NBD 2.0: Harmonizing Data to Make It Really Sing
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It is not unusual for data to have vast discrepancies in consistency, modes of measurement and coverage. This is a challenge when trying to get an accurate picture of the consumer packaged goods market and its consumers. Among the most long-standing and basic data in its vast library of data sets, IRI uses point-of-sale (POS) and National Consumer Panel data in a complementary fashion to provide clients with a well-rounded view of attitudes and behaviors, down to the household level.
To ensure maximum data accuracy and minimize data’s innate weaknesses, IRI adjusts and aligns this data through complex statistical processes. One of these processes is negative binomial distribution (NBD) adjustment. NBD is a widely used probability distributional model to align observed count data, or data that counts rather than ranks.
Click here to learn more about how NBD adjustment fits into the data science strategies that ensure the integrity and longevity of the world’s largest CPG big data set.