Nine partners with Data Republic to provide grocery and loyalty data to advertisers
Nine has signed an agreement with data exchange company Data Republic which will give Nine advertisers access to key grocery-buying segments across its network.
The agreement, set to be announced at today’s Nine upfronts event, will see Data Republic provide Nine with grocery and loyalty data sourced from a network of more than 1,600 independent grocers.
Subsets from this data have been used to develop aggregate grocery segments which will allow advertisers to improve customer targeting across the Nine digital network and its 15.3m authenticated user IDs.
The data will be aggregated and used across 45 segments targeting a range of different spending habits and levels. It will then be used across Nine’s digital network and to better target its 15.3 million authenticated users.
Alex Parsons, Nine’s chief digital and marketing officer, said the decision to dive into the grocery-data space is linked to Nine’s announcement regarding it’s women’s network.
“Groceries in that category have a very hand-in-glove approach in that space,” he said.
“It’s also a category that, historically, digital hasn’t catered to extremely well in terms of FMCG, so there’s a tonne of opportunity in that space.
“It’s a good start for us in terms of our working relationship with Data Republic before we start to branch it out. The one area where we believe there is some material upside in terms of FMCG and that’s the grocery +space.”
Nine said the deal includes scope to extend into other audience segments such as banking and retail.
Granular grocery data + programatic don’t mix.
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Building GB segments based on independent grocery chains would not be representative consumer behavior.
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“allow advertisers to improve customer targeting across the Nine digital network and its 15.3m authenticated user IDs”
Advertisers being anyone who isn’t a competitor to IGA in the FMCG category that is, if they see you as a competitor you are blocked out from buying these segments.
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Loose data mapping at the very best. Why start with FMCG store trends and not more robust data like the banking sector where you can do a 1:1 match.
Further, refer to comments 1-3.
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