Predictive Analytics

In the white paper “Seven Reasons You Need Predictive Analytics Today” the author Eric Siegel (President, Prediction Impact, Inc. and Chair, Predictive Analytics World) states:

Predictive analytics has come of age as a core enterprise practice necessary to sustain competitive advantage. This technology enacts a wholly new phase of enterprise evolution by applying organizational learning, which empowers the business to grow by deploying a unique form of data-driven risk management across multiple fronts. This white paper reveals seven strategic objectives that can be attained to their full potential only by employing predictive analytics, namely Compete, Grow, Enforce, Improve, Satisfy, Learn, and Act.

1. Compete – Secure the Most Powerful and Unique Competitive Stronghold

A predictive model distinguishes the microsegments of customers who choose your company from those who defer or defect to a competitor. In this way, your organization identifies exactly where your competitor falls short, its weaknesses.

2. Grow – Increase Sales and Retain Customers Competitively

Each customer is predictively scored for sales-related behavior such as purchases, responses, churn and clicks. The scores then drive enterprise operations across marketing, sales, customer care and website behavior. In this way, predictive analytics delivers its unique competitive advantage to a range of customer-facing activity.

3. Enforce – Maintain Business Integrity by Managing Fraud

Scoring and ranking transactions with a predictive model leverages the organization’s recorded experience with fraud to dramatically boost fraud detection. […] more fraud is detected, and more losses are prevented or recouped.

4. Improve – Advance Your Core Business Capacity Competitively

Predictive analytics improves product manufacturing, testing and repair in many ways. For example, during production, faulty  items are detected on the assembly line.

5. Satisfy – Meet Today’s Escalating Consumer Expectations

Predictive analytics is an explicit selling point to the end consumer, […] with predictive analytics, the consumer gets better stuff for less, more easily and more reliably.

6. Learn – Employ Today’s Most Advanced Analytics

The capacity for predictive analytics to learn from experience is what renders this technology predictive, distinguishing it from other business intelligence and analytics techniques.

7. Act – Render Business Intelligence and Analytics Truly Actionable

[…] predictive analytics is specifically designed to generate conclusive action imperatives. Each customer’s predictive score drives action to be taken with that customer. In this way, predictive analytics is by design the most actionable form of business intelligence.

To read the full white paper click here.

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