Integration with Salesforce centralizes key customer data and lead history, enabling more accurate deal forecasting and targeted marketing initiatives. For instance, users can combine SQL and Python to automatically aggregate deal data, then employ MDX-powered dashboards to track deal closure rates in real time. Moreover, by analyzing support tickets alongside historical customer interactions, teams can uncover insights that directly enhance customer satisfaction. With Morph, these data-driven processes become streamlined, allowing organizations to make faster, more informed decisions 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

• salesforce API Docs