The Supermetrics ChatGPT integration gives you seamless access to your marketing data across different platforms, offering invaluable insights right within ChatGPT. You can ask the AI chatbot questions to understand your data better and further enhance your data retrieval and analysis processes.
By following the best practices outlined in this article, you can make the most out of the Supermetrics ChatGPT integration for data analysis.
The Supermetrics ChatGPT integration is available for users with ChatGPT Business or Enterprise plan.
Data sources supported by the Supermetrics ChatGPT integration
Amazon Ads
Adobe Analytics 2.0
Adform
Google AdSense
AdRoll
Apple Search Ads
Adobe Analytics
Google Ads
Bing Webmaster Tools
Criteo
Google Display & Video 360
Google Campaign Manager 360
Google Ad Manager
Facebook Ads
Facebook Insights
Google Analytics 4
Google My Business
Google Search Console
HubSpot
Instagram Insights
Klaviyo
LinkedIn Ads
LinkedIn Company Pages
Marketo
MailChimp
Outbrain Amplify
Pinterest Ads
Quora Ads
Snapchat Marketing
Salesforce
Shopify
StackAdapt
X Ads (Twitter)
TikTok Ads
The Trade Desk
Yahoo DSP
Yandex.Direct
Yandex.Metrica
How to start using the Supermetrics ChatGPT integration
There are two ways to get the Supermetrics ChatGPT integration:
Option 1: Click this direct link to access the Supermetrics ChatGPT integration.
Option 2: In ChatGPT, go to Explore GPTs, and search for "Supermetrics".
The Supermetrics ChatGPT integration will prompt you to authenticate your connection to the data sources as necessary. To connect your data, authenticate the connection using your Google or Microsoft account, the same one you use to log in to Supermetrics Hub.
How to secure your data while using Supermetrics integration in ChatGPT
If you want to prevent OpenAI from using your data for future training of its AI software, go to Settings → Data Controls and disable the Chat history & training setting before using the Supermetrics integration.
After you disable the chat history and training, be aware that once a conversation is closed, it can't be retrieved anymore. If any valuable information, data, or graphs are generated during a chat that you want to save for later, make sure to save the data before ending the session.
Best practices for using Supermetrics ChatGPT integration
Specify metrics and date range when fetching data
When querying data, ensure that you specify the following in your prompt to guarantee the accuracy and relevance of the responses:
Date range, such as 'past 7 days' or 'last month'
Metrics, such as 'Impressions', 'Clicks', 'Cost', 'CTR', or 'CPC'
Dimensions for breakdown, such as 'breakdown by country' or 'use age group for rows'
Examples
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Tips for optimizing the output
If the outputs are too long, ask the for a shorter response.
If outputs are too simple, ask for an expert-level response or elaboration with more details.
If you want information in a structured way, ask the AI chatbot to show the results in a table format.
Specify the task when initiating or transitioning between tasks
Initiate each task with a specific prompt that informs the Supermetrics ChatGPT integration about the task at hand. For example, start with a prompt like "Next, help me with analyzing marketing data for my fashion webshop" or "Let's gather advertising data for an educational app and then analyze it to refine marketing strategies."
If you're transitioning to a new task that doesn't require previous data or context, start a fresh conversation. This ensures that the chatbot doesn't inadvertently use outdated information for the new task.
Specify each step for complex tasks
If you need the Supermetrics ChatGPT to perform a series of tasks, break them down into smaller, more manageable steps. This will help the chatbot understand your instructions and execute the tasks accurately.
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Instruct the ChatGPT integration to reason step-by-step
Often, questions seem obvious and simple to a human but actually involve many more steps of reasoning for an AI. "Let's think step by step" or "Explain your chain of reasoning before answering" would be good instructions to be included in your prompt. This helps understand the logic behind the insights, aiding better decision-making.
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Encourage the ChatGPT integration to provide multiple solutions or options
Sometimes, after the integration provides you with the specific metrics and data, you may find yourself overwhelmed or unsure of how to proceed with the analysis. To move forward, you can ask the chatbot to generate multiple possible solutions along with their corresponding pros and cons. This will help you narrow down your options and guide the chatbot in the most appropriate direction. The chatbot can even select and justify the most suitable solution for your specific needs.
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Ask the GPT to adopt a persona or even multi-role-play
Include a persona for the chatbot to assume in your prompt, such as "Think like a digital marketing expert. You need to perform a task to…".
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You can even ask the model to adopt several different roles at the same time, challenge, validate, and refine actions or suggestions on each persona, and continue for multiple rounds to find the best result.
An example prompt of 3-role-play for modification/copying
Now you need to play 3 different roles. Role A, a PPC marketer adjusting online ad spend based on performance; Role B, an Account Manager overseeing marketing strategies, supervising Role A, and deriving insights from data; Role C, a client needing an overview of marketing data for business decisions and seeking advice on improving marketing efficiency. In a review meeting, these roles will interact, discussing past ad performances and planning optimizations for the next week. Use data from Supermetrics ChatGPT integration when necessary and avoid fabricating results. During data analysis, clearly explain your reasoning step by step, ensuring accuracy. Begin now.
Prompt examples
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Use delimiters to clearly separate contents
Delimiters, such as triple quotations, can help separate different types of content clearly. With delimiters, you can break longer prompts into sections, and make it clear for the language model to understand which part of the prompt text needs to be treated differently.
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