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Ad Server Logs
This page describes the Adnuntius Ad Server Log format. Obtaining access to logs is a premium feature; please contact Adnuntius if you would like this to be enabled for your account
Ad Server logs can be downloaded via an SFTP server or pushed to cloud storage. An example of log data can be found here. The logs are in a JSON format, with each line having the format described below.
Field Name
Data Type
Description
eventTime
Timestamp
An ISO 8601 date string (yyyy-MM-ddTHH:mm:ss.sss)
eventId
String
The identifier for the original ad server request. Can be used to match clicks to impressions etc
referrer
String
The HTTP Referer header of the ad request
userAgentString
String
The User-Agent header of the ad request
segments
Collection[ObjectId]
User segments that apply to the ad request
keyValues
Map[String, Collection[String]]
Key Values that apply to the ad request e.g. {"interests":["sport", "music"]}
keywords
Collection[String]
Keywords that apply to the ad request e.g ["news", "business", "australia"]
categories
Collection[String]
Categories that apply to the ad request
iabCategory
String
An IAB Category for the Advertiser e.g. IAB_3_1_3_8
cost
MonetaryAmount
The cost for this event
deviceProperties
Map[String, String]
​
location
Location
The detected location
consents
Collection[Consent]
The user consents provided to Adnuntius with this request.
latitude
Float
The detected latitutde
longitude
Float
The detected longitude
pseudoUserId
String
An anonymised user identifier. It cannot be used to track individual users. See below for further details.
adUnit
ObjectId
The Adnuntius Ad Unit that received this ad request
lineItem
ObjectId
The Adnuntius Line Item that won the auction
creative
ObjectId
The Adnuntius Creative that won the auction
advertiser
ObjectId
The Adnuntius Creative that won the auction
You can also read more about log data and see an example of a single data record here: https://adnuntius.com/blog/adnuntius-brings-the-big-data​

Object Identifiers

References to Adnuntius objects in the logs are desribed using an ObjectId, which has the following fields:
Field Name
Data Type
Description
id
String
The Adnuntius object ID
name
String
The object name
Example:
{
"id": "s8734kjhw98",
"name": "July Line Item"
}

Monetary Amounts

Costs are described using a MonetaryAmount object.
Field Name
Data Type
currency
String
amount
Number
Example:
{
"curreny": "EUR",
"amount": 10.0
}

Locations

The location is reported using the following properites:
  • CONTINENT
  • COUNTRY
  • REGION
  • CITY
  • POSTCODE
Example:
{
"CONTINENT": "Oceania",
"COUNTRY": "Australia"
"REGION": "Victoria",
"CITY": "Melbourne",
"POSTCODE": "3000",
}

Consent

One of the following values:
Name
Description
TCF_PURPOSE_1
IAB Europe Transparency & Consent Framework Purpose 1 - Store and/or access information on a device
TCF_PURPOSE_2
IAB Europe Transparency & Consent Framework Purpose 2 - Select basic ads
TCF_PURPOSE_3
IAB Europe Transparency & Consent Framework Purpose 3 - Create a personalised ads profile
TCF_PURPOSE_4
IAB Europe Transparency & Consent Framework Purpose 4 - Select personalised ads
TCF_PURPOSE_5
IAB Europe Transparency & Consent Framework Purpose 5 - Create a personalised content profile
TCF_PURPOSE_6
IAB Europe Transparency & Consent Framework Purpose 6 - Select personalised content
TCF_PURPOSE_7
IAB Europe Transparency & Consent Framework Purpose 7 - Measure ad performance
TCF_PURPOSE_8
IAB Europe Transparency & Consent Framework Purpose 8 - Measure content performance
TCF_PURPOSE_9
IAB Europe Transparency & Consent Framework Purpose 9 - Apply market research to generate audience insights
TCF_PURPOSE_10
IAB Europe Transparency & Consent Framework Purpose 10 - Develop and improve products
More information can be found here.

User Identifiers

The logs include "pseudo" user identifiers that have been anonymised so that they no longer uniquely identify a single user. The same user will always be assigned the same identifier, but that same identifier can and will also be assigned to multiple other users as well. The identifiers can be used with a probabilistic cardinality estimation method, such as the popular HyperLogLog algorithm, to estimate the number of unique users that viewed an advertisement without knowing precisely the number of times that each individual user viewed the ad.