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How Does Basking Track Data Accuracy?

A comprehensive calibration process aligns our data with real-world observations, guaranteeing our clients receive reliable insights right from the start. From there, we continuously track accuracy metrics to ensure ongoing reliability in our data and reporting.


Initial Calibration Process

When a site first connects to Basking, we embark on a calibration phase lasting several weeks. During this period, we compare Basking’s data with supplementary sources, such as badge scans or manual counts. Key metrics like Mean Absolute Error (MAE) and Variance Rate are evaluated to assess the alignment between the ground truth and Basking’s observations. This critical step ensures that our data aligns closely with other sources, maintaining minimal variance while accounting for the inherent margin of error in each data source.

Continuous Accuracy Monitoring

Once the initial calibration is complete, Basking doesn’t stop there. We continuously track accuracy metrics to ensure ongoing reliability and consistency. Each new algorithm undergoes rigorous testing through our internal systems to validate its effectiveness before deployment, ensuring that only the most accurate methods are used.

Our proprietary machine learning models play a crucial role in this process:

  • Device Clustering: We group multiple devices per person to avoid duplication and ensure that each individual is accurately represented in our data.
  • Non-Human Device Identification: Our algorithms can identify non-human devices, such as printers, further enhancing data reliability.

Comprehensive Accuracy Reporting

At Basking, transparency is key. We provide our customers with detailed accuracy reports that include transparent assessments of data quality and on-demand recalibration options when necessary. This approach not only facilitates informed decision-making but also fosters trust among our clients. Any user within an organization can leverage this information to confirm the accuracy of site data, empowering them to make decisions based on reliable insights.


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