PLUGIN SETUP
Start using CallRail in ChatGPT
Connect CallRail to Adzviser, install Adzviser in ChatGPT, and start asking questions about your data.
Connect CallRail to Adzviser
Connect CallRail using an API key, then select one company for the workspace.
Install Adzviser in ChatGPT
Open Adzviser in ChatGPT's plugin directory, install it, and sign in to your Adzviser account when asked.
Open Adzviser in ChatGPT ↗Ask your first CallRail question
Start a new ChatGPT conversation and ask Adzviser to list your workspaces and show the company connected to each. Choose a workspace, ask about performance or trends, and continue with follow-up questions.
CHOOSE THE RIGHT CHATGPT CONNECTOR
CallRail in ChatGPT: CallRail's official MCP server vs. Adzviser's read-only reporting connector
This side-by-side comparison covers CallRail's official MCP server and Adzviser's read-only CallRail reporting connector in ChatGPT. CallRail offers a first-party connection for call analytics and supported account actions. Adzviser keeps CallRail read-only and adds the campaigns and channels that drove those leads.
CallRail's official MCP server
Analyze CallRail with optional record and SMS actions
Connect with a CallRail-provided MCP URL in a supported paid AI plan. This is a manual ChatGPT connection: enable Developer mode, add that remote MCP address, and authorize it. Developer mode availability depends on the account and workspace policy.
Investigate calls, forms, messages, and lead journeys; optionally use enabled record or SMS tools.
Can analyze calls and leads; enabled write tools can update records or send SMS.
CallRail only: work with calls, forms, messages and lead journeys.
Best for: teams that only need CallRail context in their AI assistant.
Read CallRail's API documentationAdzviser's read-only CallRail reporting connector
Analyze CallRail with your other marketing data in ChatGPT
Connect CallRail in Adzviser, then install Adzviser from ChatGPT's plugin directory.
Open with a question about calls, sources, campaigns and conversions, inspect the answer, and continue the same conversation with follow-up questions.
Read-only reporting; ChatGPT cannot change anything in CallRail through Adzviser.
Analyze CallRail in the same ChatGPT conversation as connected advertising, analytics, commerce, email, and CRM sources.
Best for: marketers and agencies that want read-only CallRail reporting beside other marketing and revenue data in ChatGPT.
Open Adzviser in ChatGPTCONVERSATION FLOW
Turn CallRail data into clear next steps in ChatGPT
Start with the results, focus on the decision in front of you, and keep asking follow-up questions in the same conversation.
Review recent performance
Weekly overview of call tracking metrics. Ask for a compact table and make the reporting period clear.
See the “Weekly Call Volume Summary” promptFocus on a decision
Optimize marketing spend based on call attribution. Ask ChatGPT to compare the options, supporting evidence, and possible downsides.
See the “Marketing Channel ROI Optimization” promptAsk a follow-up
Compare recent results with the previous period and call out the largest changes. Ask what may explain the result, what evidence is missing, and what to examine next.
See the “Call Trend Analysis” promptCHATGPT STARTERS
Start with a quick check, then analyze CallRail
First, confirm ChatGPT can access the right data. Then ask a detailed question and follow up on the recommendation that matters most.
List my connected CallRail companies and show the Adzviser workspace for each. After I choose one, return "Calls" for the last 7 complete days.
Optimize marketing spend based on call attribution.
Analyze CallRail call attribution ROI from the workspace I choose for the last 30 complete days. For each source: Calls, Qualified Calls, Estimated Marketing Cost, and Cost per Qualified Call. Which sources deliver the best call ROI? Recommend budget reallocation.
Keep the same data source and time period. Which recommendation should I prioritize, what results support it, and what should I review before acting on it?
