QuestionPro

Advancing research for everyone.

Integrate the QuestionPro API with the Go API

Setup the QuestionPro API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate QuestionPro and Go remarkably fast. Free for developers.

Run Go Code with the Go API

Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.

 
Try it

Overview of QuestionPro

QuestionPro provides a suite of tools to create, distribute, and analyze surveys. Utilizing its API within Pipedream allows you to automate workflows around survey distribution, response collection, and data analysis. You can trigger actions based on new survey responses, generate reports, and integrate survey data with other apps to enrich customer profiles, support decision-making processes, or measure satisfaction levels across various services.

Connect QuestionPro

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    questionpro: {
      type: "app",
      app: "questionpro",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://${this.questionpro.$auth.environment}.questionpro.com/a/api/v2/organizations/4734262`,
      params: {
        apiKey: `${this.questionpro.$auth.api_key}`,
      },
    })
  },
})

Overview of Go

You can execute custom Go scripts on-demand or in response to various triggers and integrate with thousands of apps supported by Pipedream. Writing with Go on Pipedream enables backend operations like data processing, automation, or invoking other APIs, all within the Pipedream ecosystem. By leveraging Go's performance and efficiency, you can design powerful and fast workflows to streamline complex tasks.

Connect Go

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package main

import (
	"fmt"

	pd "github.com/PipedreamHQ/pipedream-go"
)

func main() {
	// Access previous step data using pd.Steps
	fmt.Println(pd.Steps)

	// Export data using pd.Export
	data := make(map[string]interface{})
	data["name"] = "Luke"
	pd.Export("data", data)
}