Customer.guru
Customer.guru is an easy-to-setup tool for tracking customer satisfaction using Net Promoter Score. Connect with your customers, in a matter of minutes.
Integrate the Customer.guru API with the Python API
Setup the Customer.guru API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Customer.guru and Python remarkably fast. Free for developers.
Popular Customer.guru and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of Customer.guru#
The Customer.guru API is a potent tool for gauging customer satisfaction and Net Promoter Score (NPS). By integrating with Pipedream, you can automate the collection and analysis of customer feedback, trigger targeted actions based on NPS results, and meld those insights with other data sources. Pipedream's serverless platform lets you create workflows that react to Customer.guru events in real-time, enrich customer data, and drive personalized engagements.
Connect Customer.guru#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
customer_guru: {
type: "app",
app: "customer_guru",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://customer.guru/export/ratings`,
headers: {
"Content-Type": `application/json`,
},
params: {
api_token: `${this.customer_guru.$auth.api_token}`,
api_secret: `${this.customer_guru.$auth.api_secret}`,
},
})
},
})
Overview of Python#
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:
Connect Python#
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}}