White Papers Archives

B2B Sales & Marketing Machine Learning

This whitepaper reviews an approach for applying machine learning and predictive analytics in a B2B sales & marketing environment.

By Drew Clancy, 7 yearsSeptember 19, 2018 ago

White Papers

Advanced Statistics for Email A/B Testing

Applying statistical inference is a great way for businesses to get more value out of there email marketing programs.

By Drew Clancy, 7 yearsJanuary 4, 2018 ago

White Papers

Machine Learning for Customer Experience

We examine how businesses can apply machine learning to propensity modeling, CLV, segmentation, attribution, and churn.

By Drew Clancy, 8 yearsApril 27, 2017 ago

White Papers

Dispatch Routing Optimization

In this whitepaper, we examine how different companies can attack the dispatch routing optimization problem using ML & AI.

By Drew Clancy, 8 yearsJanuary 25, 2017 ago

White Papers

The Energy industry holds multiple predictive analytics and data science opportunities. One large utility hired a management consulting firm to study their data process. The management consultants identified over $300 Million of value by utilizing the data this utility had already collected over many years.

By Drew Clancy, 9 yearsJuly 20, 2016 ago

White Papers

Using Data Science to Score Marketing Content

Applying AI for scoring marketing content effectiveness is a great use case for businesses.

By Drew Clancy, 9 yearsMarch 1, 2016 ago

White Papers

Predicting Employee Churn

This white paper examines a machine learning approach to predicting employee churn and optimizing for retention.

By Drew Clancy, 11 yearsMarch 19, 2014 ago

White Papers

Why Enterprise Data Warehouse Projects Fail

Our paper focuses on why enterprise data warehouse projects fail and what to do about it.

By Drew Clancy, 11 yearsFebruary 4, 2014 ago

White Papers

The Value of Information in the Age of Big Data

This white paper explores how traditional models of the value of information (VoI) can be extended effectively to account for uncertainties presently inherent in gathering and analyzing big data.

By Drew Clancy, 11 yearsJanuary 30, 2014 ago