a use case of your own analyst

Payment analytics from Stripe without manual exports

Q: Can it change anything in Stripe?

No. Stripe access is read-only: your own analyst creates no refunds, changes no subscriptions and touches no settings. All it does is read payments, refunds and customer data and build the table and the summary from them. Any action in Stripe is taken by a person on your team.

Q: How often does the close arrive?

By default on the first of the month, and on request in the chat at any time for any period. We agree the frequency and the table layout at onboarding, together with the list of countries and plans. If you need a weekly payments digest, your own analyst sends it on the same schedule as the other reports.

Every month it pulls all Stripe payments, classifies them and hands over a ready table for the accountant plus a short summary in the chat.

Build your AI agent Everything your own analyst does

Payment analytics from Stripe is a use case of your own analyst from sviy.ai for subscription products: a monthly close of payments, refunds and failed payments, every transaction classified by plan, country and customer type, and a ready export to Google Sheets or Excel. Stripe data is read-only; a person checks the numbers before they go to the accountant.

Stripe, read-only
monthly on a schedule
export to Sheets or Excel

Your own analyst · Slack

The September close is ready. Revenue $48,920, refunds $1,140, 23 failed payments worth $1,980.

Full table: 1,412 transactions, each with plan, country and customer type. The total matches the Stripe balance.

What hurts

Every month I export Stripe into a spreadsheet and count revenue by country and plan by hand.

The formulas in the close spreadsheet drift, and every month the numbers come out slightly different.

Refunds and failed payments surface after the report has already gone to the accountant.

What your own analyst does

Reads Stripe

On the first of the month it pulls all payments, refunds, failures and customer data for the month via the read-only API.

Classifies transactions

Sorts each one by plan, country, customer type (B2B or B2C) and status — by the rules agreed at onboarding.

Builds the close

Calculates revenue, MRR, refunds and failed payments, reconciles the total with the Stripe balance and flags discrepancies.

Hands over the result

A short summary with a chart in Slack or Telegram and the full table with a row per transaction in Google Sheets or Excel.

Sources and channels

Stripe
Google Sheets
Excel
Slack or Telegram

Before → after

Before: Half a day on the monthly Stripe export

After: The close table ready on the 1st by 09:00

Before: Formulas and classification differ every month

After: One set of classification rules for every transaction

Before: Refunds surface after the report

After: Refunds and failed payments in the same summary, with causes

What it looks like in the chat

08:00The September close is ready. Revenue $48,920, refunds $1,140, 23 failed payments worth $1,980.

Revenue by country, $K · September

Stripe_close_September.xlsxFull table: 1,412 transactions, each with plan, country and customer type. The total matches the Stripe balance.

Why are there more failed payments than in August?

August had 9. Of the 23 in September, 17 are cards from one bank in Poland, declined on 12–14 September. Looks like an outage on the bank's side; 11 customers have already paid again. Added a note to the table.

Questions

Does this replace the accountant?

No. Your own analyst prepares the classified table and the summary; journal entries, taxes and filings stay with the accountant. It saves the time spent on exports and classification and cuts manual errors, but it makes no accounting decisions. Your accountant agrees the classification rules at onboarding.

Can it change anything in Stripe?

How often does the close arrive?

Updated: October 8, 2026

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