TL;DR Most ecommerce brands track too many metrics and act on too few. Focus on 10 KPIs that actually drive decisions: revenue, AOV, conversion rate, CAC, LTV, repeat rate, ROAS, contribution margin, inventory turnover, and email revenue %. Let us build your KPI dashboard.
The Problem With Tracking Everything
Your analytics stack probably shows you 200+ metrics. GA4 alone has dozens of default reports. Shopify has its own dashboard. Your ad platforms each have 50+ columns.
More data doesn’t mean better decisions. It usually means analysis paralysis, vanity metric obsession, and weekly reporting that nobody reads.
The best ecommerce operators we’ve worked with — across 20+ teams — track fewer than 15 metrics in their primary dashboard. They check it daily. They act on it weekly.
Here’s what belongs on that dashboard and what doesn’t.
The 10 KPIs That Drive Decisions
1. Revenue (Net)
Not gross revenue. Net revenue after refunds, returns, and discounts.
Why it matters: It’s your topline reality. Everything else ladders up to this.
Frequency: Daily.
2. Average Order Value (AOV)
Total net revenue divided by total orders.
Why it matters: Increasing AOV by 10% has the same effect as increasing traffic by 10% — without the ad spend. It’s the easiest lever most brands ignore.
Frequency: Daily, trended weekly.
3. Conversion Rate
Orders divided by sessions (from GA4 or your analytics tool).
Why it matters: A 0.5% improvement in conversion rate at 100K monthly sessions = 500 more orders. That’s real money.
Frequency: Weekly (daily is too noisy).
4. Customer Acquisition Cost (CAC)
Total marketing spend divided by new customers acquired.
Why it matters: Tells you how much it costs to buy growth. If CAC exceeds first-order profit, you need repeat purchases to break even.
Frequency: Weekly, trended monthly.
5. Customer Lifetime Value (LTV)
Cumulative revenue per customer over a defined period (typically 12 months), by cohort.
Why it matters: The only metric that tells you whether your CAC is sustainable. LTV:CAC ratio below 3:1 means you’re buying unprofitable growth.
Frequency: Monthly.
6. Repeat Purchase Rate
Percentage of customers who buy more than once within 90 days.
Why it matters: Acquiring a new customer costs 5-7x more than retaining one. This metric tells you whether you have a product people come back to or a one-hit wonder.
Frequency: Weekly.
7. Blended ROAS
Total revenue divided by total ad spend across all channels.
Why it matters: Platform-reported ROAS is inflated. Blended ROAS is your reality check. If you’re spending $50K/month on ads and making $200K in revenue, your blended ROAS is 4.0 — regardless of what Meta or Google claim.
Frequency: Daily.
8. Contribution Margin
Revenue minus COGS minus variable costs (shipping, payment processing, ad spend) divided by revenue.
Why it matters: Revenue growth without margin is just burning cash faster. This tells you whether you’re actually making money on each order.
Frequency: Weekly.
9. Inventory Turnover
Cost of goods sold divided by average inventory value.
Why it matters: Dead stock kills cash flow. High turnover means efficient capital allocation. Low turnover means you’re a warehouse, not a business.
Frequency: Monthly.
10. Email/SMS Revenue %
Revenue attributed to email and SMS as a percentage of total revenue.
Why it matters: This is your owned channel revenue — acquired customers buying again without additional ad spend. Healthy brands get 25-40% from retained channels.
Frequency: Weekly.
The KPI Dashboard Layout
Here’s how to structure it:
| Section | Metrics | View |
|---|---|---|
| Top banner | Revenue (today, WoW, MoM) | Scorecards |
| Row 1 | AOV, Conversion Rate, Sessions | Sparklines with trend |
| Row 2 | CAC, Blended ROAS, Ad Spend | By channel |
| Row 3 | Repeat Rate, LTV:CAC, Email Revenue % | Trended monthly |
| Row 4 | Contribution Margin, Inventory Turnover | Monthly trend |
Everything fits on one screen. No scrolling. No tabs. One view that tells you if the business is healthy.
💡 This is what we do. We build focused KPI dashboards in Looker Studio for ecommerce brands — pulling from Shopify, GA4, and ad platforms via BigQuery. One screen, the metrics that matter, refreshed daily. Book a 20-minute discovery call — no pitch, just scoping.
What to Stop Tracking
Here are metrics that feel important but rarely drive action:
Bounce rate. It’s noisy, ambiguous, and GA4 redefined it anyway. A high bounce rate on a product page might mean people are buying immediately, not leaving.
Time on site. More time could mean confusion, not engagement. It tells you nothing actionable.
Social media followers. Vanity metric. Correlates weakly with revenue.
Page views. Unless you’re ad-supported, page views don’t pay bills.
Add-to-cart rate in isolation. Only useful as part of a full funnel analysis, not as a standalone KPI.
Platform-specific ROAS. Already covered by blended ROAS. Platform numbers are inflated and self-serving.
How to Use These KPIs
Tracking metrics is worthless without a decision framework. Here’s how each KPI should trigger action:
| KPI Trend | Signal | Action |
|---|---|---|
| Revenue down, sessions stable | Conversion problem | Check site speed, pricing, product pages |
| CAC rising, ROAS falling | Audience fatigue or competition | Refresh creative, test new audiences |
| AOV dropping | Product mix shifting | Review bundling, upsell flows |
| Repeat rate declining | Retention problem | Audit email flows, product quality |
| Contribution margin shrinking | Cost creep | Review COGS, shipping rates, discounts |
| Email revenue % dropping | List health issue | Re-engagement campaign, list cleaning |
The Weekly Review Ritual
The best operators spend 30 minutes every Monday reviewing these 10 metrics. They ask three questions:
- What changed significantly this week?
- Why did it change? (Dig into one level deeper)
- What are we doing about it this week?
That’s it. No 50-slide deck. No 2-hour meeting. A focused review that drives 2-3 actions per week. Over a year, that’s 100+ data-driven decisions.
Building This Dashboard
The technical requirements:
- Data sources: Shopify (revenue, orders, customers), GA4 (sessions, conversion), ad platforms (spend), accounting (COGS)
- Warehouse: BigQuery to blend all sources
- Extraction: Fivetran for automated daily syncs
- Visualisation: Looker Studio for the dashboard
Setup time: 2-3 weeks if you know what you’re doing. The SQL modelling for contribution margin and LTV cohorts is the complex part.
Know someone drowning in spreadsheets? Share this guide with them.
If this sounds like more work than you want to take on, that’s what we do at Chartica. Book a 20-minute discovery call — we’ll scope it out, no pitch.