Task: Determine Data Mining Goals

A business goal states objectives in business terminology. A data mining goal states project objectives in technical terms. For example, the business goal might be to “Increase catalog sales to existing customers.” A data mining goal might be to “Predict how many widgets a customer will buy, given their purchases over the past three years, demographic information (age, salary, city, etc.), and the price of the item.”

Purpose

Translate business goal into a data mining reality. For example, the business objective to “reduce churn” can be translated into a data mining goal that includes:

· Identifying high-value customers based on recent purchase data

· Building a model using available customer data to predict the likelihood of churn for each customer

· Assigning each customer a rank based on both churn propensity and customer value

These data mining goals, if met, can then be used by the business to reduce churn among the most valuable customers.

Relationships

Roles	Primary Performer: Data Miner/Data Scientist	Additional Performers: Client Subject Matter Expert
Process Usage	ASUM-DM > Analyze-Design-Configure&Build > Understand Business > Determine Data Mining Goals

Steps

Define Data Mining Goals

Describe the type of data mining problem, such as clustering, prediction, or classification.
Document technical goals using specific units of time, such as predictions with a three-month validity.
If possible, provide actual numbers for desired outcomes, such as producing churn scores for 80% of existing customers.

Define Data Mining Success Criteria

Define the criteria for a successful outcome to the project in technical terms—for example, a certain level of predictive accuracy or a propensity-to-purchase profile with a given degree of “lift.” As with business success criteria, it may be necessary to describe these in subjective terms, in which case the person or persons making the subjective judgment should be identified.

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