Wave Business reporting analytics dashboard : 2026

Reporting Wave Business = visibilité revenue + KPIs business. Dashboard analytics + exports automatiques = standard 2026 PME modernes.

TL;DR

- KPIs essentiels : transactions, taux conversion, CA, refunds.

- Stack : PostgreSQL + Metabase (gratuit).

- Cron daily reports email + Slack.

- Comparatifs M-1, Y-1, growth tracking.

KPIs essentiels Wave

`

• Transactions :
• Volume / jour
• Tickets moyens
• Taux succès vs échec

• Revenue :
• CA brut / net (après frais Wave)
• Par produit / catégorie
• Par canal (web, app)

• Customer behavior :
• Conversions checkout → paiement
• Abandons paiement (+ raisons)
• Repeat customers

• Operationnel :
• Refunds / chargebacks
• Failed payments
• Réconciliation gaps

`

Stack reporting 2026

• PostgreSQL (DB transactions Wave normalized)
• +
• Metabase (BI gratuit, self-host ou cloud)
• ou
• PowerBI / Looker Studio
• +
• Cron jobs daily reports
• +
• Slack webhooks alerts

Schema DB analytics

`sql

-- Table dénormalisée pour analytics

CREATE TABLE wave_transactions_analytics (

id UUID PRIMARY KEY,

wave_id VARCHAR UNIQUE,

amount INT,

currency VARCHAR(3),

status VARCHAR(20),

type VARCHAR(20), -- 'checkout' | 'payout' | 'refund'

-- Dates

created_at TIMESTAMP,

paid_at TIMESTAMP,

date DATE GENERATED ALWAYS AS (DATE(created_at)) STORED,

hour INT GENERATED ALWAYS AS (EXTRACT(HOUR FROM created_at)) STORED,

weekday INT GENERATED ALWAYS AS (EXTRACT(DOW FROM created_at)) STORED,

-- Customer

customer_id UUID,

customer_phone VARCHAR,

is_repeat_customer BOOLEAN,

-- Product / order

order_id UUID,

product_category VARCHAR,

product_name VARCHAR,

-- Wave details

wave_fee INT,

net_amount INT,

device VARCHAR,

-- Indexes

INDEX idx_date (date),

INDEX idx_status (status),

INDEX idx_customer (customer_id)

);

`

Queries SQL standards

`sql

-- 1. CA daily 30 derniers jours

SELECT

date,

COUNT(*) AS transactions,

SUM(amount) AS gross_revenue,

SUM(net_amount) AS net_revenue,

AVG(amount) AS avg_ticket

FROM wave_transactions_analytics

WHERE status = 'completed'

AND date >= CURRENT_DATE - INTERVAL '30 days'

GROUP BY date

ORDER BY date DESC;

-- 2. Top 10 produits

SELECT

product_category,

product_name,

COUNT(*) AS sales,

SUM(amount) AS revenue

FROM wave_transactions_analytics

WHERE status = 'completed'

AND date >= CURRENT_DATE - INTERVAL '30 days'

GROUP BY product_category, product_name

ORDER BY revenue DESC

LIMIT 10;

-- 3. Heures pic conversion

SELECT

hour,

COUNT(*) AS transactions,

AVG(amount) AS avg_ticket

FROM wave_transactions_analytics

WHERE status = 'completed'

GROUP BY hour

ORDER BY transactions DESC;

-- 4. Customer cohort retention

WITH cohorts AS (

SELECT

customer_id,

DATE_TRUNC('month', MIN(created_at)) AS cohort_month

FROM wave_transactions_analytics

WHERE status = 'completed'

GROUP BY customer_id

)

SELECT

cohort_month,

DATE_TRUNC('month', t.created_at) AS activity_month,

COUNT(DISTINCT t.customer_id) AS active_customers

FROM wave_transactions_analytics t

JOIN cohorts c ON t.customer_id = c.customer_id

GROUP BY cohort_month, activity_month

ORDER BY cohort_month, activity_month;

`

Daily report cron

`typescript

cron.schedule('0 8 * * *', async () => { // 8am every day

const yesterday = new Date(Date.now() - 24 * 3600 * 1000)

.toISOString().slice(0, 10);

const stats = await db.query(`

SELECT

COUNT(*) AS transactions,

SUM(amount) AS revenue,

SUM(amount) FILTER (WHERE status = 'completed') AS net_revenue,

COUNT(*) FILTER (WHERE status = 'failed') AS failed,

COUNT(*) FILTER (WHERE type = 'refund') AS refunds,

AVG(amount) AS avg_ticket

FROM wave_transactions_analytics

WHERE date = $1

`, [yesterday]);

// Send Slack

await slackWebhook({

text: 📊 Rapport Wave ${yesterday},

blocks: [

{ type: 'section', text: { type: 'mrkdwn', text:

*Transactions* : ${stats.transactions}\n*Revenue* : ${stats.revenue.toLocaleString()} FCFA\n*Failed* : ${stats.failed}\n*Refunds* : ${stats.refunds}\n*Ticket moyen* : ${stats.avg_ticket.toLocaleString()}

} },

],

});

// Email équipe finance

await sendEmail('finance@kolonell.com', {

subject: Rapport Wave ${yesterday},

body: renderEmailTemplate(stats),

});

});

`

Metabase setup gratuit

`bash

# Self-host Metabase

docker run -d -p 3000:3000 \

-v metabase-data:/metabase-data \

--name metabase metabase/metabase

# Connect to PostgreSQL

# Create dashboards :

# - Daily revenue

# - Top products

# - Customer retention

# - Failed transactions

`

Coût : 0€ self-host, 80-300€/mois cloud.

FAQ

Q : Wave provides analytics dashboard ?

R : Basic. Export CSV + custom analytics = recommandé pour insights deep.

Q : Real-time vs daily ?

R : Real-time pour ops critiques (refunds, failed). Daily pour reporting business.

Conclusion

Wave Business reporting 2026 : PostgreSQL + Metabase + cron daily = stack moderne PME. KPIs business + opérationnel critiques. Self-host gratuit, cloud 80-300€/mois.