The science that drives the solution
Data, science, and math are at the core of every Copilot decision. We apply academic rigor to every problem and encourage experimentation. The first thing we tell all brands we work with: start with all of your available data (inputs) and the end-goal you want to achieve (output).
Consider offline data, vertical trends, or even mapping journeys through your site. You control the desired privacy approach.
We have the tools and talent to deliver a differentiated outcome strategy.
- Access to algorithms
- Talent to train
- Data integrations
- Actionable insights
The core Copilot algorithms and how they work
Linear Programming is:
a type of optimization used when you want to maximize or minimize a linear objective function given some variables and constraints.
objective function: what you are trying to maximize or minimize variables: what you are trying to solve for constraints: the limits you have
Clustering algorithms are very common
Clustering is a classic example of unsupervised learning- finding patterns in data sets without a right or wrong answer. The goal is to simply learn about the structure of your data and not to make predictors.
Models are only made unique from the data and talent training them. See some of our executions:
Get drivers behind the wheel
Get drivers behind the wheel. A unique optimization strategy that correlates key digital or offline actions to real life test drives and adjusts delivery in real time. Utilize a customized Copilot algorithm mapped to various online or offline points of influence to increase the likelihood of a real dealership visit while improving cost effectiveness. "Take it for a spin", "Hit the road", "Off the lot.