Integrate the Customer.guru API with the Go API

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

Popular Customer.guru and Go Actions#

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 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 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#

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)
}