"What's a good Shopify conversion rate?" is the wrong question — but it's the one every operator asks first. The honest answer: it depends on your vertical, your traffic source, your AOV, and whether you're comparing all sessions or just product-page sessions. This piece gives the actual benchmarks and explains why chasing CR in isolation is how stores miss their forecast.
Median conversion rate by vertical (2026)
These are blended all-session conversion rates for stores doing more than $250K annual revenue. Higher-AOV verticals run lower CR; impulse-purchase verticals run higher.
- Beauty & cosmetics: 2.4% – 4.0%
- Apparel & accessories: 1.8% – 3.2%
- Health & wellness supplements: 2.0% – 3.8%
- Food & beverage: 2.5% – 4.5%
- Pet products: 2.2% – 3.6%
- Home goods & decor: 1.4% – 2.4%
- Electronics & gadgets: 1.2% – 2.0%
- Furniture (high AOV): 0.4% – 1.0%
- Jewelry (high AOV): 0.6% – 1.4%
If you sit at the median, you're average — not failing. Below the low end, diagnose the funnel; above the high end, your moat is probably brand or product-market fit, not a tactical CRO trick anyone can copy.
The four metrics that move revenue more than CR
- AOV (average order value). A 10% AOV lift moves revenue 10% immediately. Bundles, upsells, and free-shipping thresholds all move AOV faster than CR experiments do.
- Repeat-purchase rate. The second order changes the unit economics of the first. If your repeat rate sits below 20% within 90 days, your CAC math is fragile no matter how good the CR.
- Contribution margin per order. Revenue is vanity; contribution margin (price − COGS − payment fees − shipping − returns − fulfillment) is what funds growth. CR-obsessed stores often discount their way to higher CR and lower margin.
- Email/SMS revenue share. Best-in-class stores get 25–35% of revenue from owned channels. That share is the difference between a brand and a Meta-ads-dependent reseller.
Our Shopify revenue calculator models all four together so you can see which lever moves your number the most.
The forecast trap
Most store forecasts assume traffic grows linearly while CR and AOV stay constant. Reality: scaling paid traffic almost always drags CR down because incremental audiences are colder. If you're modeling a 3× traffic increase, model a 15–25% CR decline alongside it. The forecast still might pencil, but it pencils honestly.
How to read your funnel without lying to yourself
Segment everything. A blended 2.1% CR can hide:
- 4.5% CR on returning visitors
- 1.6% CR on cold paid traffic
- 0.4% CR on social referrals
The fix in each case is different. Improving cold-paid CR is a creative + landing page problem; improving social-referral CR is usually a "wrong audience" problem upstream of the site.
What "good" looks like, holistically
A healthy Shopify store at $1M+ ARR usually shows: vertical-median CR, AOV at least 1.4× the cost of acquiring a customer, repeat-purchase rate above 25% at 90 days, contribution margin above 35%, and 25%+ revenue from email/SMS. Hit four of those five and you have a real business. Optimize for CR alone and you have a metric.
For paid acquisition
If a meaningful portion of your traffic is Google Ads, model the spend before scaling. Our Google Ads ROAS calculator includes break-even CPA and gross-margin-adjusted ROAS so you can see whether the campaign actually pencils.