Strong Blog

Read our thoughts on data science, machine learning, predictive models, and optimization.



Keanu: Enter the Model.Matrix

Mar 28th, 2018 by Jacob Dink

One of R’s strengths is its powerful formula-based interface to modelling. It saves you the headache of one-hot-encoding categorical variables, manually constructing higher-level interactions, and rewriting models just to add or drop terms. Instead, you just specify the model you want in high-level notation, and R will handle transforming it into the raw numerical model-matrix that’s needed for model-fitting. We wrote keanu to make tackling situations where R's built-in interfaces fall short. It allows you to focus on the core aspects of your models, providing the tools that handle the busywork of translating abstract model-specifications into the nuts-and-bolts of model-fitting.

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Open Role: Data Scientist

Dec 1st, 2017 by Brock

Strong Analytics is seeking a data scientist to join our team in developing machine learning pipelines, building and validating statistical models, and helping our clients discover value in their data.

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How can Deep Learning Help Your SaaS Business?

Apr 20th, 2017 by Jacob

It's easy to see how deep learning is a powerful tool for companies like Google, Twitter, Facebook, and Amazon. In this post, I review several ways that deep learning can have immense value for smaller SaaS companies. The same technology that powers self-driving cars can even help you win new customers, make recommendations, and decrease churn.

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Predictive Model ROI ($) Calculator

Mar 15th, 2017 by Brock

Understanding the value that a predictive model can add to your business is often challenging. We wanted to make things simpler by building a free tool to calculate the ROI ($) of your predictive model based on its performance, number of possible events, baseline rate of events, and profits/costs of your intervention.

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Introducing Optimail: Email Marketing powered by Artificial Intelligence

Sep 18th, 2016 by Brock

Optimail offers its users the opportunity to continuously and automatically optimize their email campaigns using artificial intelligence. Marketers can simply draft the emails they want to send (or many versions thereof), define the goals they want these emails to achieve, then sit back and watch as Optimail learns the strategy that drives customers most effectively toward those goals.

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Is Data Science only Useful for Organizations with 'Big Data'?

May 3rd, 2016 by Brock

Some think that making data-driven decisions requires 'big data,' leaving smaller organizations out of the recent data science movement. I argue to the contrary that thinking about data science early on can not only prepare your organization for future growth, but offer insights even from the small data you have now.

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