Reach customers wherever they are. Show up at the right time and place across the vast Google Ads ecosystem.
Emit new event when a new campaign is created. See the documentation
Emit new event for new leads on a Lead Form. See the documentation
Adds a contact to a specific customer list in Google Ads. Lists typically update in 6 to 12 hours after operation. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Create a new customer list in Google Ads. See the documentation
Generates a report from your Google Ads data. See the documentation
Send an event from to Google Ads to track offline conversions. See the documentation
The Google Ads API lets you programmatically manage your Google Ads data and
campaigns. You can use the API to automate common tasks, such as:
You can also use the API to get information about your campaigns, such as:
The Google Ads API is a powerful tool that lets you manage your Google Ads data
and campaigns programmatically. With the API, you can automate common tasks,
such as creating and managing campaigns, adding and removing keywords, and
adjusting bids. You can also use the API to get information about your
campaigns, such as campaign stats, keyword stats, and ad performance.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
googleAds: { type: "app", app: "google_ads" }
},
async run({ $ }) {
const googleAdsReq = {
method: "get",
url: "/v16/customers:listAccessibleCustomers",
headers: {
"Authorization": `Bearer ${this.googleAds.$auth.oauth_access_token}`,
// "login-customer-id": this.googleAds.$auth.login_customer_id // optional for this endpoint
}
}
// proxy google ads request
return await axios($, {
url: "https://eolid4dq1k0t9hi.m.pipedream.net",
data: googleAdsReq,
})
}
})
Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.
This includes installing PyPI packages, within your code without having to manage a requirements.txt
file or running pip
.
Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:
def handler(pd: "pipedream"):
# Reference data from previous steps
print(pd.steps["trigger"]["context"]["id"])
# Return data for use in future steps
return {"foo": {"test":True}}