IRI has introduced a broad, new consumer packaged goods data set available for distribution to academics. These data are intended to enable academic researchers to study important research topics in marketing and economics of concern to practitioners, policy makers, and scholars.
This database contains:
- 11 years of weekly store data (2001-2011) for chain grocery and drug stores in 47 markets.
- Store-week-UPC level for 30 large CPG categories in 47 markets
- Panel data for two BehaviorScan markets (11 years, same categories)
- TNS advertising data for two categories for some early years.
Is there a published description of this dataset?
An article describing this dataset was published in Marketing Science in 2008, and can be found here.
Why is IRI charging academics for this data?
We're not selling the data, we're making the data available gratis for academic research purposes. We're also trying not to ship free USB hard drives to everybody who asks for one. There are also costs related to the assembly of this data in this form (e.g. removing retailer identification) which we would like to partially recover.
Does IRI plan to continue this program?
IRI plans to continue this program, although this is not guaranteed. No one should make completing their PhD contingent on receiving 2012 data! The consumer household panel data will definitely not be continued after 2012 in its current form.
Can you make changes to the NDA which our university lawyers would like?
No. The conditions were worked out with INFORMS (the professional society for Marketing Science). They have been standard in IRI's academic contracts since the 1980's.
For a data set we are making available for a handling charge, we have obviously not budgeted legal costs and can not entertain legal negotiations. We've held to that since this data set was released in 2008. Any change would undercut this position and lead to further costs down the road as we go through the same contract negotiation with future clients. This would lead to either a large increase in the cost of the data set or (more likely) the elimination of its availability entirely.