Deterministic Data

Use deterministic data to conduct real-world consumer analytics.

CONSUMER ANALYTICS WITH LOCATION INTELLIGENCE

The Importance of Using Deterministic Data in Analytics

When analysts evaluate different types of data for analysis, they often look at the type of data, how it is collected, and the source. Deterministic consumer data is regarded as the most accurate data type: it is by definition first-person, and verifiable. Probabilistic data, on the other hand, is implied behavior.

Based on Real-World Consumer Insights

Our location intelligence is classified as deterministic, as it is obtained from real-world customer behaviors. This provides our customers with a more in-depth customer data: about the choices they make and the events they attend, which provides information about their interests, values, and attributes. 

A deterministic data analysis gives analysts better insight into real-world consumer behavior. Using this type of data prevents analysts from using inaccurate consumer data, which could skew the results of their analysis. Probabilistic data is useful information to have, but hardly accurate enough to be the sole source of decision-making data. It is the result of applying predictive analytics that attempt to project values or attitudes based on historical information.

Based on Real-World Consumer Insights

High-Quality Location Data

It’s important for deterministic data to be verifiable. We collect high-quality, pseudonymized location data from mobile device users who visit commercial places of interest and events. We also verify consumer attendances to ensure data accuracy. In addition, our forensic flags provide analysts with the ability to determine which location mobile signals to use in their data analyses. Our customers are then empowered to analyze data without worrying about the quality impacting their results.

Deterministic Data for BI Analysis

Many companies use business intelligence to make strategic data-driven decisions. We recommend checking out this white paper to learn how to use our data to enhance the customer experience.

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