> ## Documentation Index > Fetch the complete documentation index at: https://docs.vortexiq.ai/llms.txt > Use this file to discover all available pages before exploring further. # Average Order Value, Adobe Commerce > Average Order Value for Adobe Commerce stores. Tracked live in Vortex IQ Nerve Centre. How to read it, why it matters, and how to act on it. **Metrics type:** [Supporting Metrics](/nerve-centre/overview#metrics-types-explained) • **Category:** [Ecommerce Platform](/nerve-centre/connectors#connectors-by-type) ## At a glance > Average Order Value across all orders in the period: `SUM(grand_total) / COUNT(orders)`. AOV on Adobe Commerce typically runs higher than Shopify/BigCommerce equivalents due to the B2B mix; a typical Adobe Commerce merchant sees blended AOV of $150 to $400 vs Shopify's $80 to $150. Movements in AOV reveal product-mix changes, promotional impact, and B2B/B2C segment shifts. | | | | ------------------------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **What it counts** | `AVG(grand_total)` over orders within the period. Each order contributes one observation regardless of line-item count. | | **API field** | `grand_total` from `GET /rest/V1/orders`. | | **VAT / tax treatment** | **Tax-inclusive on B2C; tax-exempt on most B2B** (resale certificates). For a B2B-heavy Adobe Commerce store the blended AOV understates the inclusive-equivalent figure for the B2C portion. | | **Shipping inclusion** | **Included.** `grand_total` adds `shipping_amount`. Stores with sharp regional shipping differences (heavy items, fragile glassware) see non-trivial AOV variance month-on-month from shipping alone. | | **Discounts** | **Already deducted.** Post-promotion. A flash-sale period drags AOV down. | | **Credit Memo refund treatment** | **NOT subtracted.** AOV is gross. For net-of-refund AOV, divide [Total Revenue](/nerve-centre/kpi-cards/adobe-commerce/total-revenue) net by [Order Count](/nerve-centre/kpi-cards/adobe-commerce/total-orders). | | **`state` machine inclusion** | All states except `canceled`. Includes `pending_payment` (B2B net-30 in particular). | | **`pending_payment` quirk** | Included. Adobe Commerce orders sit in `pending_payment` until gateway callback or AP approval; excluding them would make AOV volatile and understate B2B contribution. | | **Multi-currency `grand_total` vs `base_grand_total`** | Uses `base_grand_total` for cross-currency roll-up. Display can be configured per-currency for merchants who want to see GBP-only and USD-only averages. | | **Store View scope (`store_id`)** | All Store Views by default. Per-Store-View AOV is recommended on multi-region stores; the consumer-USD AOV typically differs materially from B2B-USD AOV. | | **Time window** | `30D vsP` (trailing 30 days vs prior 30 days). | | **Alert trigger** | `drop >10% vsP`. | | **Sentiment key** | `aov_trend` | | **Roles** | owner, marketing | ## Calculation ``` AVG(grand_total) WHERE date BETWEEN [period_start, period_end] ``` ## Worked example A specialty kitchenware retailer on Adobe Commerce 2.4.6 with US, UK, and B2B Store Views. Trailing 30-day window ending Monday 4 May 26. **Blended AOV (all Store Views, all customer types):** | Period | Order count | `SUM(base_grand_total)` | AOV | | ------------ | ----------- | ----------------------- | --------- | | Trailing 30D | 6,070 | \$1,230,340 | \$202.69 | | Prior 30D | 6,140 | \$1,178,800 | \$191.99 | | **Delta** | -1.1% | +4.4% | **+5.6%** | **Per-segment breakdown:** | Segment | Trailing 30D AOV | Prior 30D AOV | Delta | | --------------- | ---------------- | ------------- | ----- | | B2B (Companies) | \$642.82 | \$618.40 | +3.9% | | B2C consumer | \$68.29 | \$69.90 | -2.3% | **Per-Store-View breakdown:** | Store View | Orders | AOV | | ----------- | ------ | -------- | | US consumer | 2,610 | \$72.40 | | UK consumer | 2,040 | \$63.10 | | B2B portal | 1,420 | \$642.82 | What this is telling the merchant: 1. **Blended AOV grew 5.6%** but the headline obscures the segment story. 2. **B2B AOV grew 3.9%**: healthy, accounts buying slightly larger baskets. 3. **B2C AOV dropped 2.3%**: smaller consumer baskets. Could be promotional drag, smaller-basket demographic shift, or a shipping-fee change that pushed customers to single-item orders. 4. **The blended AOV is rising despite B2C contracting because B2B order count grew** (412 trailing vs 386 prior, +6.7%); more B2B mix in the average pulls it up. 5. **The composition trap**: a leadership view that watched only blended AOV would conclude "AOV is up, all is well". The segmentation reveals B2C contraction that warrants its own action plan. 6. **Cross-checking [B2B Revenue Share](/nerve-centre/kpi-cards/adobe-commerce/b2b-revenue-share)**: B2B share rose from 47% to 53%. Confirms the mix shift driving blended AOV. 7. **Cross-checking [Discount %](/nerve-centre/kpi-cards/adobe-commerce/discount-of-revenue)**: discount% on B2C is up 2.4 pts, pulling AOV down on that segment. A spring sale is running. Once the sale ends, B2C AOV should recover. 8. **Action**: extend the discount monitoring window, set a checkpoint to re-measure B2C AOV in the 30 days after the sale ends. If it doesn't recover, the issue is structural rather than promotional. The point: AOV is a composite metric. On Adobe Commerce especially, the B2B/B2C and per-Store-View segmentation reveals 2 to 3 distinct stories that the blended figure masks. ## Sibling cards merchants should reference together AOV is a composite; the value comes from the cards that decompose it. | Card | Why pair it with AOV | | ----------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------ | | [Total Revenue](/nerve-centre/kpi-cards/adobe-commerce/total-revenue) | The numerator. AOV change can be revenue-driven (numerator change) or order-driven (denominator change); both decompositions matter. | | [Total Orders](/nerve-centre/kpi-cards/adobe-commerce/total-orders) | The denominator. Watch for AOV moving inversely to order count, classic mix-shift signature. | | [B2B AOV vs B2C AOV](/nerve-centre/kpi-cards/adobe-commerce/b2b-aov-vs-b2c-aov) | The segment split. Adobe Commerce blended AOV is 80% explained by segment mix in most stores. | | [B2B Revenue Share](/nerve-centre/kpi-cards/adobe-commerce/b2b-revenue-share) | The shift in mix that drives blended AOV. | | [Discount %](/nerve-centre/kpi-cards/adobe-commerce/discount-of-revenue) | Discounts pull AOV down. A campaign period sees AOV drop and discount% rise in lockstep. | | [Customer Segments](/nerve-centre/kpi-cards/adobe-commerce/customer-spend-segments) | Per-cohort AOV. New customers vs repeat have different AOV; mix shifts surface here. | | [Top Refunded SKUs](/nerve-centre/kpi-cards/adobe-commerce/top-refunding-customers) | If a high-AOV SKU is being refunded heavily, gross AOV looks healthy but net is contracting. | | [`shopify.aov`](/nerve-centre/kpi-cards/shopify/average-order-value) | Cross-platform peer for agency benchmark. | ## Reconciling against the vendor's own dashboard **Where to look in Adobe Commerce Admin:** > **Reports > Sales > Orders** with the date range set to "Last 30 days". The "Average" column shows AOV for the period. Adobe also displays AOV on the **Dashboard > Lifetime Average Order Value** tile, but that tile is all-time, not 30-day. For per-Customer-Group AOV (manual computation needed): > **Reports > Sales > Orders** with Customer Group filter applied (Adobe Commerce 2.4.4+). Sum the totals and divide by the order count. For per-Store-View: > Switch the scope selector at the top-left to a single Store View, then **Reports > Sales > Orders**. **Why our number may legitimately differ from Adobe Admin:** | Reason | Direction of divergence | | ---------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------- | | **Time-zone**. Admin in Store View timezone; card in UTC. 30-day window boundaries shift. | ±1 day inclusion | | **Currency**. Card uses `base_grand_total`; Admin uses Store View base currency. Multi-currency stores see FX-related differences. | Material on multi-currency mixes | | **`canceled` exclusion**. Card excludes; Admin Reports > Sales include unless filtered. | Card AOV slightly higher (cancellations skew small) | | **Sync lag**. Card uses OpenSearch sync (5-15 min); Admin live. | Negligible at 30D | **Internal identity (within Adobe Commerce):** `adobe_commerce.aov = total_revenue ÷ order_count` Component cards (these should be self-consistent, if they're not, it's a sampling or rounding issue, not real divergence): * [`adobe_commerce.total_revenue`](/nerve-centre/kpi-cards/adobe-commerce/total-revenue) * [`adobe_commerce.order_count`](/nerve-centre/kpi-cards/adobe-commerce/total-orders) **Cross-connector reconciliation (when both connectors are connected for this merchant):** These connectors view the same orders/sessions/transactions through different lenses. Numbers should agree within tracking-gap accuracy. Divergence is a data-quality signal worth investigating. * [`google_analytics.ga_aov`](/nerve-centre/kpi-cards/google-analytics/average-order-value) **Expected relationship:** GA4 AOV ≈ Adobe AOV × (1 - tracking gap). GA4 typically misses 10 to 25% of orders (ad blockers, consent rejection, tag-fire failure on slow pages). The orders missed by GA4 tend to be a representative sample, so the AOV figure should match within 2 to 5%. Material divergence (>10%) signals one of: (a) GA4 is missing high-AOV B2B orders (B2B portal customers often run private/incognito for security, blocking GA tags), in which case GA4 AOV is biased low; (b) GA4 is double-counting on multi-step checkout (purchase event firing twice), biasing high; (c) currency mismatch: GA4 reports in the property's reporting currency, Adobe in `base_grand_total`. ***
Documentation cross-reference (for agencies running multiple platforms) This metric exists with the same definition on other commerce platforms. This is **not** a reconciliation, your Adobe Commerce store doesn't have a parallel store on those platforms to compare against. These references exist purely so an agency running clients across multiple platforms can cross-link the same metric across docs. * [`shopify.aov`](/nerve-centre/kpi-cards/shopify/average-order-value) * [`bigcommerce.aov`](/nerve-centre/kpi-cards/bigcommerce/average-order-value)
## Known limitations / merchant FAQs **Why is my Adobe Commerce AOV so much higher than industry benchmarks for ecommerce?** Adobe Commerce skews toward complex use cases: B2B, multi-store, custom-attribute-driven catalogues, hospitality and industrial verticals. Industry "ecommerce AOV" benchmarks are dominated by Shopify-class pure DTC consumer brands ($60 to $120 typical). A typical Adobe Commerce store with any B2B mix runs $150 to $400 blended; pure B2B easily $500 to $2,500. Use category-and-edition-matched benchmarks (B2B distribution vs DTC fashion), not generic ecommerce benchmarks. **Adobe Commerce vs Magento Open Source: any AOV difference?** None at the calculation level; both editions use `grand_total` identically. The merchant-mix difference matters: Adobe Commerce paid edition is overwhelmingly used by larger merchants (and B2B-heavy merchants), so the average Adobe Commerce installation has higher AOV than the average Open Source installation. This is a customer-base effect, not an edition difference. **My multi-store AOV is misleading because of currency mixing, what should I do?** The card defaults to `base_grand_total` (FX-converted at order time) for cross-currency rollup. For per-currency views, configure per-Store-View variants. Don't rely on `grand_total` for multi-currency comparison; FX swings from order time to display time make the figure unreliable. **My B2B AOV is much higher than B2C, will the blended AOV always trend with B2B mix?** Yes. Blended AOV is a weighted average; the higher-AOV segment (B2B) has outsized influence. A 5pt mix shift toward B2B can move blended AOV by 30%+ even if neither segment's own AOV changed. The correct interpretation: blended AOV is a mix-mix indicator, not a quality-of-customer indicator. For quality, use per-segment AOV from [B2B AOV vs B2C AOV](/nerve-centre/kpi-cards/adobe-commerce/b2b-aov-vs-b2c-aov). **Why include `pending_payment` orders in AOV?** They are genuine pipeline; B2B net-30 specifically. Excluding them would understate AOV (since net-30 orders skew large) and create false volatility (when a batch of pending orders flips to processing, AOV would jump). Including them gives a stable cash-pipeline view. **Why is AOV gross of refunds rather than net?** Two reasons. First, refunds happen days to weeks after the order, so net-of-refund AOV is always a backward-looking moving target. Second, the act of refunding is a separate operational signal tracked in [Refund Rate](/nerve-centre/kpi-cards/adobe-commerce/refund-rate); folding it into AOV obscures both signals. For a net view, divide net Total Revenue by Order Count manually. **A flash sale ran for 3 days, AOV dropped 8%, is that a problem?** Probably not. Promotional AOV drag is expected behaviour: discounts pull `grand_total` down by definition. The diagnostic question is whether the volume lift compensated. Cross-check [Total Orders](/nerve-centre/kpi-cards/adobe-commerce/total-orders): if order count rose more than AOV fell, total revenue is up. Cross-check [Total Revenue](/nerve-centre/kpi-cards/adobe-commerce/total-revenue) directly. If revenue is up despite AOV falling, the campaign is working. **Why does AOV rise on weekends but Total Revenue falls?** Common pattern on B2B-heavy stores. Weekend orders are mostly consumer (smaller AOV would suggest revenue should drop) but B2B accounts who DO order on weekends tend to be operations-team-driven emergency orders (high AOV). The mix shift toward fewer, larger orders pushes the average up while the volume push down on revenue. The pattern is healthy mix variation, not a problem. **My multi-store Adobe Commerce, AOV varies 5x across regions, normal?** Yes. Region-level AOV differences reflect (a) tax-inclusive pricing vs exclusive (UK +20% VAT, US varies), (b) shipping fee structures, (c) regional product mix (the UK store may stock lower-priced lines), (d) currency-strength effects. A 5x variance suggests US is mostly B2B and UK is mostly consumer (or vice versa); check Store View routing and segment classification. **Should I optimise for AOV or for Total Revenue?** Total Revenue. AOV is a means, not an end. Pushing AOV by raising minimum-order-value thresholds reduces volume; the net revenue impact is what matters. The exception: when AOV is dropping and volume is flat (the bad mix-shift case), the AOV signal is the indicator that something needs fixing. *** ### Tracked live in Vortex IQ Nerve Centre *Average Order Value* is one of hundreds of KPI pulses Vortex IQ tracks across Adobe Commerce and 70+ other ecommerce connectors. Nerve Centre runs the detection layer; Vortex Mind investigates the cause when something moves; Ask Viq lets you interrogate any number in plain English. [Start for free](https://app.vortexiq.ai/login) or [book a demo](https://www.vortexiq.ai/contact-us) to see this metric running on your own data.