Deterministic Data
Gain a deeper understanding of your customers based on their buying habits, the choices they make, and the events they attend.
Evaluating different types of data involves understanding data: how it is collected, and what it indicates. One of the basic differentiators between types of data is whether it is deterministic, or probabilistic.
Deterministic consumer data is regarded as the most accurate data type: it is by definition first-person, and verifiable. It ties an individual (identified by name, email or mobile device ID), to an action – a purchase, inquiry, or interaction.
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Verified Data Means More Accurate Insights.
Gravy Analytics’ location intelligence is classified as deterministic data, as it is obtained from real-world customer behaviors and opens the door to thousands of individualized data points.
You can use Gravy’s deterministic data points to:
- Keep customer profiles up-to-date, as interests are always changing.
- Link disparate profiles to the correct person, avoiding skewed data sets excess spend.
- Sharpen multi-touch attribution tactics to uncover successful campaign tactics
Avoid Incorrect Assumptions
Probabilistic data, on the other hand, is implied behavior. It is the result of applying predictive analytics that attempt to project values or attitudes based on historical information.
Probabilistic data is similar to a weather report: it is useful information to have, but hardly accurate enough to be the sole source of decision-making data.
Authenticate Mobile Event Data.
Gravy connects an individual’s location to verified attendance at specific events. This provides deterministic data for a deeper customer understanding: about the choices they make and the events they attend, which provides solid information about their interests, values, and attributes.
For your reference, related pages:
Foot Traffic Data
Advertising Attribution
Competitive Intelligence Tools
CASE STUDY: NATIONAL CINEMEDIA
National CineMedia used Gravy Analytics to provide better insight into potential customers using geo-location and behavioral data.