All
perm_phone_msg
Twitter Targeting
Adjusts line item settings based on Twitter hashtags and locations specified in a sheet.
Impact Level
| Spend Optimization |
|
| Spend Growth |
|
| Time Savings |
|
| Account Health |
|
| Csat Improvement |
|
Value Proposition
| Create campaigns that respond to twitter trends. |
| Activate spend when a specific tag trends. |
| Protect brand by disabling advertising based on trends. |
| Fully automated, just provide locations, hashtags and line item settings to change. |
Instructions
| Click Run Now and a sheet called Twitter Targeting will be generated with a tab called Twitter Triggers. |
| Follow instructions on the sheets tab to provide triggers and lineitems. |
| Click Run Now again, trends are downloaded and triggered. |
| Or give these intructions to the client. |
Details
| Open Source | YES |
| Age | June 4, 2018 (4 years, 7 months) |
| Authors | kenjora@google.com |
| Shedule Days | Configured by user. |
| Shedule Hours | 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24 |
[
{
"dataset": {
"description": "Create a dataset where data will be combined and transfored for upload.",
"auth": {
"field": {
"name": "auth_write",
"kind": "authentication",
"order": 1,
"default": "service",
"description": "Credentials used for writing data."
}
},
"dataset": {
"field": {
"name": "recipe_slug",
"kind": "string",
"order": 1,
"description": "Place where tables will be created in BigQuery."
}
}
}
},
{
"sheets": {
"description": "Read mapping of hash tags to line item toggles from sheets.",
"auth": {
"field": {
"name": "auth_read",
"kind": "authentication",
"order": 0,
"default": "user",
"description": "Credentials used for reading data."
}
},
"template": {
"sheet": "https://docs.google.com/spreadsheets/d/1iYCGa2NKOZiL2mdT4yiDfV_SWV9C7SUosXdIr4NAEXE/edit?usp=sharing",
"tab": "Twitter Triggers"
},
"sheet": {
"field": {
"name": "recipe_name",
"kind": "string",
"prefix": "Twitter Targeting For ",
"order": 2,
"description": "Name of sheet where Line Item settings will be read from.",
"default": ""
}
},
"tab": "Twitter Triggers",
"range": "A7:E",
"out": {
"bigquery": {
"dataset": {
"field": {
"name": "recipe_slug",
"kind": "string",
"description": "Place where tables will be created in BigQuery."
}
},
"table": "Twitter_Triggers",
"schema": [
{
"name": "Location",
"type": "STRING",
"mode": "REQUIRED"
},
{
"name": "WOEID",
"type": "INTEGER",
"mode": "REQUIRED"
},
{
"name": "Hashtag",
"type": "STRING",
"mode": "REQUIRED"
},
{
"name": "Advertiser_Id",
"type": "INTEGER",
"mode": "REQUIRED"
},
{
"name": "Line_Item_Id",
"type": "INTEGER",
"mode": "REQUIRED"
}
]
}
}
}
},
{
"twitter": {
"description": "Read trends from Twitter and place into BigQuery.",
"auth": {
"field": {
"name": "auth_write",
"kind": "authentication",
"order": 1,
"default": "service",
"description": "Credentials used for writing data."
}
},
"secret": {
"field": {
"name": "twitter_secret",
"kind": "string",
"order": 3,
"default": "",
"description": "Twitter API secret token."
}
},
"key": {
"field": {
"name": "twitter_key",
"kind": "string",
"order": 4,
"default": "",
"description": "Twitter API key token."
}
},
"trends": {
"places": {
"single_cell": true,
"bigquery": {
"dataset": {
"field": {
"name": "recipe_slug",
"kind": "string",
"description": "Place where tables will be created in BigQuery."
}
},
"query": "SELECT DISTINCT WOEID FROM {dataset}.Twitter_Triggers",
"legacy": false,
"parameters": {
"dataset": {
"field": {
"name": "recipe_slug",
"kind": "string",
"description": "Place where tables will be created in BigQuery."
}
}
}
}
}
},
"out": {
"bigquery": {
"dataset": {
"field": {
"name": "recipe_slug",
"kind": "string",
"description": "Place where tables will be created in BigQuery."
}
},
"table": "Twitter_Trends_Place"
}
}
}
},
{
"google_api": {
"description": "Combine sheet and twitter data into API operations for each line item. Match all possibilities and PAUSE if no trigger match.",
"auth": {
"field": {
"name": "auth_write",
"kind": "authentication",
"order": 1,
"default": "service",
"description": "Credentials used for writing data."
}
},
"api": "displayvideo",
"version": "v1",
"function": "advertisers.lineItems.patch",
"kwargs_remote": {
"bigquery": {
"dataset": {
"field": {
"name": "recipe_slug",
"kind": "string",
"order": 4,
"default": "",
"description": "Name of Google BigQuery dataset to create."
}
},
"query": " SELECT CAST(S.Advertiser_Id AS STRING) advertiserId, CAST(S.Line_Item_Id AS STRING) AS lineItemId, STRUCT( IF(LOGICAL_OR(T.Name is NULL), 'ENTITY_STATUS_ACTIVE', 'ENTITY_STATUS_PAUSED') AS entityStatus ) AS body, 'entityStatus' AS updateMask, FROM `{dataset}.Twitter_Triggers` AS S LEFT JOIN `{dataset}.Twitter_Trends_Place` As T ON S.WOEID=T.WOEID AND REPLACE(LOWER(S.Hashtag), '#', '')=REPLACE(LOWER(T.Name), '#', '') GROUP BY 1,2 ",
"parameters": {
"dataset": {
"field": {
"name": "recipe_slug",
"kind": "string",
"description": "Place where tables will be created in BigQuery."
}
}
}
}
},
"results": {
"bigquery": {
"dataset": {
"field": {
"name": "recipe_slug",
"kind": "string",
"order": 4,
"default": "",
"description": "Name of Google BigQuery dataset to create."
}
},
"table": "Trigger_Results"
}
},
"errors": {
"bigquery": {
"dataset": {
"field": {
"name": "recipe_slug",
"kind": "string",
"order": 4,
"default": "",
"description": "Name of Google BigQuery dataset to create."
}
},
"table": "Trigger_Errors"
}
}
}
}
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