From e02330cfa16deb773ae6a6ecb3fa9a1d6b9bb33d Mon Sep 17 00:00:00 2001 From: benjaminsavage <52456851+benjaminsavage@users.noreply.github.com> Date: Wed, 14 Jun 2023 17:12:21 +0100 Subject: [PATCH] Consensus write-up on "Optimization" Use Case In our last meeting we reached general agreement that the group wants to support the "Optimization" use case. This is a write-up of that agreement. --- measurement-use-cases.md | 24 ++++++++++++++++++++++++ 1 file changed, 24 insertions(+) create mode 100644 measurement-use-cases.md diff --git a/measurement-use-cases.md b/measurement-use-cases.md new file mode 100644 index 0000000..69e6a8e --- /dev/null +++ b/measurement-use-cases.md @@ -0,0 +1,24 @@ +# Measurement Use Cases + +The group is currently working on developing a privacy preserving ad measurement system. + +There is general agreement that we want such a system to satisfy the following use cases: + +# Advertiser Reporting + +TODO: fill this in + +# Optimization + +Ad selection systems often attempt to estimate the probability that if an ad is shown, it will lead to a conversion event. +More sophisticated systems may also attempt to predict conversion values / counts / categories. + +The information produced by "Advertiser Reporting" is already sufficient to make naive predictions (i.e. just estimate the average conversion rate for all users). +But there is interest in the group to intentionally design the private measurement system to do better than this. + +There is general agreement in the group that: + +1. This is a use case that we explicitly want to support +2. Within our agreed privacy bounds we would like to design outputs which provide as much utility as possible for this use case +3. We are flexible on the mechanism to support this, and potentially envision a private measurement system which supports multiple modalities intended to support this use case. +