Data Panda brings your PostHog 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.
PostHog was founded in 2020 by James Hawkins and Tim Glaser as a Y Combinator W20 batch company, built around an open-source core that customers can self-host or run on PostHog Cloud (US or EU residency). What started as a single product-analytics tool has grown into a bundled platform: Product Analytics, Session Replay, Feature Flags, Experiments, Surveys, Web Analytics, a Data Warehouse and an LLM observability product, all backed by the same event store and identity graph.
The reason to pull PostHog into a warehouse next to it is that the bundle works well one product at a time and gets brittle the moment a team wants to ask cross-product questions over a longer window. Funnel impact of a feature flag four months after the rollout, replay storage cost weighed against the insights replays unlocked over time, experiment significance once exposure overlap with other tests is corrected, self-hosted version lag against the latest schema on Cloud: those are the questions where the PostHog UI runs out of room. Next to Stripe revenue, HubSpot deals and support tickets, the same PostHog event log gets the cross-tool joins that decide the next quarter of the roadmap.
Analytics, replays, flags and experiments joined to revenue, plan and cohort.
Let PostHog signals drive the rest of the stack instead of staying in the PostHog UI.
Use the full event and replay-metadata stream to score behaviour and risk.
Internal tools on PostHog data for teams that do not live in the PostHog UI.
A list of concrete reports, automations and AI features we have built on PostHog data. Pick the one that matches your situation.
Did the feature flag move revenue, not just the funnel?
Flag exposure per account joined to Stripe revenue and renewal outcome, six and twelve weeks out. Separates the rollout that lifted PostHog's funnel chart from the rollout that lifted paid retention, which are not always the same flag.
Are our experiments significant once exposure overlap is corrected?
A/B test results recomputed across users that sat in multiple tests in the same window, with the variance contribution of each overlapping test reported. Catches the experiment that PostHog called significant when the lift came from another test running at the same time.
Are session replays paying for their storage cost?
Replay storage and review-hours per month against the funnel steps that replays changed, by team. Surfaces the modules where replay earns its cost in fixed friction and the modules where the team records a lot and watches almost nothing.
Feature-flag and experiment outcomes tied to paid revenue, cohort and renewal. Roadmap defence stops being told in PostHog funnel charts and starts being told in retained revenue per flag.
PostHog product events, flag membership and survey responses on every CRM contact and account. Reps see the customer who was in the new-billing variant for two months and is now answering five out of ten on NPS, before the renewal call.
Replay storage cost, experiment overlap and self-hosted version drift on one operations dashboard. The fragile event PostHog flags depend on stops being rediscovered the week it stops firing and shows up as a trend instead.
PostHog events, flag membership and aggregate usage per account push onto the HubSpot contact and deal record. Sales sees the trial that got the new pricing variant, the power user who hit activation last week and the dormant account on the same timeline as the deal stage.
Aggregate PostHog usage, feature-flag cohort and recent experiment exposure per account flow to Salesforce as fields and timeline events. Account executives walk into a QBR with the exact features the customer used, the variant they were in and the surveys they answered, not with marketing-reported averages.
Activation milestones, drop-off events, feature-flag exposure and survey responses push into Customer.io as metric events on the customer profile. Lifecycle messages fire on real product behaviour, and a journey can pause for users in a specific experiment variant so the test result is not contaminated by the messaging.
Low NPS responses, sudden usage drops on key accounts and failed experiment guardrail checks open targeted Slack threads in the right channel, with the customer record, recent events and the active feature-flag membership attached. The CS lead sees the at-risk account before the next standup, not at month-end.
These are the 15 tables we currently pull from PostHog into your warehouse. Query them directly in SQL, join them to the rest of your stack, or build reports on top.
Missing a table you need? We can extend the sync. Tell us what is missing and we will build it for you.
You keep the reporting tool you already have. We connect it to the warehouse where your PostHog 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.
Both are supported. PostHog Cloud (US and EU) is pulled via the standard API and event export. Self-hosted instances are pulled either through the same API or directly from the underlying ClickHouse store, depending on access. The warehouse schema is identical, so dashboards built on Cloud keep working when a project moves to self-hosted, or the other way around.
Yes. PostHog Cloud EU data is processed in EU regions and lands in a warehouse region you control. Routing, identifiers and pseudonymisation are configured so an EU-residency project can be joined with the rest of your stack without leaving the region.
We review your PostHog setup and the systems around it. Together we pick the first thing worth building.