How to calculate AOV: Formula and examples

The basic AOV formula

Average order value = Total revenue ÷ Number of orders. Store generates $28,500 revenue from 750 orders = $38 AOV. Simple division reveals average spending per transaction. Formula works for any timeframe: daily ($850 revenue ÷ 22 orders = $38.64 AOV), weekly ($6,300 ÷ 165 orders = $38.18 AOV), monthly ($28,500 ÷ 750 orders = $38 AOV). Calculation stays consistent regardless of period analyzed.

Use completed orders only—not abandoned carts, not pending orders, not refunded orders. AOV measures actual revenue per completed transaction. Including incomplete transactions distorts calculation. Customer adds $85 to cart but abandons = not included in AOV. Customer completes $85 order = included. Customer completes $85 order then refunds 3 days later = remove from AOV calculation (no revenue occurred). Most analytics platforms handle inclusions/exclusions automatically, but understanding what counts prevents misinterpretation.

Step-by-step AOV calculation

Example 1: Daily AOV calculation

Monday’s completed orders: $42, $67, $23, $95, $38, $51, $72, $29, $88, $45. Step 1: Sum all order values. $42 + $67 + $23 + $95 + $38 + $51 + $72 + $29 + $88 + $45 = $550 total revenue. Step 2: Count number of orders. 10 orders. Step 3: Divide total revenue by order count. $550 ÷ 10 = $55 AOV. Monday’s average order value was $55, meaning typical customer spent $55 per transaction.

Example 2: Weekly AOV calculation

Week of March 4-10: Monday $850 revenue (22 orders), Tuesday $920 (24 orders), Wednesday $1,100 (28 orders), Thursday $890 (23 orders), Friday $1,350 (35 orders), Saturday $1,680 (42 orders), Sunday $1,210 (31 orders). Step 1: Sum weekly revenue. $850 + $920 + $1,100 + $890 + $1,350 + $1,680 + $1,210 = $8,000 total. Step 2: Sum weekly orders. 22 + 24 + 28 + 23 + 35 + 42 + 31 = 205 orders. Step 3: Calculate AOV. $8,000 ÷ 205 = $39.02 AOV. Weekly average order value was $39, combining all days together for more stable metric than daily fluctuation.

Example 3: Monthly AOV calculation

February revenue: $45,600. February orders: 1,140. February AOV: $45,600 ÷ 1,140 = $40 AOV. Monthly calculation smooths daily and weekly variance providing reliable baseline for analysis. Compare monthly AOV across time identifying trends: January $38, February $40, March $42 shows growing AOV pattern indicating successful optimization or favorable traffic mix changes.

Common calculation mistakes to avoid

Including shipping and taxes

Depends on business model, but most stores calculate AOV using product revenue only—excluding shipping charges and taxes. Order total $95 = $80 products + $12 shipping + $3 tax. AOV calculation uses $80 (product revenue), not $95 (order total). Why? Shipping and taxes aren’t controllable revenue—they’re pass-through amounts. AOV optimization focuses on increasing product purchasing, not shipping charges. Exception: if you use dynamic shipping (free on large orders, charged on small orders), including shipping in AOV calculation shows total customer cost behavior. Most important: choose one method (with or without shipping/tax) and use consistently.

Mixing currencies

International stores accepting multiple currencies must convert to single currency before AOV calculation. Monday’s orders: 3 US orders totaling $150, 2 EU orders totaling €95, 1 UK order £42. Can’t average mixed currencies. Convert all to primary currency (assuming USD): €95 = ~$103 at 1.08 rate, £42 = ~$53 at 1.26 rate. Total revenue: $150 + $103 + $53 = $306. Total orders: 6. AOV: $306 ÷ 6 = $51. Use transaction-date exchange rates for accuracy, or accept slight variance using month-end rates for simplicity.

Including refunded orders

Refunded orders should be removed from AOV calculation—they generated no actual revenue. Customer orders $85 on Monday, refunds Tuesday = not counted in AOV. Tracking platforms handle this differently: some automatically exclude refunded orders from historical reports, others require manual adjustment. Verify your platform’s approach: complete test order, immediately refund, check if AOV report includes or excludes refunded amount. High refund rates (5%+) create meaningful AOV variance if not handled correctly.

Wrong time period aggregation

Don’t calculate daily AOV, then average the daily AOVs for weekly/monthly figures—mathematically incorrect. Wrong method: Monday $42 AOV, Tuesday $38 AOV, Wednesday $45 AOV, Thursday $41 AOV, Friday $48 AOV. Average the daily AOVs: ($42 + $38 + $45 + $41 + $48) ÷ 5 = $42.80 AOV. This is WRONG. Correct method: Sum all weekly revenue ($8,000), divide by all weekly orders (205), get true weekly AOV ($39.02). Averaging AOVs weights each day equally regardless of order volume—mathematically invalid for multi-day periods.

Calculating AOV by segment

AOV by traffic source

Different sources generate different spending behaviors—segment reveals where high-value customers originate. Email: $2,400 revenue from 48 orders = $50 AOV. Organic search: $3,100 from 85 orders = $36.47 AOV. Paid search: $1,800 from 52 orders = $34.62 AOV. Social media: $900 from 38 orders = $23.68 AOV. Analysis: email generates highest AOV (2x social), organic solid, social significantly lower. Decision: prioritize email list growth (highest AOV source), investigate social targeting (lowest AOV—wrong audience or discovery-mode browsing?).

AOV by device type

Desktop: $4,200 revenue from 95 orders = $44.21 AOV. Mobile: $3,800 from 110 orders = $34.55 AOV. Tablet: $400 from 10 orders = $40 AOV. Mobile AOV is 22% lower than desktop—normal pattern reflecting purchase behavior differences. Mobile browsing versus desktop completing. Device segmentation identifies whether mobile optimization focuses on conversion improvement (get mobile browsers to buy) or AOV improvement (get mobile buyers to spend more). Large gaps (40%+) indicate device-specific experience problems worth investigating.

AOV by customer type

New customers: $1,850 revenue from 58 orders = $31.90 AOV. Returning customers: $6,550 from 147 orders = $44.56 AOV. Returning customer AOV is 40% higher—typical pattern showing trust and familiarity enable larger purchases. Growing returning customer percentage naturally increases overall AOV. If returning AOV isn’t significantly higher (under 15% difference), investigate why loyal customers aren’t spending more—suggests product line limitations or missed upsell opportunities.

AOV by product category

Apparel orders: $5,200 from 142 orders = $36.62 AOV. Accessories orders: $1,100 from 48 orders = $22.92 AOV. Footwear orders: $2,100 from 35 orders = $60 AOV. Category AOV reveals: footwear drives highest spending, accessories lowest, apparel middle. Strategy implications: promote footwear more aggressively (high AOV source), bundle accessories with apparel/footwear purchases (raise accessories AOV through complementary buying). Category analysis informs product mix optimization and promotional focus.

Using AOV calculations for decisions

Determining free shipping threshold

Current AOV: $58. Free shipping threshold should sit 25-35% above current AOV encouraging incremental purchases. Calculation: $58 × 1.25 = $72.50, $58 × 1.35 = $78.30. Set threshold at $75 (round number between calculated range). Customers currently spending $58 see $75 threshold within reach—adding one more item achieves free shipping. Monitor AOV after implementing: if AOV increases toward threshold, strategy works. If AOV stays flat, threshold might be too high or free shipping insufficiently motivating.

Calculating break-even AOV

Fixed costs per order: payment processing $0.30 + 2.9% of order value, packaging $3.50, labor $4.20, shipping label $0.80 = $8.80 base costs (ignoring percentage fee temporarily). With 35% product margin, break-even AOV calculation: (Fixed costs ÷ Margin %) + payment processing adjustment. Basic formula: $8.80 ÷ 0.35 = $25.14. Adding 2.9% processing: $25.14 ÷ 0.971 = $25.89 break-even AOV. Orders below $26 lose money before marketing costs. Current AOV $58 provides comfortable buffer—most orders are profitable. Helps inform: minimum order policies, shipping surcharges for small orders, marketing cost sustainability.

Setting profitable discount thresholds

Offering $10 off orders over $50. Current AOV $58, margin 40%. Impact analysis: Without discount: $58 order × 40% = $23.20 gross profit. With discount: ($58 - $10) × 40% = $19.20 gross profit. Discount costs $4 in profit per redeemed order (17% profit reduction). If discount increases order frequency or AOV enough to offset profit loss, remains viable. Track: does $10 off $50 increase orders from customers who would have spent $45-50? Does it increase AOV from $58 baseline? If yes to either, discount works. If customers who would have spent $58+ use discount without increasing spending, discount is pure margin loss.

Tracking AOV trends over time

Week-over-week AOV comparison

Week 1: $62 AOV. Week 2: $58 AOV. Week 3: $65 AOV. Week 4: $60 AOV. Weekly variance is normal—10% fluctuation (±$6 on $60 baseline) doesn’t indicate problems. Look for sustained directional trends: 8+ weeks of declining AOV indicates systematic issue (traffic quality degradation, pricing pressure, product mix changes). 8+ weeks of increasing AOV indicates positive trends (successful optimization, improving customer mix, effective bundling). Don’t overreact to single-week changes—requires multi-week pattern for meaningful interpretation.

Year-over-year AOV comparison

March 2024 AOV: $55. March 2025 AOV: $64. Year-over-year increase: 16.4%. Significant improvement indicating successful growth—pricing increases, better product mix, improved bundling, premium customer acquisition, or combination of factors. YoY comparison isolates real growth from seasonal variance. March-to-April comparison might show AOV change due to seasonality, but March-to-March isolates actual performance evolution. Always include YoY perspective in monthly AOV reviews preventing misinterpretation of seasonal patterns.

Seasonal AOV patterns

Fashion retailer AOV pattern: January $52 (post-holiday, bargain hunting), February $48 (slowest retail month), March $54 (spring wardrobe refresh), April $56 (growing season), November $68 (Black Friday boost), December $72 (holiday shopping). Understanding seasonal baseline prevents misinterpreting normal patterns. December AOV $72 versus November $68 = expected increase (holiday gifting). December 2025 $72 versus December 2024 $69 = meaningful 4.3% improvement (pricing, optimization, or mix). Separate seasonal movement from performance improvement through YoY analysis.

Advanced AOV calculations

Revenue per session using AOV

Revenue per session (RPS) combines conversion rate and AOV revealing session value. Formula: Conversion rate × AOV = RPS. Example: 2.5% conversion rate, $60 AOV. RPS = 0.025 × $60 = $1.50 per session. Every 100 sessions generates $150 revenue on average. RPS enables traffic source valuation: Source A delivers 1,000 sessions at $1.50 RPS = $1,500 revenue. Source B delivers 600 sessions at $2.20 RPS = $1,320 revenue. Despite lower volume, Source B generates comparable revenue through better quality (higher conversion or AOV or both). RPS calculation prevents volume bias—optimizing for session value, not just session count.

AOV impact on customer acquisition cost

Maximum sustainable CAC calculation uses AOV and margin. Formula: (AOV × Margin %) × Target profit retention = Max CAC. Example: $80 AOV, 40% margin, 70% target profit retention (keeping 70% of gross profit, spending 30% on acquisition). Calculation: ($80 × 0.40) × 0.70 = $22.40 for retained profit. Maximum CAC: ($80 × 0.40) × 0.30 = $9.60. Store can spend up to $9.60 acquiring customers at $80 AOV maintaining target economics. Increasing AOV to $100 same margin: max CAC becomes $12. AOV growth expands acquisition capacity—can bid more aggressively while maintaining profitability.

Weighted average AOV

Calculating combined AOV across multiple channels with different performance. Email: $1,200 revenue, 24 orders, $50 AOV. Organic: $2,800 revenue, 82 orders, $34.15 AOV. Paid: $1,600 revenue, 42 orders, $38.10 AOV. Don’t average the AOVs ($50 + $34.15 + $38.10 = $122.25 ÷ 3 = $40.75)—mathematically wrong. Correct weighted calculation: Total revenue $5,600 ÷ Total orders 148 = $37.84 overall AOV. Weights naturally by volume—82 organic orders influence average more than 24 email orders. Always calculate from totals, never by averaging averages.

Interpreting AOV changes

AOV increase with stable conversion rate

Month 1: 2.4% conversion, $58 AOV. Month 2: 2.4% conversion, $65 AOV. Interpretation: successful AOV optimization without harming conversion. Customers buying more per transaction—bundling working, upsells effective, premium products gaining traction, or favorable traffic mix shift. Continue strategies driving AOV growth. Calculate revenue impact: Month 1 RPS = 0.024 × $58 = $1.39. Month 2 RPS = 0.024 × $65 = $1.56. Revenue per session improved 12% purely from AOV gains.

AOV increase with conversion rate decline

Month 1: 2.8% conversion, $55 AOV, RPS $1.54. Month 2: 2.2% conversion, $68 AOV, RPS $1.50. Interpretation: AOV optimization cannibalized conversion—higher pricing, aggressive bundling, or minimum orders pushed some buyers away. Revenue per session declined despite AOV gains. Strategy failed—reversed optimization preserving conversion rate. AOV improvements must maintain or improve RPS, otherwise they reduce revenue despite higher individual order values.

AOV decline with conversion rate increase

Month 1: 2.0% conversion, $72 AOV, RPS $1.44. Month 2: 2.6% conversion, $58 AOV, RPS $1.51. Interpretation: successfully attracted more buyers at lower price points—promotions, discounts, entry-level products. Revenue per session improved 5% despite AOV decline. Strategy worked—volume increase offset individual order value decrease. Common pattern during promotional periods or audience expansion. Acceptable if RPS improves; concerning if RPS declines.

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Frequently asked questions

Should I include or exclude taxes and shipping in AOV?

Most stores exclude shipping and taxes, calculating AOV from product revenue only. Reason: shipping and taxes are pass-through amounts, not controllable revenue. AOV optimization focuses on product purchasing behavior. Exception: if shipping strategy is integral to pricing (free shipping always, or dynamic shipping based on order size), including shipping shows total customer cost. Most important: choose one method and use consistently. Mixed approaches over time create incomparable data. Document your method preventing confusion during analysis.

Why is my Shopify AOV different from my Google Analytics AOV?

Platforms calculate AOV slightly differently: inclusion/exclusion of shipping, handling of refunds, timezone differences, attribution windows. Small differences (5-10%) are normal and expected. Choose one platform as source of truth—typically your e-commerce platform (Shopify, WooCommerce) since it has definitive order data. Use that platform’s AOV consistently rather than switching between sources or trying to reconcile differences. Platform differences don’t indicate problems—just definitional variances.

How do I calculate AOV if some orders are in different currencies?

Convert all orders to your primary currency using transaction-date exchange rates, then calculate AOV normally. Most platforms handle this automatically—verify by checking reports showing single-currency totals. Manual calculation: convert each order at its transaction-date rate, sum converted revenue, divide by total orders. Acceptable shortcut: use month-end exchange rates for all orders in that month. Creates small inaccuracies but dramatically simpler than tracking daily rate fluctuations. Impact is minimal unless extreme currency volatility.

Should I set different AOV targets for different traffic sources?

Yes. Different sources naturally generate different AOV—email typically highest, social typically lowest, organic and paid in between. Set source-specific targets based on each source’s historical performance: Email current $52 AOV, target $57 (10% improvement). Social current $28 AOV, target $34 (20% improvement). Organic current $42 AOV, target $46 (10% improvement). Percentage improvement targets appropriate to baseline, rather than forcing all sources toward single absolute target. Email reaching $57 and social reaching $34 both represent success despite $23 gap between them.