Analysis reportJuly 1, 2026
Ecommerce KPI Dashboard
- Source
- sample-data.csv · 8 rows
Revenue (month)
$248k
+9.6%Conversion rate
2.9%
+0.2ppAvg. order value
$74
+$3Repeat purchase rate
31%
+1.4ppRevenue by week
Sample data — trailing 8 weeks
Ecommerce KPI dashboard
Ecommerce produces more metrics than any other business model; the dashboard's job is ruthless selection. Revenue, conversion, AOV, and repeat rate tell the whole story — everything else explains movements in those four.
Live render with sample data — upload your own export and this structure regenerates from your numbers, with the computation attached to every figure.
The ecommerce KPIs that matter, defined
- Conversion rate
- Orders divided by sessions. Segment by device and channel — mobile conversion problems hide inside blended rates.
- Orders ÷ Sessions × 100
- Average order value (AOV)
- Revenue divided by orders. The cheapest growth lever: raising AOV 10% usually costs less than raising traffic 10%.
- Revenue ÷ Orders
- Cart abandonment rate
- Carts created but not purchased. Above ~70% is category-normal; the dashboard should track your trend, not the scary global average.
- (Carts − Orders) ÷ Carts × 100
- Repeat purchase rate
- Share of customers with 2+ orders in the period. The retention economics of the whole store live in this number.
- Customer lifetime value (LTV)
- Average revenue per customer over their lifetime. Paired with CAC, it sets the ceiling on what you can pay for acquisition.
- AOV × Purchases per year × Years retained
Frequently Asked Questions
Everything you need to know about using AnalyzeData.
Four headliners — revenue, conversion rate, AOV, repeat purchase rate — with channel mix, cart abandonment, and LTV:CAC as the explanatory layer beneath them. The example above shows that structure.
Yes — export orders as CSV, upload, and ask for your KPI view. Revenue, AOV, and repeat-rate math are computed from the raw order rows with the code visible.
Not necessarily. Above roughly 70% is category-normal for ecommerce, so comparing yourself to the scary global average tells you little. What matters on the dashboard is your own trend: abandonment climbing week over week points at a checkout, shipping-cost, or payment-friction issue worth investigating, while a stable rate inside the normal band is just the cost of browsing behaviour.
Usually average order value, not traffic. Raising AOV 10% typically costs less than raising traffic 10%, since you are selling more to visitors you have already paid to acquire. Pair it with repeat purchase rate, where the retention economics of the whole store live, and use the LTV-to-CAC relationship to set the ceiling on what you can afford to acquire the next customer.
Build your ecommerce KPI dashboard
Upload the export you already have — the dashboard computes itself, verifiably.
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