Integration with Intercom centralizes chat logs and user interaction histories, enhancing customer engagement and support quality. For example, you can use SQL and Python to automatically aggregate inquiry data, then leverage MDX dashboards for insights into user engagement and response status. Additionally, analyzing support tickets and tracking retention rates allows teams to pinpoint areas for improvement, driving optimized customer experiences. With Morph, these data-driven processes are streamlined, empowering team collaboration and efficient decision-making across the board.

Set up connection information

Please refer to the DB/SaaS Connection to register the integration.

Once the integration is created, you can retrieve an AccessToken using the integration name from get_auth_token. With this token, you can proceed with data processing using the API.

import pandas as pd

import morph
from morph import MorphGlobalContext
from morph_lib.api import get_auth_token

@morph.func
def get_salesforce_opportunities(context: MorphGlobalContext) -> pd.DataFrame:
    access_token = get_auth_token("salesforce-connection-name")

    # ↓↓↓ call API with access_token ↓↓↓

Links

• Intercom API Docs