SPSS Names Winners of Insight Awards

Advance Auto Parts, Bancolombia and Nu Skin Enterprises were recognized for their use of IBM SPSS predictive analytics software to improve market basket analysis and supply chain optimization, monitor and identify suspicious money laundering activities and increase marketing campaigns to reduce churn, respectively. These organizations join commercial, government and academic customers that are deploying predictive analytics to acquire, grow and retain customers, while mitigating risk and reducing fraud.

Established in 2004, the Insight Awards recognize customers that have delivered exceptional business value and gained significant return on investment (ROI) - in quantitative results or objective observations. The Insight Awards honor customers for the use of predictive analytics contributing to their organizations.

Advance Auto Parts, a retailer of automotive parts, uses IBM SPSS predictive analytics software for market basket analysis and supply chain optimization to accurately manage inventory at warehouses and individual stores. The organization chose IBM SPSS predictive analytics to leverage all data assets to produce, evaluate and deploy analytical models on SKU association modeling, market basket and cluster analysis when processing sales transaction data.

Bancolombia, a commercial bank in Colombia and one of the largest in Latin America, uses IBM SPSS predictive analytics software to monitor the transactional patterns of its customers. Bancolombia is committed to prevent money laundering activities in its organization, implementing pattern recognition, anomaly detection, risk analysis and predictive modeling capabilities that IBM predictive analytics software offers. Employing this technology, the bank reduced the number of suspicious operations that required auditing by more than 90 percent. The bank also increased accuracy in identifying positive cases of money laundering, helping investigators to adapt models to the changing tactics of those engaged in this criminal activity.

Nu Skin Enterprises Inc., a $1 billion global direct selling company, markets anti-aging personal care and nutrition products through a global network of more than 750,000 active independent distributors. The organization selected IBM SPSS predictive analytics software to build, validate and deploy predictive models for its marketing campaigns and segmentation.

Using IBM SPSS predictive analytics software, Nu Skin's business development department built propensity models that allowed the company to identify customer and distributor segments in its market. With these models, Nu Skin said it was able to understand customer and distributor trends, and then re-engage distributors - on an individual basis - with event-based marketing activities.

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