At a glance
Amazon revenue as a percentage of total commerce revenue (Amazon + connected DTC connectors), trailing 90 days. The headline answers “what share of the brand depends on Amazon?” with a concentration alert at 70%, the threshold above which Amazon-side disruption (Buy Box loss, account-health flags, suppression cascade) becomes existential.
| What it counts | amazon.total_revenue ÷ (amazon.total_revenue + sum_of_DTC_total_revenue), trailing 90 days, in unified settlement currency. DTC connectors include Shopify, BigCommerce, and Adobe Commerce when connected. |
| API endpoint + report | SP-API Orders API for Amazon side (gross OrderTotal.Amount), plus the connected DTC connectors’ Total Revenue for the denominator. Computed in our Vortex IQ Nerve Centre cross-channel index. |
| ASIN vs account scope | Account-level only. This is a strategic concentration KPI, not a per-ASIN view. |
| Buy Box impact | Indirect but profound. The higher the Amazon dependency, the more Buy Box state matters to brand survival. A 90% Amazon-dependent brand losing Buy Box across 5 ASINs faces revenue collapse; a 30% Amazon-dependent brand absorbs the same event with limited operational pain. |
| FBA vs FBM | Both contribute to the Amazon side; not separated in the headline. Drill down to Order Count split by FulfillmentChannel for the FBA/FBM mix. |
| Fees / commission | Gross. The card uses Amazon’s pre-fee revenue against DTC’s pre-payment-processor revenue for like-for-like comparison. Net-of-fees comparison would shift the headline by 3 to 5 percentage points (Amazon’s fees are higher than DTC payment processor fees), but the strategic interpretation is the same. |
| Refunds | NOT deducted on either side. Both sides are gross to keep the comparison clean. |
| Cancellations | Included on both sides where indexed. |
| Currency | Settlement currency, with FX conversion applied to all DTC-side currencies if multi-currency selling is enabled. |
| Marketplace dynamics | Single-marketplace dependency (e.g. amazon.com only) is more concentrated than the headline suggests; even within Amazon, a single marketplace going At Risk collapses revenue. Drill into per-marketplace mix when total Amazon dependency is high. |
| Return-window vs refund-window | Not applicable. |
| Time window | 90D (trailing, smooth enough to ignore week-to-week noise; long enough to reflect strategic mix shifts). |
| Alert trigger | Amazon dependency >70%, the threshold above which Amazon disruption becomes a brand-survival risk. |
| Roles | owner, finance. |
Calculation
Calculated automatically from your Amazon (Selling Partner) 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 Amazon-first DTC supplements brand. Trailing 90 days, 02 Feb 26 to 02 May 26. Connectors: Amazon SP-API + Shopify.| Channel | Trailing 90D revenue (gross) | Share | Trend vs prior 90D |
|---|---|---|---|
| Amazon (amazon.com) | $2,140,000 | 86.0% | +12% |
| Shopify (DTC) | $348,000 | 14.0% | +3% |
| Total commerce | $2,488,000 | 100% | +10.6% |
- Buy Box loss = sales loss, instantly, and at 86% dependency it’s an existential threat. A simulation: if 5 of the brand’s top ASINs lose Buy Box for 30 days (a realistic worst case during a reseller war or post-OOS recovery), the brand loses roughly 35% of Amazon revenue, equating to a 30% drop in TOTAL commerce revenue across that window. The DTC channel can’t cushion the fall; it’s too small. The brand needs to either grow DTC to 30%+ or accept the concentration risk and run a tighter Amazon operational playbook.
- Commission erodes 12 to 15% of headline, and the brand has limited leverage at 86% dependency. Amazon-first brands can’t push back on Amazon fee changes; they have nowhere to go. Brands at 30 to 50% Amazon dependency can afford to deprioritise Amazon when fees rise; brands at 86% can’t. This is the strategic cost of concentration that the card surfaces.
- Amazon-first buyers don’t migrate to your DTC site. The brand has tried twice in the last year to push Shopify campaigns to Amazon-buyer email lists (scraped from “Request a Review” replies). Click-through both times: 2 to 3%; conversion 0.2 to 0.4%. The buyer cohorts are separate. Growing DTC requires acquiring DTC-native buyers (Meta ads, influencer, organic SEO), not converting Amazon shoppers. This is a structural insight that should inform the diversification plan.
- Out-of-stock punishes you for weeks, and concentrated dependency amplifies the cost. A two-week FBA stockout on a top SKU costs an Amazon-only brand the entire SKU’s revenue plus 14 to 28 days of organic-rank recovery. At 86% dependency, that single SKU’s loss can move the brand’s monthly P&L by 5 to 10%. Lower-dependency brands absorb the same event more comfortably.
- Amazon doesn’t share customer data, which limits diversification options. Amazon does not give sellers customer email addresses or contact info. A brand at 86% dependency has 86% of its customers in a list it cannot directly market to. Diversification efforts have to start from a near-zero CRM, which is why DTC growth from a high-Amazon baseline is structurally slow. Plan for 18 to 36 months to materially shift the mix; faster shifts usually mean acquisition-channel spending that erodes margin.
Sibling cards merchants should reference together
This is the strategic concentration KPI. Pair with these to size diversification options:| Card | Why pair it with Channel Mix (Amazon vs DTC) |
|---|---|
| Total Revenue | The Amazon side of the ratio. |
| Net Revenue | Net-of-fees view; some brands prefer this for like-for-like with DTC. |
| Account Health Status | The single biggest risk to a high-dependency brand. Watch alongside this card daily. |
| Buy Box Trend | Buy Box loss disproportionately damages high-dependency brands. |
| Revenue at Risk (live) | Operational risk size. At >70% dependency, a £10k/month at-risk reading is a ~3% hit to total commerce. |
| Shopify Total Revenue | The DTC denominator side. Growing this is the primary diversification lever. |
| BigCommerce Total Revenue | Same role for BC stores. |
| Amazon Ads ACOS | High-dependency brands typically over-spend on Amazon Ads to defend share; watch ACOS for diminishing returns. |
Reconciling against the vendor’s own dashboard
Where to look in Amazon Seller Central: Amazon does not publish a “share of total commerce revenue” view (Amazon doesn’t know about your DTC channels). Closest reconcilable views:- Reports → Business Reports → Sales and Traffic by Date for the Amazon side of the ratio. Use the Ordered Product Sales column over the same 90-day window.
- Reports → Payments → All Statements for settled (post-fee) Amazon revenue, useful when reconciling against a DTC connector’s net-of-payment-processor revenue for like-for-like.
- Cross-reference your DTC platform’s revenue dashboard for the same 90-day window to compute the ratio manually.
| Reason | Direction | Why |
|---|---|---|
| Time zone | Boundary days only | Amazon Business Reports run in Pacific Time; DTC connectors run in shop timezone; this card uses UTC. The 90-day window is long enough that boundary-day effects average out, but a manual rebuild can boundary-shift by 7 to 8 hours. |
| Settlement-period lag | Either | If you reconcile against Amazon’s Payments / Settlement view (post-fee) and your DTC against gross revenue, you’ll get a different ratio than this card (which compares gross-to-gross). Pick a consistent basis for the comparison. |
| API rate limits | Ours can lag during high-volume periods | Both SP-API and DTC connectors are throttled; the trailing 90D window is robust to small lags but bursty days near the window boundary can shift the ratio by ±1 percentage point briefly. |
| Reports API generation latency | Up to 4 hours | Velocity inputs use the most recent successful pull; today’s ratio may include up to 4 hours of stale data. |
| DTC connector coverage | Could differ | The card uses every connected DTC connector. If you have multiple Shopify stores or a BigCommerce + Shopify combo, all connected stores feed the denominator. Manually building the ratio on one DTC store will produce a higher Amazon dependency. |
| Card | Expected relationship | What causes legitimate divergence |
|---|---|---|
shopify.total_revenue | Shopify Total Revenue feeds the DTC denominator. | Different stores in different geographies aggregate together; if you want region-specific dependency, configure per-region pairing in Nerve Centre → Channel Mix Settings. |
bigcommerce.total_revenue | As above. | Same dynamic. |
amazon_ads.aads_acos | Indirect: high-dependency brands typically run higher Amazon Ads spend defending share, raising ACOS. | Cross-check on a 90D correlation between Amazon dependency and ACOS. |
stripe.stripe_total_revenue | Zero overlap by design. | Amazon orders settle through Amazon’s payment rails, never through Stripe. Stripe sees only DTC orders. So stripe ≤ DTC denominator. |
Known limitations / merchant FAQs
My dependency is 86% and the alert is firing. What do I do? You can’t move the dependency below 70% in a quarter; this is an 18 to 36 month strategic effort. Start with: (1) acknowledge the risk operationally (run a tighter Amazon ops playbook, monitor Account Health Status daily, eliminate avoidable suppressions and Buy Box losses), (2) build DTC-native acquisition (Meta + Google Ads aimed at first-time DTC buyers, not Amazon-buyer remarketing), (3) consider eBay or another marketplace as a near-term diversification (faster than DTC growth, similar margin profile), (4) set a dependency target (e.g. 60% in 24 months) and track the trajectory monthly on this card. Don’t try to “stop selling on Amazon”, that’s almost always the wrong answer; the goal is to grow other channels, not shrink Amazon. Should I reconcile gross or net of fees? The card uses gross on both sides. Net comparison is a different lens: Amazon’s ~13% blended fee is higher than DTC’s ~3% payment processor fee, so a net-net comparison shifts Amazon’s effective share down by 5 to 10 percentage points. Both views are valid; gross is the default because it answers “how much of my customer-facing brand depends on Amazon”, which is the strategic question. Net is the right view for margin and operating leverage discussions. Why doesn’t Stripe revenue feed the DTC side? Because Stripe is a payment processor, not a sales channel. The DTC sales channels (Shopify, BigCommerce, Adobe) are the source of truth; Stripe is downstream of them. Adding Stripe to the DTC denominator would double-count the same revenue. Use Stripe Total Revenue for processor reconciliation only. ACOS observations, why does the card mention them? Because high-dependency brands typically over-invest in Amazon Ads to defend market share. They run ACOS at 25 to 35% (where 15 to 20% is healthy), spending more per dollar of revenue to maintain volume in a competitive marketplace. This pattern is so consistent that an unusually low ACOS at high dependency often signals that the brand has a strong organic position, while an unusually high ACOS at high dependency signals competitive pressure. Cross-check on Amazon Ads ACOS. FBA vs FBM, do they affect the dependency calculation? No. The card uses gross Amazon revenue regardless of fulfilment channel. But high-dependency brands tend to be FBA-heavy (FBA fees are higher but Buy Box-protective), which compounds the strategic risk: not only are you dependent on Amazon for revenue, you’re also dependent on Amazon for warehousing and fulfilment. Multi-marketplace, does the card aggregate amazon.com + amazon.co.uk + amazon.de? Yes, all connected Amazon marketplaces sum into the Amazon side. If you’re 50% amazon.com and 30% amazon.de, your Amazon side is 80% of total commerce, with 50/30 mix internally. Drill down to per-marketplace if the diversification strategy needs to address marketplace-specific dependency (e.g. amazon.com is a different account from amazon.de; an account suspension hits one but not the other). Settlement timing, does this affect the ratio? On the headline, no, the 90-day window is long enough to absorb settlement timing differences. But on a “today” or “yesterday” view, Amazon’s settlement lag can make recent-period numbers look slightly low relative to DTC; the ratio understates true Amazon dependency by 1 to 2 percentage points for the most recent 14 days. Use the trailing 90D headline, not “today”. Return-window confusion, do return-window differences between Amazon and DTC affect the ratio? Slightly. Amazon’s standard 30-day return window means more refunds happen within the 90-day measurement period; DTC return windows vary (60 days, 90 days, lifetime depending on policy). On a gross basis (this card’s default), refunds don’t enter the calculation. On a net basis, Amazon’s higher in-window refund rate slightly reduces Amazon’s share of net revenue. The strategic interpretation is unchanged. Why isn’t the Shopify-Amazon channel app data the source of truth? Because the channel app is a publishing tool that pushes Shopify product data to Amazon listings; it does not measure or reconcile total commerce revenue. The SP-API gives us Amazon revenue; the Shopify Admin API gives us Shopify revenue; the card joins them. Disable the channel app entirely and the card calculation is unaffected. If you do use it, channel-app-routed Amazon orders may also appear in Shopify Total Revenue (double-counting on the DTC side), in which case filtertags = "amazon" out of Shopify revenue before reconciling. See the FAQ on Total Revenue for the full channel-app caveat.
Why does today’s number rarely change?
Because the trailing 90-day window dilutes recent days heavily. A single big day shifts the ratio by <0.5 percentage points. The card is intentionally smooth to support strategic planning; for daily Amazon-side volatility use Total Revenue directly. The ratio is meant to be checked monthly against the 70% threshold and quarterly against the diversification trajectory, not daily.