GLOSSARYProbabilistic Scoring
What is it and why it is important?
What is Probabilistic Scoring?
A method that assigns a confidence level to each visit or event based on spatial patterns, context, and behavior to quantify its likelihood of being accurate.
Why is Probabilistic Scoring Important?
Not all visits are equal. Probabilistic scoring helps filter out low-confidence data points, ensuring marketers and analysts work with the most trustworthy signals.
What are the Benefits of Probabilistic Scoring?
Enables transparent data quality assessments, prioritization of high-confidence data, and better outcomes in segmentation and attribution workflows.
How Precisely Can Help
Precisely Audiences data uses probabilistic methods to infer audience characteristics from anonymized location data, enhancing targeting accuracy. For instance, identifying high-intent shoppers or lapsed customers for QSR campaigns involves scoring based on visitation patterns, which can be probabilistic when direct identifiers are unavailable. Products like Signal Engine include built-in probabilistic scoring to help teams trust and validate visit data for decision-making, without relying on opaque, black-box models.
Precisely Audiences
Reach the right people and power real results with pre-built, privacy-safe audience segments with verified visitation insights.
Precisely Visits
Develop smarter marketing strategies and drive real-world consumer actions, on your own terms.