Should you buy or build AI? Considerations for marketing teams
The race to implement reliable, scalable AI is on, and you only get one chance to beat your competitors.
Predictive modeling
Articles related to predictive modeling from the team that helps B2C companies build and defend revenue with AI.
Predictive personas: Work smarter to know your customers better
You could be speaking directly to your core audience on a deeper, more personalized level with images that speak to who they are and what they love.
Happy Money customer spotlight: Optimizing omnichannel marketing with data-driven audiences
Happy Money is a fintech company on a mission to turn borrowers into savers, specializing in helping people pay off their credit card debt and save up for the future.
Customer cohort analysis: Using event data to understand customer behavior
We like cohorts because they are only able to grow, retaining each individual customer that enters. The fact that someone can’t be removed from a cohort means that, when modeling, we can expect results from our historical models to be consistent.
Using propensity models to predict customer behavior
While there are various types of propensity models, the one we use most at Faraday is the random decision forest. Like real forests, this one is made of trees — decision trees. Decision trees are classifier algorithms that look like flow charts, showing the choices made to reach a certain outcome.
The weighted scale: Mitigating implicit bias in data science
An algorithm contains the biases of its builder. At Faraday, we have a handful of approaches we use to minimize these effects at each level of our machine learning pipeline.