​
Details

The AI Agent asks pre-configured questions, adapts to responses, and manages objections to ensure seamless data collection. Integrations with NIKO/GHL workflows allow for dynamic storage and post-processing of the collected information. This Scenario helps organizations systematically gather information while maintaining professionalism and privacy compliance.

​
Key Features

  1. Purpose
  • Focused on structured and compliant data collection.
  • Ensures professional communication to build trust with contacts.
  • Adaptable for various use cases, including market research, feedback collection, and more.
  1. Customizable User Input Fields

Users can configure the following fields to guide the AI Agent:

  • Initial Greeting – The opening line of the call to establish trust.
  • Introduction – Script introducing the AI and the purpose of the call.
  • Purpose of Call – Explanation of why the data is being collected.
  • Representative Name–Human contact agent is working on behalf of.
  • Company Name– The organization represented on the call.
  • Profession– Indicates the role or title of the representative the agent is supporting.
  • Data Collection Purpose– Explains why the data is being collected to encourage participation.
  • Estimated Duration– Sets expectations for how long the conversation will take—reduces friction or drop-off.
  • Privacy Statement – Data protection and compliance information.
  • Question Set (1–16) – Configurable questions tailored to specific data collection needs.
  • Objection Handling – Responses to common concerns or pushbacks.
  • Key Information– Highlights essential details or context the AI should reference during the call.
  • Closing Statement – End-of-call script summarizing next steps.
  • Voicemail Message – Script for situations where the contact doesn’t answer.
  1. Objectives
  • Collect structured data efficiently using guided questions.
  • Store collected information securely in NIKO/GHL for post-processing.
  • Enable actionable insights through workflow automation, tagging, and reporting.

Here is the Project Configurations interface of this scenario, alongside instructions and some examples:

Remember that Scenarios are defined at the Project level, and every Campaign inherits the pre-filled fields from the Project, which means every Campaign can have different information in the input boxes, allowing you to tailor communications per Campaign to align with your customer/client or business needs.

​
Example Configurations

Below is a sample setup for a Data Gatherer project configuration in AVA:

  1. Initial Greeting – The opening line of the call to establish trust.
    • “Hello, this is [AI Agent Name]. Am I speaking with [Client Name]?”
    • “Good day, this is [AI Agent Name]. Am I speaking with [Client Name]?”
  2. Introduction – Script introducing the AI and the purpose of the call.
    • “Hi [Client Name], I’m a Virtual Assistant calling on behalf of [Representative Name] from [Company Name]. Is now a good time to chat?”
    • “Hello [Client Name], I’m assisting [Representative Name] at [Company Name]. I’d like to ask a few quick questions if this is a good time.”
  3. Purpose of Call – Explanation of why the data is being collected.
    • “To gather essential information for [specific purpose] and ensure we provide you with the best possible service.”
    • “We’re collecting a few quick insights to better understand your preferences and improve our service offerings.”
  4. Privacy Statement – Data protection and compliance information.
    • “This call is recorded for accuracy purposes, and your data will remain confidential. Is that okay with you?”
    • “All data collected will remain confidential and is used only for internal analysis. Do you consent to proceed?”
  5. Question Set (1–16) – Configurable questions tailored to specific data collection needs.
    • Q1: “Which of the following best describes your age group: 18–24, 25–34, 35–44, or 45+?”
    • Q2: “Do you prefer to shop online, in-store, or both?”
    • Q3: “Would you say price, brand, or sustainability matters most when choosing a product?”
  6. Objection Handling – Responses to common concerns or pushbacks.
    • “I understand you’re busy — this will only take a couple of minutes and can really help us tailor future interactions.”
    • “Totally understandable — would it be okay if we tried again at a more convenient time?”
  7. Closing Statement – End-of-call script summarizing next steps.
    • “Thank you for your time! We’ll process your information and follow up with the next steps shortly.”
    • “Appreciate your input. We’ll be reviewing your responses and will reach out soon with the next steps.”

​
GHL/NIKO Integration and Data Storage

  1. Data Capture in GHL/NIKO
  • Questions and answers are stored in the contact’s Notes section.
  • Data is organized by groups for easy reference (e.g., demographics, preferences).
  • Responses can trigger automated workflows in NIKO/GHL.
  1. Payload Access Example (Accurate Syntax)

Use the following syntax for post-processing in workflows:

Call Status: {{ava_contact_called.call_status}}
Data Gathering Status: {{ava_contact_called.data_status}}

Demographic & Contact Information
Q1: Age Group    {{ava_contact_called.questions_and_answers.0.answer}}
Q2: Shopping Preference    {{ava_contact_called.questions_and_answers.1.answer}}
Q6: Phone Number Confirmation    {{ava_contact_called.questions_and_answers.5.answer}}

Shopping Behavior & Preferences
Q5: Brand Preferences    {{ava_contact_called.questions_and_answers.4.answer}}
Q8: Monthly Budget    {{ava_contact_called.questions_and_answers.7.answer}}

Future Participation & Preferences
Q12: Future Participation Interest     {{ava_contact_called.questions_and_answers.11.answer}}
  1. Example stored data in GHL:
Call Status: Completed
Data Gathering Status: Successful
Demographic Information:
Q1: Age Group - 25-34
Q2: Shopping Preference - Online
Shopping Preferences:
Q5: Brand Preferences - Sustainable products
  1. Automation Possibilities
  • Trigger follow-up campaigns based on specific responses.
  • Apply tags for segmentation.
  • Generate reports from gathered data.

Example Workflow in NIKO/GHL

Below is a sample automation workflow setup for processing Data Gatherer results:

1

Trigger:

Use the Contact Called trigger with filters based on Call Status (e.g., “Completed” or “No Answer”).

2

Action:

Store answers in custom fields using the Update Contact Field action.

3

Post-Processing:

  • Use responses (e.g., Q1-Q16) to tag contacts or trigger follow-ups.
  • Send the call transcript to ChatGPT for summarization or analysis.
4

Outcome:

  • Generate insights, trigger email sequences, or notify team members.

​
FAQs & Troubleshooting

​
General Questions

​
Configuration

​
Usage and Results

For additional questions or guidance, try using our Virtual Support Agent! Available 24/7 to help resolve most issues quickly at thinkrr.ai/support.

If you still need assistance, visit our support site at help.thinkrr.ai and submit a Ticket or contact our team directly at hello@thinkrr.ai.