Data Panda brings your GA4 event data together with the data from the rest of your business. From one place, we turn it into dashboards, automations, AI workflows and custom apps your team uses every day.
Google Analytics 4 replaced Universal Analytics in 2023 with an event-based data model. Every interaction on a website or app is recorded as an event with parameters, grouped into sessions and tied to user and device identifiers where consented. GA4 also ships a free BigQuery export that reveals the full, unsampled event stream behind its UI.
The point of pulling GA4 into a warehouse is that the GA4 interface samples, thresholds and aggregates to stay fast, and the numbers that land in a marketing deck are not always the numbers the finance team sees. Next to Google Ads, Facebook Ads, Shopify orders and CRM deals, the GA4 event stream becomes the attribution layer that ties a first touch to a paid invoice, instead of three reports that disagree on the total.
Unsampled behaviour data next to revenue, per channel, campaign and product.
Let GA4 signals fire actions in the rest of the stack, not just in GA4.
Use the full event stream to score intent and model cohorts.
Internal tools on GA4 event data that the GA4 interface cannot show.
A list of concrete reports, automations and AI features we have built on Google Analytics GA4 data. Pick the one that matches your situation.
Which channels produce customers, not just sessions?
First-touch channel linked to paid invoices twelve months out, next to GA4's own conversion number. Separates the channel that produces clicks that pay from the channel that produces clicks that only look good in the report.
How much of our revenue shows up differently in GA4 than in the ledger?
Reconciliation between GA4 conversion events and paid orders in Shopify or invoices in the accounting system, per time window. Surfaces the consistent gap between the GA4 number and the cleared number, so marketing and finance stop arguing in the Monday meeting.
Where is our paid traffic cannibalising organic?
Paid and organic sessions on the same audience and query, with attributed revenue on each. Identifies the audiences where the paid click was already going to convert organically, so pausing the paid bid would not cost revenue.
Marketing attribution tied to invoiced revenue, with GA4-to-ledger reconciliation built in. Marketing-budget conversations move from GA4 conversion counts to the cleared revenue per channel.
First-touch channel and high-intent event signals on the CRM contact before the first sales call. Reps know where a lead came from and what they looked at, instead of asking the marketing team.
Full-event detail, unsampled, with cross-device and cross-property stitching where consented. Reporting accuracy and privacy posture become a single technical design, not an annual fire drill.
GA4 session and event data lands next to the Google Ads click and cost that produced it. ROAS stops being a number Google reports against its own pixel and starts reflecting the paid orders those sessions produced, with LTV twelve months out available to Smart Bidding.
GA4 events for the pages a HubSpot contact viewed and the assets they downloaded push onto the contact timeline. Sales sees the intent trail before the first call and marketing scores leads on behaviour, not on form fills alone.
GA4 event detail joins to the Shopify order the session produced, including product view, add-to-cart and checkout drop-off. Merchandising and marketing see which product journeys end in paid revenue and which ones drop at the cart.
Facebook Ads click data and GA4 session data land in the same warehouse to produce a multi-touch picture across Meta, Google and organic. Spend decisions move from per-channel ROAS on each vendor's dashboard to a blended cost per paying customer.
You keep the reporting tool you already have. We connect it to the warehouse where your Google Analytics GA4 data lives.
OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.
Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.
We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.
We set up the foundation. Your team builds on top.
Best fit Teams that already have a BI analyst or data engineer and want to own the build.
We build the whole thing, end to end.
Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.
You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.
Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.
No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.
BigQuery export is the primary path and lands the full, unsampled event stream in the warehouse. The Data API is used where BigQuery export is not enabled or for specific aggregated metrics, and reconciliation between the two lives in the warehouse itself.
Consent signals carried on each GA4 event land in the warehouse as first-class fields. Reporting respects the consent state so unconsented users are aggregated or excluded per your policy, and PII is never derived from the event stream without an explicit rule.
We review your Google Analytics GA4 setup and the systems around it. Together we pick the first thing worth building.