including convenience stores, there are more than ten thousand stores selling brewed coffee in Taiwan. Hence, it still can be enhanced toward a higher sales percentage. Thus, the industry of the coffee shop in Taiwan is the empirical case in this study.