Grow your business with ChatMarketing today. Connect with customers via Messenger, SMS, Email, or IG using ManyChat.
Emit new event when a selected custom field on a user profile is added or updated. See the documentation
Adds a specific tag to a user specified by their user ID. This action is essential to categorize and filter users based on business-specific parameters. See the documentation
Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.
Locates a user based on a particular custom field's value. See the documentation
Delivers a dynamic message to a particular user specified by their user ID. See the documentation
The ManyChat API lets you manage and automate conversations in your chatbot, giving you control over user data, tags, and messaging. Integrating ManyChat with Pipedream can supercharge your chatbot workflows, enabling you to connect your ManyChat bot to various apps and services, automate interactions based on triggers, and analyze chatbot data to improve user engagement.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
manychat: {
type: "app",
app: "manychat",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.manychat.com/fb/page/getInfo`,
headers: {
Authorization: `Bearer ${this.manychat.$auth.api_key}`,
"accept": `application/json`,
},
})
},
})
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.
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)
}