15 min read · Ecommerce Growth · Last updated July 2026
Quick answer: Most stores track the wrong metrics. Traffic and revenue tell you what happened. Conversion rate, CAC, ROAS, AOV, and repeat purchase rate tell you why — and what to do about it. These 10 KPIs, tracked weekly, give you complete visibility over store health.
Introduction
A store owner asks: “How are we doing?”
The wrong answer is: “We did $47,000 in revenue this month.”
The right answer is: “Revenue was $47,000. CVR held at 2.8%. But CAC jumped 22% this month and repeat purchase rate dropped to 18% — we need to look at our retention campaigns.”
Revenue is a result. KPIs are the causes. Tracking only revenue tells you what happened after the fact. The right set of KPIs tell you what is going to happen — and what to do before it does.
This guide covers the 10 metrics every ecommerce operator should review weekly, with exact formulas, industry benchmarks, and what it means when each metric moves in either direction.
What you’ll learn:
– The 10 essential ecommerce KPIs and how to calculate each
– Industry benchmarks for each metric
– What a rising or falling metric actually signals
– How to build a weekly KPI review rhythm
Table of Contents
- Vanity Metrics vs Revenue Metrics
- KPI 1: Conversion Rate
- KPI 2: Average Order Value
- KPI 3: Customer Acquisition Cost
- KPI 4: Customer Lifetime Value
- KPI 5: Return on Ad Spend
- KPI 6: Cart Abandonment Rate
- KPI 7: Repeat Purchase Rate
- KPI 8: Email Revenue Attribution
- KPI 9: Product Return Rate
- KPI 10: Net Promoter Score
- KPI Dashboard Calculator
- KPI Health Checker
- FAQ
Vanity Metrics vs Revenue Metrics
Before the 10 KPIs, a framework for understanding which numbers matter.
Vanity metrics feel good but do not drive decisions:
– Total website traffic (growing traffic with declining CVR is a problem, not a win)
– Social media followers (followers who do not buy are not customers)
– Email list size (an unengaged list of 100,000 is worth less than an engaged list of 10,000)
– Page views (correlated with traffic, not with revenue)
Revenue metrics connect directly to store health:
– Conversion rate — traffic quality and UX
– AOV — product mix and upsell effectiveness
– CAC — channel efficiency and profitability
– CLV — retention and product satisfaction
Track revenue metrics. Use vanity metrics only as context.
Key takeaway: If a metric cannot help you make a specific decision, it is vanity. Every KPI in this list connects to a specific action you would take if it changed.
KPI 1: Conversion Rate
Formula: (Number of orders / Total sessions) × 100
Example: 250 orders ÷ 10,000 sessions × 100 = 2.5% CVR
Shopify benchmark: 2.5–3.0% for general merchandise. 1.5–2.5% for fashion. 4–6% for specialty/niche.
What a drop signals:
– Traffic quality change (new ad audience, channel mix shift)
– Product page or checkout UX issue
– Price increase without corresponding value communication
– Seasonal shift (common in Q1 for fashion, Q4 for most)
What a rise signals:
– CRO improvements working
– Better-qualified traffic source
– Price reduction or promotional period
– New trust signals or review volume increase
How to improve: See our full CRO guide. The fastest wins are usually guest checkout (if not enabled), page speed, and product image quality.
Review frequency: Weekly, with 7-day and 28-day trends side by side.
KPI 2: Average Order Value
Formula: Total revenue ÷ Number of orders
Example: $47,500 revenue ÷ 650 orders = $73.08 AOV
Benchmark: Varies widely by category. Fashion: $70–$120. Home goods: $80–$150. Electronics: $100–$250. Supplements: $55–$90.
What a drop signals:
– Customers buying lower-priced items (mix shift)
– Discounting on high-margin SKUs
– Loss of upsell/bundle effectiveness
– New customer mix vs. returning (new customers tend to order lower)
What a rise signals:
– Successful upsell or bundle implementation
– Customers choosing premium variants
– Free shipping threshold working (customers topping up cart)
How to improve:
– Set a free shipping threshold at 20–30% above your current AOV
– Add product bundles (complementary items)
– Implement post-add-to-cart upsell (“Customers also bought”)
– Offer volume discounts that encourage multi-unit purchases
Review frequency: Weekly. Track alongside revenue to distinguish between “selling more” and “selling more expensive.”
KPI 3: Customer Acquisition Cost
Formula: Total marketing spend ÷ Number of new customers acquired
Example: $12,000 ad spend ÷ 180 new customers = $66.67 CAC
What makes CAC useful vs. not: CAC is only meaningful in context of CLV and gross margin. A $90 CAC is fine if CLV is $350 and gross margin is 60%. It is disastrous if CLV is $80.
Benchmark: Target CAC at no more than 30–40% of first-order gross profit. If AOV is $90 and gross margin is 50%, first-order profit is $45. Max CAC = $18 for profitable first purchase.
What a rise signals:
– Ad platform CPMs increasing (Meta, Google)
– Audience saturation in core channels
– Creative fatigue (ads not performing as well)
– Competitive pressure in your niche increasing bid prices
What a drop signals:
– New efficient channel discovered
– Creative or targeting improvement
– Seasonal CPM reduction
– Organic/word-of-mouth growth reducing paid dependency
How to improve:
– Improve CVR on landing pages (same ad spend, more customers)
– Test new ad creative every 2–4 weeks
– Diversify acquisition channels (email capture, SEO, referral)
– Improve post-purchase experience to generate word-of-mouth
KPI 4: Customer Lifetime Value
Formula (simple): AOV × Average purchase frequency per year × Average customer lifespan (years)
Example: $80 AOV × 2.5 purchases/year × 2.5 years = $500 CLV
Formula (for existing customers): Average revenue per customer across their entire purchase history.
Why CLV matters more than CAC: CLV is the ceiling on how much you can afford to spend acquiring a customer. A store with CLV of $500 can outbid every competitor with CLV of $150 on the same keyword.
What a drop signals:
– Return rate increasing
– Second purchase rate declining
– Product quality issue leading to churn
– Poor post-purchase experience
What a rise signals:
– Retention email sequences working
– Product range expansion giving customers more to buy
– Community or loyalty program increasing purchase frequency
How to improve:
– Win-back email flows for customers who have not purchased in 60–90 days
– Post-purchase onboarding sequence (usage tips, complementary products)
– Loyalty program with purchase-frequency rewards
– Subscription offerings for consumable products
KPI 5: Return on Ad Spend
Formula: Ad revenue attributable ÷ Ad spend
Example: $28,000 attributed revenue ÷ $6,000 ad spend = 4.67 ROAS
How to interpret ROAS: ROAS is a ratio, not a profit metric. A 4.0 ROAS sounds good, but if your gross margin is 30%, you are breaking even. The formula for minimum viable ROAS:
Break-even ROAS = 1 / Gross margin %
- 30% margin → break-even ROAS = 3.33
- 50% margin → break-even ROAS = 2.0
- 60% margin → break-even ROAS = 1.67
Target ROAS should be 1.5–2× break-even ROAS to account for blended costs.
Benchmark by channel:
– Google Shopping: 4–8x (established campaigns)
– Meta retargeting: 5–12x
– Meta prospecting: 2–5x
– Google branded search: 10–20x (high intent, low competition)
What a drop signals:
– Creative fatigue (ad frequency too high, CTR declining)
– Audience size shrinking
– Competitive pressure increasing CPCs
– Seasonal demand decline
– Attribution window change
Review frequency: Weekly. Always review at 7-day and 28-day windows — one-week ROAS fluctuates more than the 28-day trend.
KPI 6: Cart Abandonment Rate
Formula: (1 – Completed purchases / Cart sessions) × 100
Example: 1 – (250 / 870) = 71.3% abandonment rate
Benchmark: 65–75% is typical. Below 60% is excellent. Above 80% signals significant checkout friction.
What a rise signals:
– New friction in checkout (e.g., payment option removed)
– Shipping cost increase or threshold change
– Guest checkout removed or harder to find
– Mobile checkout UX degraded
– Page speed issue in checkout
How to measure precisely: In GA4, build a funnel exploration from begin_checkout to purchase. The inverse of your completion rate is your abandonment rate at each step.
Recovery strategies:
– Abandoned cart email sequence (send at 1 hour, 24 hours, 72 hours post-abandonment)
– SMS abandonment recovery (higher open rate than email)
– Exit-intent popup in cart with a discount offer
KPI 7: Repeat Purchase Rate
Formula: (Number of customers with 2+ orders ÷ Total customers) × 100
Example: 320 repeat customers ÷ 1,400 total customers × 100 = 22.9% repeat purchase rate
Benchmark: 20–30% for general ecommerce. 35–45% for consumable or subscription products. 15% or lower signals a retention problem.
Why it matters: Repeat customers cost 5–7× less to sell to than new customers. They have higher AOV and higher CLV. Repeat purchase rate is the clearest signal of whether your product and post-purchase experience are working.
What a drop signals:
– Product quality issue
– Poor post-purchase experience
– Competitor winning your customers back
– No retention email sequence
– One-time gift buyers (seasonal spike followed by natural decline)
How to improve:
– Post-purchase email sequence: order confirmation → shipping notification → delivery + usage tips → review request → “Ready to reorder?” at predicted repurchase date
– Loyalty program that rewards frequency
– Subscription option for consumable products
– VIP access for top customers (early access to new products)
KPI 8: Email Revenue Attribution
Formula: Revenue from email-attributed orders ÷ Total revenue × 100
Typical target: Email should drive 25–40% of total revenue for an optimized ecommerce store.
What this measures: Whether your email program is a growth channel or just a newsletter.
How to track: In Klaviyo, the Revenue dashboard shows email-attributed revenue directly. In GA4, filter by Source/Medium = “email / klaviyo” (or your ESP).
Baseline flows to have running:
– Welcome series (days 0, 3, 7 post-signup)
– Abandoned cart (1 hour, 24 hours, 72 hours)
– Post-purchase sequence (confirmation, shipping, delivery, review request, winback)
– Browse abandonment (viewed product, no add to cart)
Each flow is measurable — you can see exactly which email sequence generated which revenue and optimize accordingly.
KPI 9: Product Return Rate
Formula: (Number of returned items ÷ Number of items sold) × 100
Benchmark by category:
– Apparel: 25–40% (sizing and fit issues)
– Electronics: 8–15%
– Home goods: 10–20%
– Beauty: 5–10%
Why it is a KPI: High return rates destroy margin. In apparel, a 40% return rate on a product with 50% gross margin effectively means your real margin is closer to 30% after processing and restocking costs.
What a rise signals:
– Product quality issue (inspect the returns — what reason do customers give?)
– Product images or descriptions misrepresenting the product
– Sizing issue (photos show model in size Small but description is incorrect)
– Damaged in shipping (packaging issue)
How to track: In Shopify, filter orders by refund status. In GA4, the refund event tracks this at the item level.
KPI 10: Net Promoter Score
Formula: % Promoters (score 9–10) − % Detractors (score 0–6)
Benchmark: +50 is excellent for ecommerce. +30–50 is good. Below +20 signals product or experience problems.
How to collect: Send an NPS survey in your post-purchase email sequence at 7–14 days post-delivery. One question: “How likely are you to recommend [Brand] to a friend or colleague?” (0–10 scale).
Why it matters: NPS is a leading indicator for word-of-mouth growth. High NPS stores grow organically through referrals without needing to increase ad spend proportionally.
KPI Dashboard Calculator
Weekly KPI Calculator
Enter your weekly numbers to calculate your core KPIs instantly.
KPI Health Checker
KPI Health Checker
Rate each KPI trend over the last 4 weeks.
FAQ
How often should I review these KPIs?
Weekly review of the core five: CVR, AOV, ROAS, CAC, and cart abandonment. Monthly review of CLV, repeat purchase rate, return rate, email attribution, and NPS. The weekly KPIs react quickly to changes (new ad creative, checkout change). The monthly KPIs reflect structural trends.
What should my minimum ROAS be?
Break-even ROAS = 1 ÷ gross margin. For a 50% margin store, break-even ROAS is 2.0. Target ROAS should be at least 1.5–2× break-even (3.0–4.0 ROAS for a 50% margin store) to cover overhead and generate profit.
Is a high return rate always bad?
Not necessarily — in apparel, 30–35% return rates are normal and expected. The issue is whether your return rate is above benchmark for your category, and whether specific products drive outsized returns. A single product with a 60% return rate in a fashion store needs attention. A 30% blended rate across the catalog is normal.
What is a realistic NPS target for an ecommerce store?
Above +50 is excellent. +30–50 is good and represents strong organic word-of-mouth potential. Below +20 suggests that customers are unlikely to refer others actively, which means you are more dependent on paid acquisition for growth.
How do I track repeat purchase rate in Shopify?
In Shopify Analytics → Customers → Returning customer rate. You can also build a custom report filtering customers with order count > 1 divided by total unique customers in the same period. For more granular cohort analysis, use GA4 or Klaviyo’s retention reports.
My ROAS is high but I am not profitable. How?
ROAS only measures return on ad spend — it excludes product COGS, shipping, returns, overhead, and platform fees. A 5× ROAS on a 20% margin product means you are generating $5 in revenue per $1 of ad spend, but keeping only $1 in gross profit before any other costs. Profit calculation = (revenue × gross margin) − ad spend.
Conclusion
Tracking 10 KPIs sounds like a lot. In practice, it is a 30-minute weekly review that tells you everything you need to know about store health before problems become crises.
Build a simple dashboard — even a spreadsheet works — where you enter these 10 numbers each week. Look for trends, not single-week spikes. The store that notices its repeat purchase rate sliding from 28% to 21% over 6 weeks and investigates early beats the store that notices the revenue cliff three months later.
The best ecommerce operators are not the ones who check their revenue every hour. They are the ones who check the right 10 numbers every week and know exactly what each one means.
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Written by the Ignited Nepal ecommerce team. ignitednepal.com