Data Panda brings your Stripe 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.
Stripe started in 2010 as an API that made it trivial for a developer to accept a card payment. It has since grown into a broad financial platform covering one-off payments, subscriptions and invoicing through Stripe Billing, marketplace flows through Connect, fraud prevention through Radar and in-person payments through Terminal. Large parts of the software economy route money through it, from SaaS startups to Fortune 100 commerce.
The point of pulling Stripe into a warehouse is that Stripe's own dashboard answers the question of the day, not the question of the quarter. Churn cohorts, subscription health, payment-method mix by country, dunning recovery rates and refund patterns are all in the data Stripe sends you. Next to your CRM, your webshop and your accounting package, those signals turn into a single revenue picture that survives month-end.
MRR, churn, refunds and dunning recovery on one timeline instead of three Stripe reports.
Let the rest of the stack react to what Stripe knows first.
Use Stripe history to predict the next churn and the next dunning failure.
Internal tools around the payment data that is otherwise stuck in one dashboard.
A list of concrete reports, automations and AI features we have built on Stripe data. Pick the one that matches your situation.
Which customer cohort is still growing revenue, not just retaining it?
Net revenue retention by cohort, broken into expansion, contraction and churn. Shows the acquisition month whose MRR per customer is still climbing a year later, versus the cohort where retention is hiding a quiet decline.
How much recoverable revenue are we losing to dunning?
Failed-payment volume that reached the end of its retry sequence without recovery, ranked by failure reason. Separates the card-expired segment where a prompt would fix it from the insufficient-funds segment where it would not.
Which plan changes predict a customer about to leave?
Downgrade and pause patterns in the last three months, next to support volume and product usage. Surfaces the accounts that are signalling exit before the renewal date, so customer success can intervene with context.
MRR, NRR and dunning recovery tied to the invoice and the payout that the bank cleared. No more reconciling Stripe's dashboard, the accounting package and the bank statement by hand on the fifth of the month.
Closed-won deals ranked by the first successful Stripe charge they produced, not by the optimism on the CRM record. The accounts that signed but never paid show up early, next to the ones that expanded twice in six months.
Payment-method mix by country, dispute win rate by card network, and refund patterns per SKU. The operational choices about which gateway, which currency and which product mix to push stop being based on vendor-side averages.
Every Shopify order is matched to the Stripe charge that funded it, and every Stripe payout is traced back to the orders it paid out for. Refunds and chargebacks flow back to the original order so the margin number stays honest.
Stripe payouts land in Exact Online as bank journal entries, with Stripe fees split out and the underlying charges matched to the invoices they paid. Month-end reconciliation between Stripe, the bank and the ledger stops being a multi-tab spreadsheet.
Successful Stripe payments, failed charges and refund events push into HubSpot as contact timeline activity and deal property updates. Customer success sees a failed renewal the same hour Stripe does, not at the weekly report.
Payments taken through Stripe are matched back to the Teamleader Focus invoice they settle, including partial payments and refunds. The open-invoice list in Focus reflects what Stripe has already cleared, instead of waiting for the bank reconciliation.
These are the 17 tables we currently pull from Stripe 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 Stripe 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.
Yes. Each Stripe account lands in its own schema in the warehouse with a shared customer dimension on top. For Connect platforms, we split the platform's own revenue from the connected accounts' volume, so group reporting and per-seller reporting both stay possible.
Webhooks first for events that drive automations, with a nightly API sweep as a reconciliation pass so nothing drops on the floor when a webhook retry is late. Both paths land in the same warehouse tables, deduplicated on event id.
We review your Stripe setup and the systems around it. Together we pick the first thing worth building.