Data to AI™ / ChatGPT/Google Analytics 4
Get campaign, traffic and revenue answers from Google Analytics 4 in a ChatGPT chat, with every tool call confirmed by you and recent-day caveats spelled out.
Better answers, fewer tokens.
ChatGPT
Which channel brought the most key events for its traffic last month?
Organic Search brought the most Key Events, 1,446. Email converted best, with 7 key events per 100 sessions against 5 for Paid Search and 3 for Organic Search.
| Channel | Sessions | Key Events | Engagement Rate |
|---|---|---|---|
| Organic Search google / organic | 48,200 | 1,446 | 61% |
| Paid Search google / cpc | 21,500 | 1,075 | 58% |
| Email newsletter / email | 6,400 | 448 | 72% |
Sessions are taken by channel without a Page Path breakdown, so no session is counted twice.
Google Analytics 4 measures how people reach and use your website and apps. Dataddo extracts one flexible GA4 dataset: pick from 184 standard metrics and 374 dimensions, plus custom ones defined in your property.
Show Sessions by Session Campaign Name and Session Source Medium for last month, and list every row where the campaign is (not set).
A performance marketer approves each query as ChatGPT runs it and ends up with a list of untagged traffic to fix before the monthly report goes out.
Rank our Google Ads campaigns by Return on ad spend and Ads cost from GA4 for this quarter, and compare each one with last quarter.
A paid media specialist checks which campaigns earn their spend according to the site's own analytics before moving budget between them.
Check data_status first, then rank Item Name by Purchase Revenue over the last four weeks and flag products that fell more than 25%.
An ecommerce team sees which products gained or lost revenue, with the provisional last three days called out before anyone acts on a drop.
Data to AI™ is priced per seat, like the AI assistants your team already uses, with ~25% off on annual billing. Need tailored contracts or volume pricing? Talk to us about Enterprise.
Serve governed business data to Claude, ChatGPT and other AI tools over MCP.
$10.49/month
per seat
3 seats minimum
Flexibly deploy Dataddo in any cloud or hybrid environment.
Custom
We have a payment model that works for you
| Without Dataddo |
With Dataddo
|
Outcome for you | |
|---|---|---|---|
| Bringing GA4 into a chat | Download a GA4 report as CSV, upload it to the conversation, and upload a fresh file each time someone wants another dimension or date range. | A developer-mode app reads your scheduled GA4 source when asked, and you approve each tool call before it runs. | Every lookup visible |
| Untagged campaign traffic | Traffic without campaign tags arrives as (not set), and in a spreadsheet it gets blended into other rows or silently filtered out. | ChatGPT queries Session Campaign Name and Session Source Medium as GA4 returns them, so (not set) rows stay visible and can be listed apart. | Tagging gaps surfaced |
| Questions the data cannot answer | A year-over-year question on a file with eight months of data still gets a confident answer, with no sign that half the period is missing. | The known_gaps tool tells ChatGPT which questions the GA4 data cannot answer, and the GA4 API itself allows up to 1 year of history. | Limits stated upfront |
| Which tools ChatGPT may use | Anyone with the file can paste it into any chat, with no control over what is done with it afterwards. | In the app settings you switch individual Dataddo tools on or off, for example keeping query and describe_entity while turning refresh off. | Only the tools you allow |
| Token consumption | ChatGPT spends tokens exploring raw Google Analytics 4 columns, sampling rows and retrying until it understands the data. | Field definitions and relations are supplied up front, so the model skips the exploration and goes straight to the answer. | Fewer tokens per answer |
| Answer quality | Prone to wrong joins, invented fields and numbers that are hard to check. | Answers grounded in defined fields. In the Dataddo benchmark, 78.5% of questions were answered correctly, against 65.5% with plain CSV files. | Better answers |
The Google Analytics 4 datasets marketing teams use most, with their real field names. ChatGPT queries them by name through the Dataddo semantic layer.
| Dataset | Metrics and attributes |
Ask ChatGPT
|
|---|---|---|
| Users and engagement |
|
On which days did Engagement Rate drop well below normal in Google Analytics? |
| Acquisition |
|
Which Session Campaign Name values are tagged with an inconsistent Session Source Medium? |
| Pages and events |
|
How did Event Count for our form submit Event Name trend after the site redesign? |
| Ecommerce |
|
Which Item Name brought the most Purchase Revenue this quarter? |
| Key events and ads |
|
On which days did Ads cost rise while Key Events stayed flat? |
| Audience |
|
How is our Google Analytics audience split by Device Category this month? |
We asked 43 pre-registered questions of three real datasets - Google Search Console, HubSpot deals and Google Ads - and delivered the same rows to the same model in four ways. Only the data layer changed.
of questions answered correctly - the best of the four delivery methods tested
fewer confidently wrong answers - 14.0% of runs against 24.0% and 26.3%
more correct answers on messy CRM data - better on 8 questions, worse on none
Same model, prompts and rows in every condition; 759 graded runs, ground truth frozen before any run. On Google Search Console alone, documented CSV files did as well as Data to AI™ - the advantage comes from messier data such as HubSpot deals.
Read the benchmark →Extract Google Analytics 4 with Dataddo, picking metrics such as Sessions, Purchase Revenue and Return on ad spend by Session Campaign Name, then attach the source to a ChatGPT destination or AI Model. In ChatGPT on the web, enable developer mode, create an app for https://headless.dataddo.com/mcp-data with OAuth and sign in.
Developer mode is available on Pro, Plus, Business, Enterprise and Education, on the web only. On Business and Enterprise a workspace admin may need to allow developer mode first.
ChatGPT asks for confirmation before each tool call in developer mode. You see which Dataddo tool runs, such as describe_entity or query, before any GA4 numbers come back.
No. The GA4 API allows up to 1 year of historical data. ChatGPT can only answer from the date range your source has extracted, loaded with a full data re-sync for older days.
When Google cannot assign a value such as country or gender, those users are left out of the breakdown, so the parts can add up to less than the total. ChatGPT reads the data as GA4 returns it.
GA4 returns (not set) when it received no value for a dimension, for example traffic without campaign tags. ChatGPT reports those rows as they are, which makes them easy to find and fix.
No. The Data Access MCP server is read-only over extracted data. ChatGPT asks for entities and fields by name, Dataddo never accepts SQL, and nothing is written to Google Analytics.
