Supermetrics for ChatGPT

Supermetrics for ChatGPT gives you seamless access to your marketing data across all your main marketing platforms, including Google Ads, Meta Ads, Instagram, Google Analytics, LinkedIn Ads, TikTok, Shopify, Amazon and more. This offers invaluable insights right within ChatGPT. You can ask the AI chatbot questions to understand your marketing data better and further enhance your data retrieval and analysis processes.

Data sources you can use include:

• Advertising: Google Ads, Facebook Ads (Meta), Instagram Insights, LinkedIn Ads, TikTok Ads, Microsoft Advertising (Bing), Snapchat Marketing, Pinterest Ads, Amazon Ads, Amazon DSP, X Ads (Twitter), Reddit Ads, Quora Ads, Criteo, The Trade Desk, Google Display & Video 360, Google Campaign Manager 360, Google Search Ads 360, Taboola, Outbrain Amplify, Spotify Ads, ChatGPT Ads

• Web and app analytics: Google Analytics 4, Google Search Console, Adobe Analytics, Matomo, Piwik PRO, Plausible, Mixpanel, Amplitude, AppsFlyer, Adjust, Branch, Google Play Console

• E-commerce: Shopify, WooCommerce, BigCommerce, Adobe Commerce (Magento 2), Stripe, Recharge, Squarespace Commerce, Wix Commerce, Google Merchant Center, Walmart Connect, Lazada, Shopee

• CRM and email:  HubSpot, Salesforce, Klaviyo, Mailchimp, Marketo, Brevo, Braze, Omnisend, Pipedrive, Zoho CRM, Close CRM, Eloqua

• SEO, social, and research: Semrush Analytics, Ahrefs, Similarweb, Google Trends, YouTube, TikTok Organic, LinkedIn Company Pages, Pinterest Organic, Threads Insights, Sprout Social, Sprinklr, G2 Reviews, Capterra Reviews, Glassdoor Reviews, Yelp Reviews, Tripadvisor Reviews

• Data warehouses and data preparation: Google BigQuery, Snowflake, Google Sheets, Data Blending

Some sources need no connection at all — Google Trends, Facebook Public Data, Instagram Public Data, Apple Public Data, and G2 Reviews return data immediately, without the need to authenticate.

See the list of Supermetrics data sources you can use in your AI chats.

By following the best practices outlined in this article, you can make the most out of the Supermetrics ChatGPT integration for data analysis.

Before you begin

Note the following requirements for using AI chats:

Instructions

There are two ways to get the Supermetrics ChatGPT integration:

• Option 1: Go to our ChatGPT product page, and click Try for free.

• Option 2: In ChatGPT, go to Plugins, and search for "Supermetrics".

Supermetrics will prompt you to authenticate your connection to the data sources as necessary. To connect your data and select the teams to use, authenticate the connection using your Google or Microsoft account, the same one you use to log in to Supermetrics Hub.

For more use case examples and best practices, see How to connect Supermetrics to AI tools and Use cases for Supermetrics AI chats and Supermetrics MCP server.

Use case examples for ChatGPT

Executive 30–90 day performance deck

Goal: Turn cross‑channel performance data into a slide‑ready executive review.

Example flow:

1. Pull the data

   • Pull the last 30 days of performance data from my Google Ads and Facebook Ads accounts. Clicks, Cost, and Impressions by data source, date, and campaign name.

2. Build the deck outline

   • Create a marketing performance overview as a slide‑ready deck, including in different slides a summary intro, individual channel‑level deep dives, cross‑channel comparisons, strategic recommendations, a next‑period forecast, and actionable next steps. Structure it into a clean, concise slide outline with titles, subtitles, bullet points, and insight callouts.

3. Generate the exec email

   • Write a concise email summarizing the deck to share with my CMO.

Outcome:

• Ready‑to‑use deck structure for quarterly or Month-over-Month reviews

• Clear talking points and recommendations, grounded in real data

• Saved time vs. building slides manually from spreadsheets

Week‑over‑week campaign optimization

Goal: Compare a single campaign across channels week‑over‑week and get an optimization plan.

Example flow:

1. Pull Week-over-Week data

   • Pull performance data for my ‘Brand Testimonial’ campaign running on LinkedIn Ads and Facebook Ads. Retrieve data for the last 7 days and the previous 7‑day period.

2. Visual WoW comparison

   • Provide a cross‑channel visual performance analysis of the campaign, comparing this week vs. the previous week.

3. Optimization plan

   • Provide a document that includes recommended optimizations for my campaign.

Outcome:

• Simple Week-over-Week charts/tables (CPA, spend, clicks, conversions)

• Channel‑specific actions (pause, scale, test) derived from the data

• Reusable “performance review” prompt pattern that can be run weekly

Budget pacing check

Goal: Catch over- and under-delivery before the month closes.

Example flow:

1. Pull the month-to-date spend

   • Pull month-to-date spend from all my connected ad platforms, broken down by channel and week.

2. Compare against budget

   • Compare each channel's actual spend against a €X monthly budget. Show percent paced, projected end-of-month spend at the current run rate, and flag anything more than 10% off target.

3. Reallocate

   • Recommend where to shift the budget based on which channels have the best CPA.

Outcome:

• A pacing view across every connected platform at once

• Projected month-end spend early enough in the month to act on

• Reusable monthly check that takes a minute instead of a morning

Pause and reallocate underperforming spend

Goal: Find campaigns missing their targets, pause them, and move the budget — without leaving the chat.

Example flow:

1. Review performance against target

   • Pull the last 14 days from my Google Ads and Facebook Ads accounts. Cost, conversions, and CPA by campaign, and flag anything with a CPA above €50.

2. Pause the worst offenders

   • Pause the three campaigns with the highest CPA. Show me the proposed changes before you apply them.

3. Reallocate the freed budget

   • Take the daily budget from those paused campaigns and recommend where to move it, based on which live campaigns have the best CPA over the same period.

4. Apply and confirm

   • Apply the budget increases you recommended, and list what changed.

Outcome:

• Underperformers paused and budget redeployed in one conversation, not four platform interfaces

• Every proposed change is shown for review before it goes live

• A full record in Campaign history on the Supermetrics Hub, so any change can be reverted

See How to manage ad campaigns with AI tools for more details.

Build a dashboard in chat, share it from Supermetrics Studio

Goal: Turn a one-off analysis into a live dashboard your team can open, without rebuilding it.

Example flow:

1. Pull the data

   • Pull the last 30 days from my Google Ads and GA4 accounts. Spend, clicks, and conversions from Google Ads, and sessions and engagement rate from GA4, by date.

2. Build the view

   • Build a cross-channel dashboard from this: scorecards for total spend and conversions, a line chart of spend against sessions by day, and a table of the top 10 campaigns by conversions.

3. Add context

   • Add a short summary above the charts explaining the main trend.

4. Hand off to Studio

   • Push this dashboard to Supermetrics Studio.

5. Refine it in Studio

   • Open the dashboard in Supermetrics Studio, then keep prompting in natural language to adjust layout, chart types or colours.

With the AI chats destination subscription, you can push dashboards from AI tools to Supermetrics Studio as well as view and share them. To edit dashboards in Supermetrics Studio and unlock all Studio features, you need a Supermetrics Studio destination subscription.

Outcome:

• A shareable dashboard that refreshes on its own, rather than a chat thread that goes stale

• The analysis done where you asked the question, the sharing done where your team already looks

• A reusable dashboard you can keep tuning in Studio without going back to the chat

More resources

• How to connect Supermetrics to AI tools

• Use cases for Supermetrics AI chats and Supermetrics MCP server