Prepare data before every question.
- Export files from the marketing platform
- Reformat and reconcile columns
- Rebuild the analysis for each follow-up
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Configure the Catchr remote MCP connection in ChatGPT using the connector details from Catchr.
Replace account, period, KPI target, and threshold variables before you ask ChatGPT.

“Why did CPA rise?” sounds simple. The answer is usually buried across exports, formulas, filters, and tabs before the analysis can even start.

Choose the right account, date range, breakdowns, and fields. Then wait for the file and do it again when the question changes.

Rename columns, fix formats, join tabs, and check formulas before you can trust the comparison.

Turn the numbers into a client-ready answer, then repeat the whole process for the inevitable follow-up.
Catchr MCP gives ChatGPT access to the marketing accounts you select, so each follow-up starts with the same marketing context instead of a new manual export.
Choose your role, open a workflow, then replace the bracketed variables before pasting the prompt into ChatGPT. Every prompt asks for evidence, limits, and a concrete output.
Using the Catchr MCP, pull Stripe data for [List of Client Accounts] over [Current Period] and compare each account with [Previous Comparable Period]. For every account, use Account name, Charge Created On, Charge Status, Charge Amount, Charge Amount Captured, Charge Amount Refunded, Charge Currency, Charge Failure Code, Charge Is Disputed, Balance Transaction Fee, and Balance Transaction Net to summarize payment volume, success and failure rates, captured revenue, refunds, disputes, fees, and net proceeds. Keep currencies separate unless [Currency Conversion Rules] are supplied, normalize monetary values from their smallest currency unit, and do not add charge and balance-transaction amounts together as revenue. Label each account Healthy, Watch, or Critical using [Client-Specific Thresholds], rank the clients requiring attention, and give the evidence, likely operational issue, and one next action for every flagged account.
ChatGPT can query connected Stripe data for payments, invoices, customers, subscriptions, refunds, disputes, fees, and balance reporting.
Representative fields include Balance Transaction Amount, Charge Amount Refunded by Charge Currency, Subscription ID, Subscription Status, and Subscription Start Date. Useful breakdowns include Date, Account name, Customer Country, Invoice Created At, and Invoice Collection Method. The exact field set depends on the selected dataset and compatible reporting reporting level.
The available detail depends on the fields returned for the selected dataset. Useful breakdowns include Date, Account name, Customer Country, Invoice Created At, and Invoice Collection Method.
Ask ChatGPT to state the reporting level it used and keep incompatible levels separate before calculating totals, rates, or comparisons.
Yes. ChatGPT can compare transaction, invoice, subscription, and customer revenue signals across periods. Relevant fields include Balance Transaction Amount, Charge Amount Refunded by Charge Currency, Subscription ID, Subscription Status, and Subscription Start Date.
Set the business target, comparison period, and minimum volume before requesting priorities or recommendations.
Yes. ChatGPT can surface failed or delayed payments, refunds, disputes, fee pressure, or settlement inconsistencies. Useful breakdowns include Date, Account name, Customer Country, Invoice Created At, and Invoice Collection Method.
Ask it to separate observed data, possible explanations, and the next validation step so an unusual value is not presented as a proven cause.
Strong prompts name the action, account or entity, date range, comparison, and KPI or threshold.
Yes, when the other sources are also connected to Catchr. Useful combinations include commerce, CRM, advertising, analytics, or subscription sources.
Align dates, currencies, identifiers, and definitions first. If the sources cannot be joined reliably, ask for a side-by-side comparison rather than a single attributed result.
Yes, provided each one is connected and available through Catchr MCP. Ask for separate results first, then create the combined view.
Specify the account, currency, accounting definition, period, and materiality threshold. This keeps one large entity or a definition mismatch from distorting the comparison.
You need access that can authorize and view the relevant Stripe data, a Catchr workspace with the source connected, and Catchr MCP enabled in ChatGPT.
After selecting the required entities, you can ask questions in natural language without preparing a new CSV export for each analysis.
ChatGPT analyzes the records returned through the connected Catchr source; it should not assume the data is real time. Freshness and historical coverage can vary by dataset, field, selected period, and source API limits.
Ask it to state the latest payment, invoice, subscription, or extraction date, together with the timezone, requested period, and any missing intervals before interpreting a trend.
No. Catchr MCP provides Stripe data for analysis; it does not give ChatGPT permission to create invoices, move money, issue refunds, cancel subscriptions, or edit accounting records.
Use the result to prepare an action plan, then make operational changes in Stripe. Prefer aggregated outputs whenever names, contact details, or record-level information are not required.
Our team is always here to answer any questions you may have about our data connector.
Connect yout marketing platform to ChatGPT with Catchr MCP and start investigating current campaign performance.