Investment Satisfaction Surveys
Gather structured feedback from investment clients on advisor performance, portfolio satisfaction, and likelihood to recommend — with branching follow-ups.
Why this matters
PCI-compliant, fully auditable voice automation for loans, collections, onboarding, and fraud prevention. This example shows you how to automate investment satisfaction surveys calls end-to-end with Guava's SDK — no telephony plumbing, no prompt engineering, just Python.
Installation
Install from Guava's private PyPI index. A public package is coming soon — the install command will simplify to pip install guava.
# Step 1: Install Guava
pip install gridspace-guava --extra-index-url https://guava-pypi.gridspace.com
# Public PyPI package coming soon — the install command will simplify to:
# pip install guava
# Step 2: Set your credentials
export GUAVA_API_KEY="..."
export GUAVA_AGENT_NUMBER="..."How it's built
Every Guava agent is a Python class. Walk through the key sections below, then grab the complete file at the end.
Imports
Import the Guava SDK and any helpers you need. guava.CallController is the base class for every voice agent.
# Install: pip install gridspace-guava --extra-index-url https://guava-pypi.gridspace.com
import guava
import osAgent setup
set_persona() defines how the agent presents itself. set_task() gives it its mission in plain English. The checklist drives the conversation — Guava works through it top-to-bottom, collecting Field values and speaking Say items as it goes.
class InvestmentSurveyBot(guava.CallController):
def __init__(self, client_name: str, advisor_name: str):
super().__init__()
self.set_persona(
organization_name="Vantage Wealth Management",
agent_name="Jordan",
)
self.set_task(
objective=f"Conduct a satisfaction survey with {client_name} about their experience with advisor {advisor_name}",
checklist=[
f"Introduce yourself and explain this is a brief satisfaction survey — estimated 2 minutes.",
guava.Field(
key="overall_satisfaction",
field_type="rating",
description="Overall satisfaction with wealth management services (1-10)",
),
guava.Field(
key="advisor_satisfaction",
field_type="rating",
description=f"Satisfaction with advisor {advisor_name} specifically (1-10)",
),
guava.Field(
key="nps_score",
field_type="rating",
description="How likely to recommend Vantage to a friend or colleague (0-10)",
),
guava.Field(
key="improvement_feedback",
field_type="text",
description="One thing the client would most like to see improved",
required=False,
),
guava.Field(
key="ok_to_contact",
field_type="bool",
description="Can an advisor follow up on this feedback?",
),
"Thank the client for their time.",
],
on_complete=lambda fields: print(f"Survey complete: {client_name} NPS={fields.get('nps_score')}"),
)
guava.dial(
controller=InvestmentSurveyBot,
controller_args={"client_name": "Harold Chen", "advisor_name": "Ms. Reeves"},
to=os.environ["CLIENT_PHONE"],
agent_number=os.environ["GUAVA_AGENT_NUMBER"],
api_key=os.environ["GUAVA_API_KEY"],
)Platform performance
<1s
Response time
99.99%
Uptime SLA
13+
Industries served
Full example
The complete file — copy it, save it as example.py, and run it.
# Install: pip install gridspace-guava --extra-index-url https://guava-pypi.gridspace.com
import guava
import os
class InvestmentSurveyBot(guava.CallController):
def __init__(self, client_name: str, advisor_name: str):
super().__init__()
self.set_persona(
organization_name="Vantage Wealth Management",
agent_name="Jordan",
)
self.set_task(
objective=f"Conduct a satisfaction survey with {client_name} about their experience with advisor {advisor_name}",
checklist=[
f"Introduce yourself and explain this is a brief satisfaction survey — estimated 2 minutes.",
guava.Field(
key="overall_satisfaction",
field_type="rating",
description="Overall satisfaction with wealth management services (1-10)",
),
guava.Field(
key="advisor_satisfaction",
field_type="rating",
description=f"Satisfaction with advisor {advisor_name} specifically (1-10)",
),
guava.Field(
key="nps_score",
field_type="rating",
description="How likely to recommend Vantage to a friend or colleague (0-10)",
),
guava.Field(
key="improvement_feedback",
field_type="text",
description="One thing the client would most like to see improved",
required=False,
),
guava.Field(
key="ok_to_contact",
field_type="bool",
description="Can an advisor follow up on this feedback?",
),
"Thank the client for their time.",
],
on_complete=lambda fields: print(f"Survey complete: {client_name} NPS={fields.get('nps_score')}"),
)
guava.dial(
controller=InvestmentSurveyBot,
controller_args={"client_name": "Harold Chen", "advisor_name": "Ms. Reeves"},
to=os.environ["CLIENT_PHONE"],
agent_number=os.environ["GUAVA_AGENT_NUMBER"],
api_key=os.environ["GUAVA_API_KEY"],
)Run it
Start the agent. It will connect to Guava's infrastructure and begin accepting calls on your assigned number.
python example.py