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DATA MINING
Strategic Advantage
Successful data mining implementations often lead to strategic advantage in the marketplace. The information obtained from data mining can be used for affinity grouping or forecasting.
Brand Loyalty
Today’s consumer has a wealth of information available to him/her. The internet contains sites for product users, independent product reviews, and consumer opinions. Businesses are now dealing with buyers who are armed with both information and unforgiving expectations. Building brand loyalty and retaining customers are some of the most difficult challenges business face today.

In this environment, companies that slip up – even if it’s simply failing to match customer tastes – can no longer count on their good names to carry them through. It is extremely important to keep a pulse on the market to understand what consumers are doing. Aligning existing customer information with sales and promotion analysis will assist in understanding how the organization's products are selling in the marketplace.

Consumer Behavior
Data mining is used to assist in extracting patterns from data. Predictive data mining finds patterns that are used to identify trends and points to a likelihood of a particular outcome. Clustering divides data into smaller groups based on similarity without predefinition of the groups. For example, knowing which customers have similar buying habits will assist in marketing campaigns and product offerings.
Trend Analysis
Affinity grouping describes which attributes are associated with each other and is often used by retailers to identify cross-selling opportunities and plan in store merchandising.

Consumers tend to purchase products the same way over time. Forecast of sales of target products can be made against sales of other products. This will aid in budget forecasts, quotas, and supply chain requirements.

Business Intelligence Blog


Val Matison awarded Microsoft SQL Server MVP for 2007, 2008, 2009

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