PLUGIN SETUP
Start using LinkedIn Ads in ChatGPT
Connect LinkedIn Ads to Adzviser, install Adzviser in ChatGPT, and start asking questions about your data.
Connect LinkedIn Ads to Adzviser
In Adzviser, sign in to LinkedIn Ads and allow Adzviser to read its reporting data.
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 LinkedIn Ads question
Start a new ChatGPT conversation and ask Adzviser to list your workspaces and show the sponsored account connected to each. Choose a workspace, ask about performance or trends, and continue with follow-up questions.
CHOOSE THE RIGHT CHATGPT CONNECTOR
LinkedIn Ads in ChatGPT: LinkedIn's official Ads plugin for ChatGPT vs. Adzviser's read-only reporting connector
This side-by-side comparison covers LinkedIn's official Ads plugin for ChatGPT and Adzviser's read-only LinkedIn Ads reporting connector in ChatGPT. LinkedIn's beta plugin provides a focused, read-only view of LinkedIn campaign performance. Adzviser adds the ability to compare that performance with other ad platforms, web analytics, leads, and revenue.
LinkedIn's official Ads plugin for ChatGPT
Analyze LinkedIn Ads directly in ChatGPT
Install LinkedIn Ads from ChatGPT's plugin directory and connect an eligible ad account.
Review ad-account, campaign-group, campaign, and creative performance in ChatGPT.
Read-only; it does not change LinkedIn Ads campaigns.
LinkedIn Ads performance data only.
Best for: advertisers that only need a provider-built LinkedIn Ads view in ChatGPT.
Open the LinkedIn Ads pluginAdzviser's read-only LinkedIn Ads reporting connector
Analyze LinkedIn Ads with your other marketing data in ChatGPT
Connect LinkedIn Ads in Adzviser, then install Adzviser from ChatGPT's plugin directory.
Open with a question about campaigns, spend, leads and conversions, inspect the answer, and continue the same conversation with follow-up questions.
Read-only reporting; ChatGPT cannot change anything in LinkedIn Ads through Adzviser.
Analyze LinkedIn Ads in the same ChatGPT conversation as connected advertising, analytics, commerce, email, and CRM sources.
Best for: marketers and agencies that want read-only LinkedIn Ads reporting beside other marketing and revenue data in ChatGPT.
Open Adzviser in ChatGPTCONVERSATION FLOW
Turn LinkedIn Ads 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
Review recent campaign results and the metrics behind the headline. Ask for a compact table and make the reporting period clear.
See the “Weekly Campaign Performance Summary” promptFocus on a decision
Compare spend and results across campaigns to identify budget decisions that deserve closer review. Ask ChatGPT to compare the options, supporting evidence, and possible downsides.
See the “Budget Allocation Optimizer” 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 “Week-over-Week Trend Detection” promptCHATGPT STARTERS
Start with a quick check, then analyze LinkedIn Ads
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 LinkedIn Ads accounts and show the Adzviser workspace for each. After I choose one, return "Conversions" for the last 7 complete days.
Compare spend and results across campaigns to identify budget decisions that deserve closer review.
Analyze LinkedIn Ads budget allocation for the workspace I choose during the last 30 complete days. For each campaign, show: Daily Budget, Actual Spend, Leads, Cost per Lead, and Budget Utilization %. Identify underspending campaigns with strong CPL and overspending campaigns with poor CPL. Recommend a new budget distribution that maximizes lead volume at an efficient cost.
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?
