Krijg sneller diepere inzichten met Stripe Sigma

Waarom Stripe Sigma?

Inzichten uit je Stripe-gegevens halen met SQL en AI

Stripe Sigma stelt ondernemingen in staat om eenvoudig hun Stripe-gegevens in te zien en te analyseren voor snellere zakelijke inzichten, op het Stripe-Dashboard.

Datagestuurde beslissingen nemen

Doe inzichten op, houd trends bij en analyseer patronen in je gegevens tot op transactieniveau. Gebruik SQL-query's of opdrachten in gewone taal om direct antwoord te krijgen op je vragen over je onderneming.

Maak volledig aangepaste rapporten

Monitor de prestaties van je onderneming met op maat gemaakte statistieken en rapportages die zijn afgestemd op je behoeften. Schrijf zelf nieuwe SQL-query's, gebruik een kant-en-klaar sjabloon of pas bestaande rapporten aan met behulp van de ingebouwde assistent met AI-functionaliteit. Je kunt vervolgens eenvoudig je gegevens visualiseren door je rapporten om te zetten in dynamische grafieken.

Krijg antwoorden met AI

Gebruik onze AI-gestuurde assistent om eenvoudig antwoorden te krijgen op eenvoudige zakelijke kwesties. Stel een vraag in gewoon Engels en krijg direct de query die je nodig hebt voor een aangepast rapport; geen programmeerwerk vereist.

Eenvoudig samenwerken

Houd je teams op één lijn door query's te delen, aangepaste rapporten te publiceren naar het Stripe-dashboard en rapporten te plannen die rechtstreeks in hun inbox worden afgeleverd.

Toepassingen per afdeling

Zo wordt Stripe Sigma gebruikt

Van oprichters tot financiële teams, iedereen kan eenvoudig inzichten uit hun Stripe-gegevens halen – SQL-kennis is niet vereist. Voer je vraag in en de AI-aangedreven Stripe Sigma Assistant zet deze om in een query en een bijbehorend rapport.

Tegen welk percentage chargebacks hebben we bezwaar gemaakt?

Hoeveel betalingen hadden we in februari?

Welke klanten hebben hun factuur nog niet betaald?

Welke betalingen zijn gereconcilieerd met onze laatste bankgegevens?

Hoe verandert onze cashflow van maand tot maand?

Wat is ons dagsaldo?

Hoeveel actieve klanten hebben we?

Waarom vragen klanten chargebacks aan?

Wat zijn onze meest populaire abonnementen?

Hoeveel betalingen worden er gedaan per type creditcard?

Hoeveel inkomsten genereren de verschillende klantkanalen?

Managers gebruiken Stripe Sigma om hun bedrijf efficiënter te runnen.

Financiële teams gebruiken Stripe Sigma om het boekjaar sneller af te sluiten.

Data-analisten gebruiken Stripe Sigma voor allerlei doelen, van de gemiddelde inkomsten per gebruiker tot het klantverloop.

Productbeheer gebruikt Stripe Sigma om nieuwe verkoopmogelijkheden te ontdekken.

Bedrijfsvoering

Tegen welk percentage chargebacks hebben we bezwaar gemaakt?

--This template returns an itemized list of disputed charges for the past 30 days, --along with information such as whether evidence has been submitted and the status of the dispute -- Note: if you have currencies that do not have cents (e.g. JPY), you should not divide by 100.0 select charges.id as charge_id, date_format(disputes.created, '%Y-%m-%d') as dispute_date, date_format(charges.created, '%Y-%m-%d') as charge_date, charges.card_brand, disputes.reason, disputes.status, disputes.amount / 100.00 as dispute_amount, disputes.currency, disputes.evidence_details_has_evidence as evidence_saved, case when disputes.evidence_details_submission_count = 0 then false else true end as evidence_submitted from disputes join charges on charges.id = disputes.charge_id where date(charges.created) >= date_add('day', -30, current_date) order by 2 desc
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Bedrijfsvoering

Hoeveel betalingen hadden we in februari?

-- This template returns a monthly summary of your activities, including all payments in the UTC time zone -- Note: this query may need to be modified to handle additional payout/transfer types if you are using Connect -- monthly_balance_transactions is a temporary table that aggregates and pivots different -- balance_transaction types on a monthly basis for each currency -- Note: only months with at least 1 balance transaction will be returned with monthly_balance_transactions as ( select date_trunc('month', case when type = 'payout' then available_on else created end) as month, -- payouts are considered when they are posted (available_on) currency, sum(case when type in ('charge', 'payment') then amount else 0 end) as sales, sum(case when type in ('payment_refund', 'refund') then amount else 0 end) as refunds, sum(case when type = 'adjustment' then amount else 0 end) as adjustments, sum(case when type not in ('charge', 'payment', 'payment_refund', 'refund', 'adjustment', 'payout') and type not like '%transfer%' then amount else 0 end) as other, sum(case when type <> 'payout' and type not like '%transfer%' then amount else 0 end) as gross_transactions, sum(case when type <> 'payout' and type not like '%transfer%' then net else 0 end) as net_transactions, sum(case when type = 'payout' or type like '%transfer%' then fee * -1.0 else 0 end) as payout_fees, sum(case when type = 'payout' or type like '%transfer%' then amount else 0 end) as gross_payouts, sum(case when type = 'payout' or type like '%transfer%' then fee * -1.0 else net end) as monthly_net_activity, count_if(type in ('payment', 'charge')) as sales_count, count_if(type = 'payout') as payouts_count, count(distinct case when type = 'adjustment' then source_id end) as adjustments_count from balance_transactions group by 1, 2 ) -- Compute the month_end_balance for each month and format output -- Note: if you have currencies that do not have cents (e.g. JPY), you should not divide by 100.0 select date_format(month, '%Y-%m') as month, currency, sales / 100.0 as sales, refunds / 100.0 as refunds, adjustments/100.0 as adjustments, other / 100.0 as other, gross_transactions / 100.0 as gross_transactions, net_transactions / 100.0 as net_transactions, payout_fees / 100.0 as payout_fees, gross_payouts / 100.0 as gross_payouts, monthly_net_activity/100.0 as monthly_net_activity, sum(monthly_net_activity + gross_payouts) over(partition by currency order by month)/100.0 as month_end_balance, -- use SUM Window Function sales_count, payouts_count, adjustments_count from monthly_balance_transactions where month < date_trunc('month', current_date) -- exclude current, partial month order by 1 desc, 2
~

Bedrijfsvoering

Welke klanten hebben hun factuur nog niet betaald?

-- This template returns all unpaid invoices and relevant customer and plan information -- Note: if you have currencies that do not have cents (e.g. JPY), you should not divide by 100.0 select date(invoices.date) as invoice_date, invoices.amount_due / 100.0 as amount_due, invoices.attempt_count, invoices.customer_id, customers.email, plans.name as plan_name from invoices join subscriptions on invoices.subscription_id = subscriptions.id join plans -- join subscriptions on plans to get plan name on subscriptions.plan_id = plans.id join customers -- join on customers to get customer email on invoices.customer_id = customers.id where not invoices.paid -- filter out paid and forgiven invoices and invoices.status != 'uncollectible' order by 2 desc, 1
~

Financiën

Welke betalingen zijn gereconcilieerd met onze laatste bankgegevens?

-- This template returns itemized information for transfers/payouts linked to -- automatic transfers within the past 30 days select date(transfers.date) as transfer_date, transfers.id as transfers_id, transfers.amount/100.0 as transfer_amount, transfers.status as transfers_status, balance_transactions.id as balance_transaction_id, balance_transactions.source_id as balance_transaction_source_id, balance_transactions.type as balance_transaction_type, balance_transactions.currency, balance_transactions.amount/100.0 as balance_transaction_amount, balance_transactions.net/100.0 as balance_transaction_net, charges.statement_descriptor as statement_descriptor, disputes.reason as disputes_reason, refunds.reason as refund_reason from transfers join balance_transactions on balance_transactions.automatic_transfer_id = transfers.id left join charges on charges.id = balance_transactions.source_id -- balance_transactions.source_id can be used to join on charges, disputes, and refunds table. left join disputes on disputes.id = balance_transactions.source_id left join refunds on refunds.id = balance_transactions.source_id where transfers.type = 'bank_account' and transfers.date >= date_add('day', -30, current_date) order by transfers.date desc, transfers.id, balance_transactions.created desc
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Financiën

Hoe verandert onze cashflow van maand tot maand?

-- This template returns gross processing volume for each currency per month, assuming a local timezone of PT -- Note: charges can change over time, for example if a charge gets refunded. -- Always use the balance transactions table if you need to create reports for accounting purposes -- charges_timezone_conversion is a temporary table that converts timestamp with UTC timezone to 'America/Los_Angeles' timezone with charges_timezone_conversion as ( select date_trunc('month', created at time zone 'America/Los_Angeles') as month, currency, amount from charges where captured -- filter out uncaptured charges ) -- Compute the monthly gross charges for each month and currency select date_format(month, '%Y-%m') as month, currency, sum(amount)/100.0 as gross_charges from charges_timezone_conversion where month >= date_add('month', -24, date_trunc('month', current_timestamp at time zone 'America/Los_Angeles')) group by 1, 2 order by 1 desc, 2
~

Financiën

Wat is ons dagsaldo?

-- This template returns the balance at the end of every day in the UTC time zone -- daily_balance_transactions is a temporary table that aggregates and pivots different -- balance_transaction types on a daily basis for each currency with daily_balance_transactions as ( select -- payouts are considered when they are posted (available_on) date(case when type = 'payout' then available_on else created end) as day, currency, sum(net) as daily_balance, sum(case when type = 'payout' then net else 0 end) as payouts, sum(case when type <> 'payout' then net else 0 end) as net_transactions, sum(case when type in ('charge', 'payment') then net else 0 end) as payments, -- net = amount - fee sum(case when type in ('payment_refund', 'refund', 'payment_failure_refund') then net else 0 end) as refunds, sum(case when type = 'transfer' then net else 0 end) as transfers, sum(case when type = 'adjustment' and lower(description) like 'chargeback withdrawal%' then net else 0 end) as chargeback_withdrawals, sum(case when type = 'adjustment' and lower(description) like 'chargeback reversal%' then net else 0 end) as chargeback_reversals, sum(case when type = 'adjustment' and lower(description) not like 'chargeback withdrawal%' and lower(description) not like 'chargeback reversal%' then net else 0 end) as other_adjustments, sum(case when type not in ('payout', 'transfer', 'charge', 'payment', 'refund', 'payment_refund', 'adjustment') then net else 0 end) as other_transactions from balance_transactions group by 1, 2 ) -- Compute the current_balance for each day and format output select day, currency, -- use SUM Window Function to calc. running total sum(daily_balance) over(partition by currency order by day)/100.0 as current_balance, payouts/100.0 as payouts, net_transactions/100.0 as net_transactions, payments/100.0 as payments, refunds/100.0 as refunds, transfers/100.0 as transfers, chargeback_withdrawals/100.0 as chargeback_withdrawals, chargeback_reversals/100.0 as chargeback_reversals, other_adjustments/100.0 as other_adjustments, other_transactions/100.0 as other_transactions from daily_balance_transactions order by 1 desc, 2
~

Data-analyse

Hoeveel actieve klanten hebben we?

-- This template returns itemized subscription information for each customer and plan select subscriptions.customer_id as customer_id, customers.email as customers_email, subscriptions.plan_id as plan_id, plans.nickname as plan_name, subscriptions.quantity as quantity, case when subscriptions.canceled_at is null and subscriptions.ended_at is null then 'active' else 'inactive' end as state, date_format(subscriptions.created, '%Y-%m-%d') as created_date, date_format(subscriptions.start, '%Y-%m-%d') as start_date, date_format(least(subscriptions.canceled_at, subscriptions.ended_at), '%Y-%m-%d') as end_date from subscriptions join plans -- join subscriptions on plans to get plan name on subscriptions.plan_id = plans.id left join customers on subscriptions.customer_id = customers.id order by 2
~

Data-analyse

Waarom vragen klanten chargebacks aan?

-- This template returns the number of disputes grouped by reason and dispute status select reason, -- reason given by cardholder for dispute status, -- current status of dispute count(id) as disputes, count_if(evidence_details_submission_count > 0) as disputes_with_evidence_submitted from disputes group by 1, 2 order by 3 desc
~

Productbeheer

Wat zijn onze meest populaire abonnementen?

-- This template returns itemized subscription information for each customer and plan select subscriptions.customer_id as customer_id, customers.email as customers_email, subscriptions.plan_id as plan_id, plans.nickname as plan_name, subscriptions.quantity as quantity, case when subscriptions.canceled_at is null and subscriptions.ended_at is null then 'active' else 'inactive' end as state, date_format(subscriptions.created, '%Y-%m-%d') as created_date, date_format(subscriptions.start, '%Y-%m-%d') as start_date, date_format(least(subscriptions.canceled_at, subscriptions.ended_at), '%Y-%m-%d') as end_date from subscriptions join plans -- join subscriptions on plans to get plan name on subscriptions.plan_id = plans.id left join customers on subscriptions.customer_id = customers.id order by 2
~

Productbeheer

Hoeveel betalingen worden er gedaan per type creditcard?

-- This template returns the number of charges and amounts for each card type, by currency select coalesce(card_brand, 'Non-card or Other') as card_brand, currency, count(id) as charge_count, sum(amount)/100.0 as total_amount from charges where captured group by 1, 2 order by 4 desc
~

Productbeheer

Hoeveel inkomsten genereren de verschillende klantkanalen?

-- This template returns itemized information for charges and associated customer metadata (from charges_metadata) -- charges_metadata_dictionary is a temporary table that creates a row for every charge_id with a dictionary of associated metadata with charges_metadata_dictionary as ( select charge_id, map_agg(key, value) metadata_dictionary -- MAP_AGG creates a key:value dictionary from charges_metadata group by 1) select charges.created, charges.id, charges.customer_id, charges.amount/100.0 as amount, metadata_dictionary['customer_source'] as customer_source -- 'customer_source' is the key we are accessing and returning the associated value (provided via metadata) from charges left join charges_metadata_dictionary on charges.id = charges_metadata_dictionary.charge_id where date_trunc('year', charges.created) = date_trunc('year', current_date) and charges.captured order by charges.created desc limit 1000
~

Je gegevens omzetten in praktische zakelijke inzichten

Ontdek hoe je de gegevenstools van Stripe kunt gebruiken om omzetkansen te ontdekken en je bedrijfsvoering te verbeteren. In deze whitepaper bespreken we de belangrijke statistieken die je kunt bijhouden om betere zakelijke beslissingen te nemen.

Kant-en-klare sjablonen

Geoptimaliseerd voor snelle antwoorden

We hebben al query's geschreven voor uiterst nuttige rapporten voor verschillende typen ondernemingen: van het berekenen van de gemiddelde inkomsten per gebruiker tot het analyseren van de favoriete betaalmethoden van je klanten. Je kunt dus meteen aan de slag door een van onze kant-en-klare sjablonen te bewerken, maar je kunt ook helemaal opnieuw beginnen en een rapport volledig aan je wensen aanpassen. Onze geïntegreerde assistent met AI-functionaliteit kan je ook helpen met het maken van SQL-query's op maat.

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Gebruiksvriendelijk overzicht

Data van Stripe klaar voor gebruik

Snelle toegang via de zijbalk tot de volledige structuur van je opgeslagen data in Stripe (plus eventuele aanvullende metadata die je ons stuurt), maakt het eenvoudig om alle relevante gegevens uit de producten van Stripe te combineren: betalingen, uitbetalingen, klanten, abonnementen, terugbetalingen, enzovoort.

Betaaltabellen
balance_transactions_fee_details
balance_transactions
id Varchar
amount Bigint
available_on Timestamp
created Timestamp
currency Varchar
description Varchar
fee Bigint
net Bigint
status Varchar
type Varchar
source_id Varchar
automatic_transfer_id Varchar

Bekijk het volledige schema

Samenwerken

Query's opslaan en delen met je team

Sla veelgebruikte query's op, zodat je ze eenvoudig opnieuw kunt gebruiken. Deel links naar query's met je collega's zodat zij er ook plezier van hebben.

Hoeveel klanten hebben we in Frankrijk?

select id, email, shipping_address_country from customers where shipping_address_country = 'FR'
~

Hoeveel betalingen hadden we vorige maand?

with monthly_balance_transactions as ( select date_trunc('month', case when type = 'pa' from monthly_balance_transactions where month = date_trunc('month', date '2017') order by 1 desc, 2
~

Hoe berekenen we maandelijks terugkerende inkomsten ook alweer?

with calendar_days as ( select day cast(captured_amount/customer_count as dec from monthly_summary order by 1 desc, 2
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Heb je een datawarehouse? Upgrade dan naar Stripe Data Pipeline, inclusief Stripe Sigma.

Als je gebruikmaakt van een datawarehouse of cloudopslag, kun je Data Pipeline gebruiken om je Stripe-gegevens en -rapporten te synchroniseren met je opslaglocatie, inclusief gratis toegang tot Stripe Sigma. Nieuwe gebruikers ontvangen een gratis proefperiode van 30 dagen.

Gestroomlijnd accountbeheer en snellere gegevensanalyse voor je onderneming

Met Stripe Organizations kun je alle bedrijfsonderdelen of dochterondernemingen in meerdere Stripe-accounts centraal beheren in het dashboard en nieuwe zakelijke inzichten verkrijgen door Stripe Sigma te gebruiken om gegevens in al je accounts te analyseren.

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Klaar om aan de slag te gaan?

Maak analyses en rapporten op maat met je Stripe-gegevens.

Zo werkt het

Uitvoerige uitleg over het maken van Stripe-rapporten op maat.

Stripe koppelen aan je datawarehouse

Stroomlijn je analyses en krijg toegang tot extra inzichten door je Stripe-gegevens op één plek te bewaren op je locatie voor gegevensopslag.

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