Stripe Sigma が選ばれる理由

SQL と AI を利用して Stripe データからインサイトを引き出す

Stripe Sigma を利用すると、Stripe データを調べて分析し、業務に役立つインサイトをより迅速に引き出すことができます。操作は Stripe ダッシュボード内で行えます。

データに基づいた意思決定

インサイトを引き出し、傾向を追跡。取引レベルまでデータのパターンを分析します。SQL や自然言語のプロンプトを利用して、ビジネスに関する質問の答えを瞬時に得ることができます。

完全なカスタムレポートの作成

ニーズに合わせてカスタムの指標やレポートを作成して事業を監視しましょう。SQL を新規に作成することも、事前に作成されたテンプレートを利用することも、既存のレポートを編集することもできます。AI を利用したアシスタントをご利用ください。得られたデータを動的グラフで簡単に可視化できます。

AI で回答を得る

AI を活用したアシスタントを使用して、ビジネスに関する簡単な質問に簡単に答えを得ることができます。平易な英語で質問すると、カスタムレポートに必要なクエリをすぐに取得できます。コーディングは不要です。

簡単にコラボレーション

クエリの共有、Stripe ダッシュボードへのカスタムレポートの公開、受信トレイに直接配信されるレポートのスケジュール設定により、チームの同期を維持します。

ユースケース

チームでの Stripe Sigma の利用方法

創業者から財務チームまで、SQL の専門知識がなくても、誰でも簡単に Stripe のデータからインサイトを引き出せます。質問を入力するだけで、AI 搭載のStripe Sigma アシスタントがそれをクエリと結果報告に変換してくれます。

不審請求の申請に対する異議申し立ての割合は?

2 月の売上総額は?

請求書への支払いがまだ済んでいない顧客は?

直近の銀行入金で消し込まれる支払いは?

月々のキャッシュフローの変動は?

会社の日次の収支は?

アクティブな顧客数は?

不審請求が申請される理由は?

最も人気のサブスクリプションプランは?

クレジットカードブランドごとに行われた決済回数は?

さまざまな顧客チャネルから得られる収益は?

事業運営チームは Stripe Sigma を使って経営を効率化します。

財務チームは Stripe Sigma を使って期末処理を迅速化できます。

データ分析チームは Stripe Sigma を使って、1 ユーザーあたりの平均売上 (ARPU) から顧客の解約率などの、あらゆるデータを分析できます。

商品管理チームは Stripe Sigma を使って新しいビジネスチャンスを見つけ出します。

事業運営

不審請求の申請に対する異議申し立ての割合は?

--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
~

事業運営

2 月の売上総額は?

-- 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
~

事業運営

請求書への支払いがまだ済んでいない顧客は?

-- 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
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財務

直近の銀行入金で消し込まれる支払いは?

-- 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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財務

月々のキャッシュフローの変動は?

-- 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
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財務

会社の日次の収支は?

-- 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
~

データ分析

アクティブな顧客数は?

-- 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
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データ分析

不審請求が申請される理由は?

-- 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
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商品管理

最も人気のサブスクリプションプランは?

-- 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
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商品管理

クレジットカードブランドごとに行われた決済回数は?

-- 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
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商品管理

さまざまな顧客チャネルから得られる収益は?

-- 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
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データを活用して、行動につながるビジネスインサイトを得る

売上拡大につながる機会を見極め、業務を効率化するために、Stripe のデータツールをご活用ください。このガイドでは、より良い経営判断を下すために追跡すべき主要指標について解説しています。

作成済みテンプレート

素早く結果が得られます

様々な分野の事業で使えるレポート用クエリーを用意しています。顧客単価の算出から顧客の支払い方法分析など、カスタマイズ可能な作成済みテンプレートを使用できるほか、一から作ることも可能です。組み込みの AI を利用したアシスタントを使ってカスタム SQL クエリーを簡単に作成できます。

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使いやすいスキーマ

Stripe データをすぐに活用

Stripe に保管された構造化データ(追加のメタデータを含む)に、サイドバーから素早くアクセスできます。これにより Stripe の支払い、入金、顧客、サブスクリプション、返金などのデータと簡単に連携させられます。

支払いテーブル
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

スキーマ一覧 を閲覧

コラボレーションに特化

クエリーを保存してチーム内で共有

よく利用するクエリーを保存しておけば、いつでも再実行できます。便利なクエリーへのリンクを共有することで、チームメンバーの誰もが利用できるようになります。

フランスの顧客数は?

select id, email, shipping_address_country from customers where shipping_address_country = 'FR'
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先月の売上は?

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
~

月次の売上をどうやって計算しているんだっけ?

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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料金体系

手数料シミュレーション

30 日間の無料トライアルを始めましょう。SQL や自然言語のプロンプトを利用して Stripe データのカスタムレポートを作成することができます。トライアル期間終了後は、処理した支払いの件数とオーソリリクエストの数に応じて月額手数料が発生します。

0

月間支払い件数

0

推定月額コスト

営業にお問い合わせ 
  • 0-500

    ¥2.25/

  • 501-1,000

    ¥2/

  • 1,001-5,000

    ¥1.8/

  • 5,001-50,000

    ¥1.6/

  • 50,001+

インフラ手数料

決済額が大きい場合や高額取引を行う場合、または独自のビジネスモデルを持つ企業向けのカスタム料金体系をご用意しています。詳細については、営業チーム にお問い合わせください。

企業のアカウント管理を効率化し、データ分析をスピードアップ

Stripe Organizations では、ダッシュボードで複数のStripeアカウントにまたがるすべての事業活動または子会社を一元管理し、Stripe Sigmaを使用してすべてのアカウントのデータを分析することで、新たなビジネスインサイトにアクセスできます。

sigma.non-latin-jp

今すぐ始めましょう

Stripe データを使用してカスタムレポートを分析および作成します。

仕組みを確認

カスタムの Stripe レポートの作成方法について詳しくご紹介します。

Stripe をデータウェアハウスに連結する

データ格納先に Stripe データを一元化。分析作業を効率化して、さらなるインサイトを引き出しましょう。

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