Analytics as a Conversation
Analytics rarely fails due to a lack of data. It fails because no one has the time or inclination to extract it from the tool. When the hurdle drops from “configuring complicated explorations” to “typing a query,” data suddenly becomes part of everyday life—in meetings, right before a call with a client, or while writing the monthly report.
That is exactly our goal: not more dashboards, but less friction between the question and the answer.
The data is already there—you just have to go straight to it
GA4 exports all data and every single event in raw format to a BigQuery warehouse upon request. No sampling, no pre-built reports, no aggregation that someone else has decided for us. Just the data, exactly as it was collected.
That’s exactly where our dashboard comes in. Instead of going through the GA4 interface, we access the BigQuery data warehouse directly. The dashboard displays the metrics that really matter to the client—trends, channels, countries, top pages, events, devices—in real time for the selected time period. One report, one URL, no 40 menu items, no configuration required, and directly connected to the desired LLM.
This simplification is half the battle: The customer never has to open GA4. They see their data presented in a way that makes sense for their business—not the way Google groups it by default.
The Other Half: "Ask the Data"
The most exciting part is the chat. At the bottom of the dashboard, there's a text box where you can simply type in a question:
"How has organic traffic from Switzerland changed compared to the previous month?"
Behind the scenes, the system does what an analyst would normally do: A language model recognizes the structure of the GA4 tables, writes an SQL query, runs it against BigQuery, and responds with text, a table, or a chart—right within the chat interface. The user can now have a normal conversation based on their tracking data.
So we literally “talk” to Google Analytics 4 instead of clicking our way through it. This reduces configuration and administrative overhead and significantly improves the quality of the reports. By default, API calls to GA4 are too slow for extensive analyses over longer periods of time. With Gridonic Analytics, these limitations are eliminated as well.