An end-to-end Conversational Experience Management Platform that helps get 40% better response rate.
Emit new event when a customer effort score (CES) survey receives a new submission.
Emit new event when a customer satisfaction (CSAT) survey receives a new submission.
Emit new event when a net promoter score (NPS) survey receives a new submission.
Emit new event each time a the specified survey receives a response.
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Sends a saved NPS share template via SMS to given mobile number recipients. See the documentation
Sends a saved email share template to a provided email address. Configure the saved template's name and the recipient's email address. See the documentation
The SurveySparrow API lets you tap into a robust platform for gathering feedback and insights. With Pipedream, you can automate interactions with your surveys, manage contacts, and analyze responses in real time. You can create workflows that trigger on new survey responses, sync data to other services, or even kick off email campaigns based on survey results. The power of Pipedream's serverless platform means you can integrate SurveySparrow with hundreds of other apps, enabling limitless automation scenarios without writing extensive code.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
surveysparrow: {
type: "app",
app: "surveysparrow",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.surveysparrow.com/v1/contacts`,
headers: {
Authorization: `Bearer ${this.surveysparrow.$auth.access_token}`,
},
})
},
})
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}}