Our Formula
The foundations of our approach rest on Bayes’ Theorem
BayeSim believes you’re unique. That’s why we use a combination of manual Bayesian analysis and machine learning to provide predictions that are as tailored to you as possible.
Bayes’ Theorem
Used to compute conditional probabilities, Bayes’ Theorem states that:
Our Approach
Our approach is personalized to you. Our team members work with you to manually set your priors based on your unique experiences, differentiating you from others. This manual process ensures control and transparency, so you can understand why our Social Calculator returns certain probabilities, unlike black-box ML models. Additionally, this gives you the flexibility to adjust your priors over time as we track your data and you update your beliefs.
Step II: Setting Your Priors
A team member works with you to manually define your baseline beliefs (prior probabilities) based on this data.
Phase IV: Applying Bayes’ Theorem
We deliver predictions using Bayes’ Theorem
Step I: Collecting the Data
We gather cross-platform digital behavioral data from social media and messaging apps like Instagram, Facebook, TikTok, Find my iPhone, iMessage, and WhatsApp.
Step III: Training the Model
We train an ML model on past data to predict likelihoods. We seek to understand how behaviors have shown up in your past experiences.