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.
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.