Matthias Feist

Customer Analytics for Dummies eBook

Download your free copy of our Customer Analytics for Dummies eBook. It will help you with understanding customer analytics, acquiring and segmenting valuable customers, recognising customer lifetime value, enhancing customer loyalty and retention, extracting value out of social media.

Machine learning for dummies

In this book, you will discover types of machine learning techniques, models, and algorithms that can help achieve results for your company. This information helps both business and technical leaders learn how to apply machine learning to anticipate and predict the future.

The insider’s guide to predictive analytics

Predictive analytics projects fail all the time. In this book, Jarlath Quinn draws on his experiences and those of his colleagues to explore precisely what drives success or failure in predictive analytics projects. When it works, why does it work and what can be done to manage the risk of failure?

Writing IBM SPSS Statistics extension commands

If you’re familiar with programming languages such as Python or R then you can use them to extend the functionality of SPSS, automate more processes and make your jobs more stable and robust. This white paper tells you how to develop such IBM SPSS Statistics extension commands.

The hows and whys of survey research

This white paper discusses survey research by breaking it up into a seven step process — and clearly detailing how you maximize your efforts every step of the way. At each stage, it also shows how IBM SPSS predictive analytics technology can improve your results.

Real world examples of predictive analytics

This white paper presents a number of typical, real world examples of predictive analytics and shows how it can be used to address key business issues, with the aim of illustrating practical ways in which analytical capabilities can be deployed in a range of different organisations.

R and SPSS Software – everyone wins

The purpose of this paper is to demonstrate the benefits of using R and SPSS together, rather than simply trying to go it alone with R. With SPSS software, R users get access to superior data management, a point-and-click interface, presentation-quality output and improved scalability.

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