PLUGIN SETUP
Start using MNTN in ChatGPT
Connect MNTN to Adzviser, install Adzviser in ChatGPT, and start asking questions about your data.
Connect MNTN to Adzviser
Connect MNTN using an API key.
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 MNTN question
Start a new ChatGPT conversation and ask Adzviser to list your workspaces and show the reporting scope connected to each. Choose a workspace, ask about performance or trends, and continue with follow-up questions.
CONVERSATION FLOW
Turn MNTN 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 Connected TV spend and reach overview. Ask for a compact table and make the reporting period clear.
See the “Weekly CTV Performance” promptFocus on a decision
Optimize campaigns for return on ad spend. Ask ChatGPT to compare the options, supporting evidence, and possible downsides.
See the “ROAS Optimization” promptAsk a follow-up
Measure incremental new-customer lift from CTV. Ask what may explain the result, what evidence is missing, and what to examine next.
See the “New vs Existing Visitor Lift” promptCHATGPT STARTERS
Start with a quick check, then analyze MNTN
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 MNTN reporting connections and show the Adzviser workspace for each. After I choose one, return "Raw revenue per raw visit" for the last 7 complete days.
Optimize campaigns for return on ad spend.
Review the MNTN Connected TV ROAS performance for the workspace I choose during the last 30 complete days. For each Campaign name show: Total spend, Order value, Average order value, Total conversions, CPA, ROAS, and ROI. Which campaigns deliver the best ROAS? Recommend budget shifts to maximize return.
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?
