At a glance
Top SKUs ranked by revenue (dollar value) over 30 days. The dollar leaderboard, the SKUs that contribute the most revenue regardless of unit count. The finance and merchandising teams’ primary view; pair with BC Top SKUs for the unit-volume ranking.
| What it counts | SUM(line_item.total_inc_tax) GROUP BY product_id over 30 days. Revenue per product, ranked descending. |
| VAT / tax treatment | Tax-inclusive (total_inc_tax). |
| Shipping | Excluded at line-item level. |
| Discounts | Already deducted (post-discount line revenue). |
| Refunds | Not deducted (gross). |
| Cancelled / voided orders | Included in gross. |
| Currency | Multi-currency without FX. Filter by currency for clean comparison. |
| Channels / sources | All channels contribute. Same channel-mapping considerations as BC Top SKUs. |
| Variants vs products | Default product-level. Toggle to variant-level for size/colour-specific rankings. |
| B2B Edition note | B2B portal orders inflate revenue rankings (case quantities × case prices). For retail-relevant rankings, filter to retail channel. |
| Hero SKU recognition | Top 5 SKUs typically drive 25-40% of revenue on focused-catalogue stores; 15-25% on broad-catalogue stores. |
| Time window | 30D (rolling 30 days, vs prior 30 day comparison) |
| Alert trigger | None on this card directly. |
| Roles | owner, marketing |
Calculation
Calculated automatically from your BigCommerce data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
A US homewares brand on BigCommerce Pro, 30-day window 14 Apr 26 to 14 May 26.| Rank | SKU | Product | Revenue | Units sold | AOV per unit | Margin band |
|---|---|---|---|---|---|---|
| 1 | LIN-DUV | ”Linen duvet” | $96,400 | 482 | $200 | High margin |
| 2 | TWL-6PK-IVR | ”Bath towel set 6pk, ivory” | $43,200 | 720 | $60 | Mid margin |
| 3 | MUG-CRM-04 | ”Cream mug, set of 4” | $36,800 | 1,840 | $20 | Low margin (volume hero) |
| 4 | SOFA-LNS-3ST | ”Linen sofa, 3-seat” | $36,000 | 18 | $2,000 | High margin (premium) |
| 5 | LMP-CRMC | ”Ceramic table lamp” | $34,200 | 380 | $90 | Mid margin |
| 6-10 | (5 mid-tier) | (mixed) | $114,000 | mixed | mixed | mixed |
| 11-50 | (40 SKUs) | (mixed) | $182,400 | mixed | mixed | mixed |
| Top 50 total | $543,000 | 73% of catalogue revenue |
- **The linen duvet at 200/unit) with substantial units (482) makes it the single biggest SKU. Protect it: ensure inventory, photography, SEO, ad placement all support it. OOS on this SKU = $3,200/day of lost revenue.
- Top 5 = 47% of revenue. Concentration risk: any of these going OOS, getting refund-spiked, or losing search ranking is a meaningful revenue event. Cross-reference BC Stock vs Sales for top-5 stock days remaining; cross-reference BC Refunded Products for refund-rate health.
- The premium sofa at 2,000 AOV is the high-margin hero. Low velocity but each unit contributes massively to revenue and (typically) margin. The merchandising priority for this SKU is qualitative (premium photography, story-driven product page, white-glove delivery option) not volume-driven.
- The mug set at #3 by revenue but #1 by units is the volume vs revenue trade-off. High velocity at low AOV. Operational focus on this SKU; merchandising / margin focus on the duvet and sofa.
- Top 50 = 73% of revenue. Rest of the catalogue (200+ SKUs) accounts for 27%. Cull-and-focus is usually the right move: reduce SKU count below the top 100, free up working capital and merchandising attention.
- Cross-reference with BC Top SKUs: the unit-vs-revenue ranking comparison reveals catalogue diversity. A store where top units = top revenue is concentrated; a store with two distinct lists (volume heroes ≠ revenue heroes) has good catalogue diversification.
- Verify days-of-stock for top-10 by revenue today.
- Cross-check top-10 against BC Refunded Products any high-revenue / high-refund SKU is the urgent fix.
- Allocate ad budget proportional to revenue rank for top-50 SKUs.
- Premium-SKU merchandising review ranks 4 (sofa) and similar high-AOV items deserve photography / story upgrades.
- Quarterly: cull SKUs below rank 100 with no strategic role to simplify catalogue and free working capital.
Sibling cards merchants should reference together
| Card | Why pair it with Top SKUs Revenue |
|---|---|
| BC Top SKUs | The unit-volume ranking; together they reveal catalogue concentration patterns. |
| BC Stock vs Sales | Top-revenue SKUs going OOS is the highest-leverage problem. |
| BC Refunded Products | Top-revenue + top-refund = urgent fix. |
| BC Product Margin | Revenue without margin context misleads; pair for profit-aware ranking. |
| BC Margin by Brand | Brand-level margin overlay on top-revenue SKUs. |
| BC Revenue by Brand | Top SKUs grouped by brand; brand concentration in top revenue. |
| BC Revenue by Category | Top SKUs grouped by category. |
shopify.top_products | Cross-platform reference. |
Reconciling against the vendor’s own dashboard
Where to look in BigCommerce Control Panel: Analytics → Reports → Best Selling Products ranks by revenue when you toggle the metric. Analytics → Sales by Product gives a similar view. Both should match this card within ±2-3%. Why our number may legitimately differ from BC:| Reason | Direction |
|---|---|
| Shipping inclusion. We exclude shipping at line-item level; BC’s product-revenue report may include pro-rated shipping per product. | Vortex IQ LOWER |
| Refund netting. BC may net out refunded revenue; we don’t. | BC LOWER if netted |
| Variant rollup. Both default to product-level; toggle to variant for granular view. | Match closely at default |
| Multi-currency. We don’t FX; BC may. | Different totals |
| Time-zone. BC uses store time zone; we use UTC. | Boundary differences |
| Channel coverage. We include all channels; BC reports may default to web only. | Vortex IQ HIGHER for multi-channel stores |
| Card | Expected relationship | What causes legitimate divergence |
|---|---|---|
google_ads.ga_top_skus_paid | Paid-traffic top SKUs by revenue overlap with this card. | Ads attribution windows. |
google_analytics.ga_top_items_revenue | GA4’s item_revenue ranking matches within ±15%. | GA4 misses 10-25%. |
amazon_sp.amazon_top_asins_revenue | Amazon-channel slice should match Amazon SP-API. | Amazon’s revenue is settlement; this card is gross order revenue. |
Known limitations / merchant FAQs
Why is my top SKU different by units vs by revenue? Different metrics surface different leaders. High-volume low-price SKUs win unit ranking; low-volume high-price SKUs win revenue ranking. Both views matter: units for warehouse / replenishment / packing capacity, revenue for finance / margin / ad allocation. Healthy catalogues have distinct lists. Should I optimise photography for top-revenue or top-units SKUs? Revenue. The dollar contribution is what justifies the investment. Top revenue SKUs deserve premium photography (3-5 angles, contextual lifestyle shots, close-up details, video). Top-unit SKUs benefit from clear functional photography but rarely need the premium treatment. A premium SKU at #1 by revenue with 18 units, is that healthy? Yes for premium / B2B-style merchants. Low-velocity high-AOV SKUs are real revenue contributors; the stability of the contribution depends on how repeatable it is. If the 18 units came from 18 distinct customers, healthy; if from 2 customers buying 9 each, concentrated and vulnerable. Why did my #1 by revenue drop sharply this period? Common causes: (1) OOS (no orders to count); (2) price cut due to promotion (revenue per unit dropped); (3) seasonal pull-back; (4) competitor price-undercut. Cross-reference BC Stock vs Sales and recent pricing changes. Should I cut SKUs below rank 100 by revenue? Generally yes, with strategic exceptions. Rank-100 SKU with $200/month revenue costs more in catalogue overhead than it generates. Cut unless: (a) gateway product (acquires customers who upgrade); (b) seasonal SKU with predictable pull; (c) part of a bundle where it adds value at the bundle level. My BC’s Sales by Product report shows different totals, why? Common reasons: shipping inclusion, refund netting, variant rollup choice, time-zone, channel coverage. See reconcile section. Both views should agree to within ±5%; larger gaps signal a configuration mismatch. Why are my marketplace SKUs at the bottom of the revenue ranking when Amazon Seller Central shows them as top? Two possible causes: (1) you’re looking at all-channel revenue here while Amazon Central shows Amazon-only, marketplace SKUs are big on Amazon but small as a portion of total store revenue; (2) Channel Manager mapping is misconfigured (revenue attributing to the wrong BC product). Audit Channel Manager mapping. Top SKUs by revenue concentration is too high (top-5 = 60%), is that risky? Yes. Concentration above 50% in top-5 makes the store fragile to single-SKU events (OOS, refund spike, supplier issue, ad-platform algorithm change). Action: invest in the next 5 SKUs (ranks 6-10) to broaden the base. Aim for top-5 < 40% within 12 months. Variant-level view: my top-revenue variant is the King size; is that surprising? Not really. King-size linens, large-size apparel, premium-tier electronics typically rank above their smaller counterparts in revenue (higher per-unit price). Stocking strategy should reflect this: prioritise King size availability over Twin / Single. Should I show top SKUs to my supplier in negotiations? Yes. Showing a supplier “this SKU drives $96k/month for us” is leverage for better terms (volume rebates, exclusive variants, faster restocks). Suppliers respond to data; this card is the easiest exhibit to share. My B2B revenue dominates this view, can I see retail-only? Yes. Filter to retail customer group or to web channel (channel_id = 1). The retail-only view is often very different from all-channel; B2B inflates AOV and skews toward bulk-friendly SKUs.
Why doesn’t this card show profit?
COGS data is required for profit; BC doesn’t store it natively for most products. Use BC Product Margin for margin-aware ranking via Vortex Mind’s COGS overlay. A high-revenue low-margin SKU may contribute less profit than a mid-revenue high-margin one; revenue-only ranking can mislead profit-allocation decisions.