E-Commerce-Datenanalyse für Einsteiger
Verwandle Zahlen in Entscheidungen — die wichtigsten Kennzahlen (CAC, LTV, AOV, Conversion Rate), die jeder Verkäufer kennen muss, plus die kostenlosen Tools zu ihrer Messung.
The 4 metrics that decide everything
| Metric | Formula | What it tells you |
|---|---|---|
| AOV (Avg Order Value) | Revenue ÷ Orders | Should you raise prices or upsell? |
| CAC (Customer Acquisition Cost) | Ad spend ÷ New customers | Is advertising profitable? |
| LTV (Lifetime Value) | Avg orders × AOV × Repeat rate | How much is a customer worth? |
| CVR (Conversion Rate) | Orders ÷ Visitors | Is your listing good enough? |
The golden rule: LTV > 3× CAC. If a customer costs $10 to acquire (CAC), they should bring $30+ over their lifetime (LTV). Below 3×, you're burning money.
Where to find your data (free tools)
- Amazon Seller Central → Business Reports: daily units, conversion rate, session data, Buy Box %. Free for all sellers.
- Shopee Seller Center → Business Insights: views, conversion, traffic sources.
- Shopify Analytics → Dashboard: revenue, traffic, conversion, repeat rate. Free on all Shopify plans.
- Google Analytics 4 → for Shopify/DTC. Tracks traffic source, user journey, funnel.
- Helium 10 / Jungle Scout → Amazon product research + competitor data (paid).
Reading Amazon Business Reports
- Detail Page Sales & Traffic → find your top ASINs. The 80/20 rule: 20% of products make 80% of revenue. Double down on winners.
- Session percentage → which products get the most traffic. High traffic but low sales = listing problem (fix images/copy/price).
- Unit Session % (conversion) → below 10% means your listing isn't converting. Above 15% is excellent.
- Buy Box % → if below 90%, you're losing the Buy Box (price too high or out of stock).
Weekly review routine (30 min)
- Revenue vs last week → trending up or down? Investigate drops.
- Top 5 keywords (search term report) → are customers finding you for the right terms?
- ACOS / TACOS → ad efficiency. Rising ACOS with flat sales = optimize campaigns.
- Inventory days → will you stock out in 30 days? Reorder now if so.
- Return rate → spikes mean a quality issue. Check recent reviews for patterns.
Common data mistakes
- Looking at revenue, not profit → $10k revenue with $9k cost = $1k profit. Track margin, not top line.
- Ignoring LTV → a $20 CAC looks bad until that customer buys 5 times ($150 LTV).
- Not tracking ad-attributed vs organic → if sales only come from ads, you have no organic moat. Build reviews + ranking.
- Analysis paralysis → 5 key metrics, weekly review, act on patterns. Don't drown in data.
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