List of IBM SPSS Modeler Customers

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Logo Customer Industry Empl. Revenue Country Vendor Old Product New Product Category When SI
ABL Life Insurance Korea Insurance 900 $400M South Korea IBM Legacy IBM SPSS Modeler ML and Data Science Platforms 2010 n/a
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Buyer Intent: Companies Evaluating IBM SPSS Modeler

ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating IBM SPSS Modeler. Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating IBM SPSS Modeler for ML and Data Science Platforms include:

  1. University of Naples Federico, a Italy based Education organization with 4910 Employees

Discover Software Buyers actively Evaluating Enterprise Applications

Logo Company Industry Employees Revenue Country Evaluated
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FAQ - APPS RUN THE WORLD IBM SPSS Modeler Coverage

IBM SPSS Modeler is a ML and Data Science Platforms solution from IBM.

Companies worldwide use IBM SPSS Modeler, from small firms to large enterprises across 21+ industries.

Organizations such as ABL Life Insurance Korea are recorded users of IBM SPSS Modeler for ML and Data Science Platforms.

Companies using IBM SPSS Modeler are most concentrated in Insurance, with adoption spanning over 21 industries.

Companies using IBM SPSS Modeler are most concentrated in South Korea, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of IBM SPSS Modeler across Americas, EMEA, and APAC.

Companies using IBM SPSS Modeler range from small businesses with 0-100 employees - 0%, to mid-sized firms with 101-1,000 employees - 100%, large organizations with 1,001-10,000 employees - 0%, and global enterprises with 10,000+ employees - 0%.

Customers of IBM SPSS Modeler include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.

Contact APPS RUN THE WORLD to access the full verified IBM SPSS Modeler customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of ML and Data Science Platforms.