Få djupare insikter snabbare med Stripe Sigma

Fördelarna med Stripe Sigma

Få insikter från dina Stripe-data med hjälp av SQL och AI

Stripe Sigma gör det möjligt för företag att enkelt utforska och analysera sina Stripe-data för snabbare affärsinsikter i Stripe Dashboard.

Fatta datadrivna beslut

Få insikter, håll koll på trender och analysera mönster i dina data ner på transaktionsnivå. Använd SQL eller anvisningar på naturligt språk för att direkt få svar på dina affärsfrågor.

Skapa helt anpassade rapporter

Övervaka ditt företag genom att skapa anpassad statistik och rapporter som passar dina behov. Skriv SQL från början, utgå från en färdig mall eller ändra befintliga rapporter med hjälp av vår AI-baserade assistent. Sedan blir det enkelt att visualisera dina data genom att omvandla rapporter till dynamiska diagram.

Få svar med hjälp av AI

Använd vår AI-drivna assistent för att enkelt få svar på frågor om företag. Ställ en fråga på vanlig engelska och få direkt den sökning du behöver för en anpassad rapport - ingen kodning krävs.

Samarbeta enkelt

Håll dina team synkroniserade genom att dela frågor, publicera anpassade rapporter till Stripe Dashboard och schemalägga rapporter som levereras direkt till deras inkorgar.

Användningsfall

Så använder team Stripe Sigma

Alla – från grundare till ekonomiteam – kan på ett enkelt sätt hämta insikter från sina Stripe-data, utan att det krävs särskilda SQL-kunskaper. Beskriv vad du vill veta så kommer den AI-styrda Stripe Sigma Assistant att omvandla det till en fråga och generera en rapport.

Hur stor procentandel av alla tvister bestred vi?

Hur många betalningar fick vi i februari?

Vilka kunder har inte betalat sina fakturor?

Vilka debiteringar kan avstämmas mot vår senaste bankutbetalning?

Hur mycket förändras kassaflödet från månad till månad?

Vad är företagets dagliga resultat?

Hur många aktiva kunder har vi?

Varför bestrider kunder betalningar?

Vilka är våra populäraste abonnemang?

Hur många betalningar görs med varje utfärdares bankkort?

Hur mycket intäkter får vi från olika kundkanaler?

Affärsteam använder Stripe Sigma för att effektivisera företaget

Ekonomiteam använder Stripe Sigma för att göra bokslut snabbare.

Datateam använder Stripe Sigma för att analysera allt från genomsnittlig intäkt per användare till kundbortfall.

Produkthanteringsteam använder Stripe Sigma för att identifiera nya affärsmöjligheter.

Operativ verksamhet

Hur stor procentandel av alla tvister bestred vi?

--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
~

Operativ verksamhet

Hur många betalningar fick vi i 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
~

Operativ verksamhet

Vilka kunder har inte betalat sina fakturor?

-- 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
~

Ekonomi

Vilka debiteringar kan avstämmas mot vår senaste bankutbetalning?

-- 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
~

Ekonomi

Hur mycket förändras kassaflödet från månad till månad?

-- 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
~

Ekonomi

Vad är företagets dagliga resultat?

-- 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
~

Dataanalys

Hur många aktiva kunder har vi?

-- 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
~

Dataanalys

Varför bestrider kunder betalningar?

-- 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
~

Produkthantering

Vilka är våra populäraste abonnemang?

-- 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
~

Produkthantering

Hur många betalningar görs med varje utfärdares bankkort?

-- 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
~

Produkthantering

Hur mycket intäkter får vi från olika kundkanaler?

-- 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
~

Omvandla dina data till användbara affärsinsikter

Läs mer om hur du använder Stripes dataverktyg för att visa intäktsmöjligheter och optimera din verksamhet. I den här guiden förklaras de nyckeltal som du kan följa upp för att kunna fatta bättre affärsbeslut.

Färdiga mallar

Optimerad för snabba svar

Vi har redan skrivit frågorna för de mest användbara rapporterna för olika typer av företag. Från att beräkna genomsnittlig intäkt per användare till att analysera vilken betalningsmetod som dina kunder föredrar – du kommer snabbt igång genom att anpassa en av våra rapportmallar eller så kan du skapa dina egna, helt nya rapporter. Vår inbyggda AI-baserade assistent är också redo att hjälpa dig bygga anpassade SQL-förfrågningar.

~
NORMAL
100%
0/1
ln
:
1

Lättanvänt schema

Dina data i Stripe – alltid redo

I sidofältet får du snabbt åtkomst till en fullständig karta över datastrukturen i Stripe (inklusive eventuella ytterligare metadata som du skickar till oss). Här kan du enkelt kombinera alla relevanta data som du behöver från de olika produkterna i Stripe: betalningar, utbetalningar, kunder, abonnemang, återbetalningar och mer.

Betalningstabeller
balance_transactions_fee_details
balance_transactions
id Varchar
belopp Bigint
available_on Tidsstämpel
skapad Tidsstämpel
valuta Varchar
beskrivning Varchar
avgift Bigint
netto Bigint
status Varchar
typ Varchar
source_id Varchar
automatic_transfer_id Varchar

Skapad för samarbete

Spara och dela frågor med ditt team

Spara vanliga frågor så att du kan kolla upp dem igen eller dela länken till en användbar fråga så att dina teammedlemmar också kan ta del av den.

Hur många kunder har vi i Frankrike?

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

Hur många betalningar fick vi förra månaden?

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
~

Kan du påminna mig om hur vi beräknar månatliga återkommande intäkter?

with calendar_days as ( select day cast(captured_amount/customer_count as dec from monthly_summary order by 1 desc, 2
~

Har du ett datalager? Uppgradera till Stripe Data Pipeline där Stripe Sigma ingår.

Om du använder ett datalager eller molnlagring kan du använda Data Pipeline för att synkronisera dina Stripe-data och rapporter till din lagringsdestination, med kostnadsfri tillgång till Stripe Sigma. Nya användare får en kostnadsfri 30-dagars provperiod.

Effektiviserad kontohantering och snabbare dataanalys för ditt företag

Med Stripe Organizations kan du i Dashboard hantera alla affärsområden eller dotterbolag för flera Stripe-konton. Genom att använda Sigma för att analysera data från alla dina konton kan du dessutom få tillgång till nya affärsinsikter.

sigma.latin-se

Är du redo att sätta i gång?

Analysera och skapa anpassade rapporter med dina Stripe-data.

Lär dig hur det funkar

Information om hur man bygger anpassade Stripe-rapporter.

Anslut Stripe till ditt datalager

Effektivisera ditt analysarbete och få tillgång till ytterligare insikter genom att centralisera dina Stripe-data i din datalagringsdestination.

Morty Proxy This is a proxified and sanitized view of the page, visit original site.