{"_id":"58ed1c0f98a5c80f008745c5","project":"55de06fa57f7b20d0097636b","__v":0,"parentDoc":null,"user":"55de06e19db51a0d0064947d","version":{"_id":"55de06fa57f7b20d0097636e","project":"55de06fa57f7b20d0097636b","__v":14,"createdAt":"2015-08-26T18:35:38.642Z","releaseDate":"2015-08-26T18:35:38.642Z","categories":["55de06fb57f7b20d0097636f","55f1962e3936d52d00fb3c8f","55f1970339e3e8190068b2b8","55f1970d229b772300779a1f","55f1971cfd98c42300acc605","55f1d5c7fd98c42300acc69f","563cbfe4260dde0d00c5e9d4","5644cf437f1fff210078e690","57dc1bbd3ed3450e00dc9ea7","58a600a2243dd30f00fd8773","58ed1bdc068f780f00f64602","58f13b3a4f0ee50f00e24e81","58f173f792f9020f009cad16","591b42f8e633fd0f00077c5a"],"is_deprecated":false,"is_hidden":false,"is_beta":false,"is_stable":true,"codename":"","version_clean":"1.0.0","version":"1.0"},"category":{"_id":"58ed1bdc068f780f00f64602","__v":0,"project":"55de06fa57f7b20d0097636b","version":"55de06fa57f7b20d0097636e","sync":{"url":"","isSync":false},"reference":false,"createdAt":"2017-04-11T18:09:32.839Z","from_sync":false,"order":11,"slug":"data-transfer-and-integration","title":"Data Transfer and Integration"},"updates":[],"next":{"pages":[],"description":""},"createdAt":"2017-04-11T18:10:23.851Z","link_external":false,"link_url":"","githubsync":"","sync_unique":"","hidden":false,"api":{"results":{"codes":[]},"settings":"","auth":"required","params":[],"url":""},"isReference":false,"order":0,"body":"PushSpring audience data is sourced from iOS and Android mobile devices and consists of device advertising identifiers (IDFA for iOS and Android Advertising ID for Android).  Data is organized by a number of attributes including Persona and Calculated Attributes like Gender, app ownership by Genre, and last known IP address.  Each PushSpring attribute has an associated code, and belongs to a standard taxonomy that is available to partners.\nIn addition, customers may use the PushSpring Audience Console to construct Custom Segments using rules like “Devices that own app xxx but not app yyy”.  Device advertising identifiers that fall into these Custom Segments can be transmitted in the formats described below.\nPushSpring does not collect, process, or transfer any Personally Identifiable Information (PII).\nTypical data integration involves importing one or more files that are made available in two PushSpring standard formats.\n[block:api-header]\n{\n  \"title\": \"Data Transfer Method\"\n}\n[/block]\nThe preferred method for a partner to obtain data from PushSpring is via Amazon AWS S3.  PushSpring will provide the partner with AWS S3 credentials and bucket information to use in downloading the data. \n[block:callout]\n{\n  \"type\": \"warning\",\n  \"body\": \"We do not support sending to a partner controlled bucket.  We will provide access to a PushSpring controlled bucket for this integration.\",\n  \"title\": \"S3 Bucket Limitation\"\n}\n[/block]\nPushSpring can also make a REST call (defined by the partner) to notify the partner that a new data file has become available.  The partner can also simply poll the S3 bucket on a schedule convenient to them in order to find and ingest new files.\n\n[block:api-header]\n{\n  \"title\": \"File Formats\"\n}\n[/block]\nFor PushSpring’s standard taxonomy of Personas, App Genre ownership, and demographic attributes we have a single format, merged attributes.\nMerged Attributes is a set of csv files containing all personas, calculated attributes (including app genres owned), and demographic segments. There will be a variable number of files each day.\n[block:api-header]\n{\n  \"title\": \"Data Refresh\"\n}\n[/block]\nPushSpring publishes an entire file refresh daily.  This refresh frequency may change in the future.   For completeness we ask partners to ingest full data files at least weekly.\n\nFiles are created with a path prefix that includes the current date. i.e. s3://<bucket>/<partnername>/syndicated/<YYYYMMDD>/*.csv.gz\n[block:api-header]\n{\n  \"title\": \"Taxonomy File\"\n}\n[/block]\nA taxonomy.csv file is created each time the data is refreshed with the same path prefix as the data.\n\nThe file contains names and descriptions for all persona and genre columns in the file.  It does not include descriptions for all columns notably COMSCORE_GENDER, COMSCORE_AGE, and COMSCORE_INCOME.  For those see the [Merged Format](doc:format-2) documentation. \n\n**Sample:** \n[block:code]\n{\n  \"codes\": [\n    {\n      \"code\": \"id,column,cpm,name,description,category1,category2,category3,category4\\n304,PERSONAID_304,1.5,Auto Shoppers,\\\"Auto Shoppers are predominantly male working professionals 25 - 44, either in the low income bracket of less than $25k or in the high income bracket of $75-$100k.They generally have valuation and listing apps such as Cars.com, AutoTrader, or CarMax.\\\",PushSpring Fraud-Free Mobile App Data,Intent,Automotive & Boating,\\n704,PERSONAID_704,1.5,Boat Shoppers,\\\"Life on the water is the goal of this audience. Skewing male, ages 55+, Boat Shoppers tend to be in the $75K+ HHI brackets. They own boat focused apps including Boat Trader.\\\",PushSpring Fraud-Free Mobile App Data,Intent,Automotive & Boating,\\n800,PERSONAID_800,1.5,Ticket Shoppers,\\\"Ticket Shoppers are evenly distributed across genders and most likely in the 25-34 year age group. This audience is always on the lookout for their next show or event, and rely on the eSeats, StubHub and LiveNation apps.\\\",PushSpring Fraud-Free Mobile App Data,Intent,Events,\",\n      \"language\": \"text\",\n      \"name\": \"taxonomy.csv\"\n    }\n  ]\n}\n[/block]","excerpt":"","slug":"overview-1","type":"basic","title":"Syndicated Segments"}

Syndicated Segments


PushSpring audience data is sourced from iOS and Android mobile devices and consists of device advertising identifiers (IDFA for iOS and Android Advertising ID for Android). Data is organized by a number of attributes including Persona and Calculated Attributes like Gender, app ownership by Genre, and last known IP address. Each PushSpring attribute has an associated code, and belongs to a standard taxonomy that is available to partners. In addition, customers may use the PushSpring Audience Console to construct Custom Segments using rules like “Devices that own app xxx but not app yyy”. Device advertising identifiers that fall into these Custom Segments can be transmitted in the formats described below. PushSpring does not collect, process, or transfer any Personally Identifiable Information (PII). Typical data integration involves importing one or more files that are made available in two PushSpring standard formats. [block:api-header] { "title": "Data Transfer Method" } [/block] The preferred method for a partner to obtain data from PushSpring is via Amazon AWS S3. PushSpring will provide the partner with AWS S3 credentials and bucket information to use in downloading the data. [block:callout] { "type": "warning", "body": "We do not support sending to a partner controlled bucket. We will provide access to a PushSpring controlled bucket for this integration.", "title": "S3 Bucket Limitation" } [/block] PushSpring can also make a REST call (defined by the partner) to notify the partner that a new data file has become available. The partner can also simply poll the S3 bucket on a schedule convenient to them in order to find and ingest new files. [block:api-header] { "title": "File Formats" } [/block] For PushSpring’s standard taxonomy of Personas, App Genre ownership, and demographic attributes we have a single format, merged attributes. Merged Attributes is a set of csv files containing all personas, calculated attributes (including app genres owned), and demographic segments. There will be a variable number of files each day. [block:api-header] { "title": "Data Refresh" } [/block] PushSpring publishes an entire file refresh daily. This refresh frequency may change in the future. For completeness we ask partners to ingest full data files at least weekly. Files are created with a path prefix that includes the current date. i.e. s3://<bucket>/<partnername>/syndicated/<YYYYMMDD>/*.csv.gz [block:api-header] { "title": "Taxonomy File" } [/block] A taxonomy.csv file is created each time the data is refreshed with the same path prefix as the data. The file contains names and descriptions for all persona and genre columns in the file. It does not include descriptions for all columns notably COMSCORE_GENDER, COMSCORE_AGE, and COMSCORE_INCOME. For those see the [Merged Format](doc:format-2) documentation. **Sample:** [block:code] { "codes": [ { "code": "id,column,cpm,name,description,category1,category2,category3,category4\n304,PERSONAID_304,1.5,Auto Shoppers,\"Auto Shoppers are predominantly male working professionals 25 - 44, either in the low income bracket of less than $25k or in the high income bracket of $75-$100k.They generally have valuation and listing apps such as Cars.com, AutoTrader, or CarMax.\",PushSpring Fraud-Free Mobile App Data,Intent,Automotive & Boating,\n704,PERSONAID_704,1.5,Boat Shoppers,\"Life on the water is the goal of this audience. Skewing male, ages 55+, Boat Shoppers tend to be in the $75K+ HHI brackets. They own boat focused apps including Boat Trader.\",PushSpring Fraud-Free Mobile App Data,Intent,Automotive & Boating,\n800,PERSONAID_800,1.5,Ticket Shoppers,\"Ticket Shoppers are evenly distributed across genders and most likely in the 25-34 year age group. This audience is always on the lookout for their next show or event, and rely on the eSeats, StubHub and LiveNation apps.\",PushSpring Fraud-Free Mobile App Data,Intent,Events,", "language": "text", "name": "taxonomy.csv" } ] } [/block]