Data Mining

Data mining is a process of uncovering hidden patterns from large amount of data using various analytics including clustering and classification, predictive modeling (decision trees, logistic regressions, neural networks, etc.), and association analysis. Data mining methods can be applied to solving various business problems and helping an organization to develop and implement marketing strategies. Currently we can provide advanced data mining analyses in various areas including:


Customer relationship management

Predictive modeling is typically used to produce customer-level models that predict the likelihood that a customer will take a certain action. The actions are usually sales, marketing and customer retention related. For example, we can provide churn analysis to help an organization gain insights into the reasons why their customers are leaving them. By understanding and identifying those customers' characteristics and behaviors, we can help you can put proactive strategies to meet their needs and reduce customer turnover.


Campaign management

Running effective marketing campaigns is critical to an organization which wants to maintain and expand its customer base in a competitive environment. We use various analytic tools to make your campaigns more efficient and profitable by effectively identifying the customers who are most likely to respond to your certain offers.


Customer value analysis

By calculating customer lifetime value (CLV) and performing customer segmentation analysis, we can help you effectively identify most profitable customer segments and identify opportunities to migrate other customers into more profitable segments.


Market Basket Analysis

by identifying and analyzing events that occur in a certain sequence at given time period, we can provide you insights to understand customer buying patterns and design your optimal product mix. This also can help you leverage cross/up selling opportunities and enhance your marketing strategies.

 PharStat Inc. © copyright 2008