The Mirage That is 1st Party Data

Brand growth is simply finding new customer meanwhile the current shiny object is 1st party data strategies They are incompatible A 1st party data strategy is actually 2nd party data and much of that data is modelled Marketers don39t have much data on their prospective customers but others do so they match Compromises ensue The match rates aren39t always high they vary and there are volume incentives to try and get some kind of match which means lookalikes or modelled data But even when match rates are good that doesn39t mean every attribution attached to the ID is deterministic much of it is modelled No one can collect all the desired attributes against all their records they have to fill in the gaps somehow and the financial incentives are thereOn top of all this matching and modelling going on there is a privacy and tech overhead that has to be paid for The marketer has less working media dollars because they have to manage privacy That is the privacy of their customers whose 1st party data they matched with 2nd party data providers who modelled looklikes and added attributes to the matched ID It39s the worst of both worlds the cost of privacy management and the cost of modellingIt gets more challenging The marketer has matched with one provider lets say a retail media network but neither the advertiser nor the RMN have data on all the customers in the category The advertiser then matches with multiple RMNs to cover the full category but now they have created two more problems sample bias and deduplication Each RMN matches with a different portion of the advertiser39s 1st party data and so their lookalike modelling has sample bias each of their projections to category looks different Plus none of the RMN39s are sharing data with each other so no one has a picture of the deduplication across them allWorse now there is a bias in the media plan towards any medium that offers 1st party data match instead of planning for effectiveness and efficiency Radio Forget it Why would anyone propose a medium that doesn39t use the shiny data clean room and all this 1st party data we invested in collecting Plus anyone who has looked at the mechanics of the Turbo Confabulator realizes that where there is mystery there is marginLastly the marketer39s challenge didn39t just pop out of nowhere Before the marketing plan there was a business plan and in that plan there are sales projections regional distribution plans market share and repeat purchase objectives all of which were developed by data scientists using modelling against top down category populations Those audience definitions were good enough to get approval for product development why not use them in marketing and media More and more of this business data science uses synthetic data national populations to support business decisions The synthetic population is nothing but a bunch of Virtual IDs VIDs with thousands of attributions attached to each VID Whether it39s product usage or media usage same thing same data same ID The VID is far more capable of spanning business and media operations than the compromises being made in 1st2nd party data match in clean rooms

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The Mirage That is 1st Party Data

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Chris Williams

Breaking Barriers: Nada Bradbury’s AD-ID Strategy for Advertising Effectiveness and Women in Tech - By E.B. Moss

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The Mirage That is 1st Party Data

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Chris Williams

Breaking Barriers: Nada Bradbury’s AD-ID Strategy for Advertising Effectiveness and Women in Tech - By E.B. Moss

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