> ## 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. # Unique Customers, Adobe Commerce > Unique Customers 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 > Distinct customer count over the trailing 30 days, computed via `CARDINALITY(customer_email)` on the orders index. Adobe Commerce uses email as the practical customer identifier (the `customer_id` field is null for guest orders). The count therefore conflates registered customers with guests-using-the-same-email. On Adobe Commerce specifically, the card distinguishes B2B Companies (single Company can have many billing emails) from consumer accounts. | | | | ------------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **What it counts** | `CARDINALITY(customer_email)` over orders in the 30-day window. Distinct emails. Compared to prior 30-day for delta. | | **API field** | `customer_email` from `GET /rest/V1/orders`. Optionally `customer_id` for registered-only counts. | | **VAT / tax treatment** | n/a, this is a count metric. | | **Shipping inclusion** | n/a. | | **Discounts** | n/a. | | **Credit Memo refund treatment** | A customer who ordered then was fully refunded still counts. They placed an order, the count reflects intent. | | **`state` machine inclusion** | All states except `canceled` (a customer whose only order was cancelled is not really an active customer). | | **`pending_payment` quirk** | Included. B2B net-30 customers whose orders sit in `pending_payment` are real customers in pipeline. | | **Multi-currency `grand_total` vs `base_grand_total`** | n/a. | | **Store View scope (`store_id`)** | All Store Views by default. The same email across multiple Store Views counts as one customer. | | **B2B Company aggregation** | Each Company is counted as one customer when filtered to the B2B segment, even if multiple buyer emails sit under the Company. This is configurable; the default groups by Company. | | **Time window** | `30D vsP`. | | **Alert trigger** | None by default. | | **Roles** | owner, marketing | ## Calculation ``` CARDINALITY(customer_email.keyword) WHERE date BETWEEN [period_start, period_end] ``` ## Worked example A homewares brand on Adobe Commerce 2.4.6 with US, UK, and B2B Store Views. Snapshot Monday 4 May 26. **Customer count by Store View:** | Store View | Distinct emails (30D) | Distinct registered customers | Distinct B2B Companies | | --------------------- | --------------------- | ----------------------------------- | ---------------------- | | US consumer | 2,420 | 1,840 | n/a | | UK consumer | 1,910 | 1,520 | n/a | | B2B portal | 188 distinct emails | 156 customers (linked to Companies) | 142 distinct Companies | | **Blended (deduped)** | **4,396 emails** | **3,360 registered** | n/a | **Vs prior 30-day:** | Metric | Current | Prior | Delta | | --------------------- | ------- | ----- | ----- | | Total distinct emails | 4,396 | 4,180 | +5.2% | | Registered customers | 3,360 | 3,210 | +4.7% | | Guest emails | 1,036 | 970 | +6.8% | | B2B Companies | 142 | 138 | +2.9% | What this is telling marketing: 1. **Customer base grew 5.2% MoM.** Healthy. 2. **Guest growth (6.8%) is outpacing registered (4.7%).** New traffic is converting but not creating accounts. This may reflect a deliberate "guest checkout first" UX, or it may be a missed opportunity for retention (registered customers are worth 2 to 3x lifetime value of guests in most categories). 3. **B2B Company count grew slightly** (+2.9%, 4 net new Companies). Each Company is potentially worth tens of thousands per year, so 4 new Companies is a measurable acquisition win. 4. **The 188 B2B emails belong to 142 Companies**: average 1.3 buyer-emails per Company. Most Companies have one buyer; some have 2 to 5. This matters for B2B email marketing: each Company should receive one strategic-Sales-touch communication, not 1.3. 5. **Cross-checking [Customer Trend](/nerve-centre/kpi-cards/adobe-commerce/customer-acquisition-trend)**: of the 3,360 registered customers, 1,420 are first-time orderers in this period (new customers). This means 1,940 are returning, a 57.7% repeat-share among registered customers. Cross with [Repeat Customer Rate](/nerve-centre/kpi-cards/adobe-commerce/repeat-customer-rate) for the lifetime view. 6. **Strategic question**: should marketing push guest-to-registered conversion (post-purchase email cadence with account-creation incentive)? On a 1,036-guest base growing at 6.8%, converting 30% to registered would add \~310 registered customers/month, materially improving retention metrics. The point: customer count is the simplest acquisition metric, but on Adobe Commerce the registered-vs-guest split and the B2B-Company-vs-emails split add necessary nuance. ## Sibling cards merchants should reference together | Card | Why pair it with Customer Count | | ------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------- | | [New Customers](/nerve-centre/kpi-cards/adobe-commerce/new-customers) | First-time orderers, the leading-edge subset of customer count growth. | | [Customer Trend](/nerve-centre/kpi-cards/adobe-commerce/customer-acquisition-trend) | Trend chart visualising count over time. | | [Repeat Customer Rate](/nerve-centre/kpi-cards/adobe-commerce/repeat-customer-rate) | Loyalty companion. High customer count + low repeat = leaky bucket. | | [Guest vs Account Checkout](/nerve-centre/kpi-cards/adobe-commerce/guest-vs-account-orders) | Decomposes count into registered vs guest. | | [Customer Segments](/nerve-centre/kpi-cards/adobe-commerce/customer-spend-segments) | LTV-cohort decomposition. | | [B2B Revenue Share](/nerve-centre/kpi-cards/adobe-commerce/b2b-revenue-share) | The dollar-weighted view. Customer count is people-weighted; both matter. | | [Total Orders](/nerve-centre/kpi-cards/adobe-commerce/total-orders) | Order count divided by customer count = order frequency. | | [`shopify.customer_count`](/nerve-centre/kpi-cards/shopify/unique-customers) | Cross-platform peer. | ## Reconciling against the vendor's own dashboard **Where to look in Adobe Commerce Admin:** > **Customers > All Customers** lists registered customers; the grid total at the bottom shows the count. This excludes guests by definition (guests don't have customer entities). > **Reports > Customers > Customers by Number of Orders** is the closest aggregated view, ranks customers by order count. > **Sales > Orders** filtered to a date range has a "Customer Email" column; the distinct-email count is your "this card" equivalent. Group by Customer Email in CSV export to compute manually. For B2B (Adobe Commerce paid edition): > **Customers > Companies** counts Company entities. **Customers > Companies > \[Company] > Users** shows users per Company. **Why our number may legitimately differ from Admin:** | Reason | Direction of divergence | | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ----------------------------------------------- | | **Guest inclusion**. Card includes guest emails; Admin's customer list shows registered only. | Card count higher | | **Multi-Store-View deduplication**. Card dedupes the same email across Store Views. Admin's customer list often shows duplicate customer entities for the same email if the customer registered separately on each Store View. | Card count lower than admin all-Store-Views sum | | **B2B Company aggregation**. Card can group by Company; Admin counts buyer-emails. | Material if many Companies have multiple buyers | | **Time window**. Card uses 30-day-ordering activity; Admin's customer list is all-time-registered. | Card count smaller | | **Sync lag**. Card uses OpenSearch sync (5-15 min); Admin live. | Negligible at 30D | **Cross-connector reconciliation (when these connectors are connected for this merchant):** | Pair | Expected relationship | What divergence tells you | | -------------------------------------------------------------------------------- | ------------------------------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------- | | [`google_analytics.ga_purchasers`](/nerve-centre/google_analytics/ga_purchasers) | GA4 purchasers ≈ Adobe customer count × (1 - tracking gap) | GA4 typically misses 10-25%. Material lower divergence (>25%) suggests GA4 tag-fire issues at checkout. | | ESP active-list size | ESP list usually exceeds customer count (subscribers who haven't bought) | Inverse relationship would be alarming (customers buying without subscribing); sometimes legitimate (B2B where buyers don't sign up to consumer ESP). | ***
Same-metric documentation cross-reference (for agencies running multiple platforms) * [`shopify.customer_count`](/nerve-centre/kpi-cards/shopify/unique-customers) * [`bigcommerce.customer_count`](/nerve-centre/kpi-cards/bigcommerce/unique-customers)
## Known limitations / merchant FAQs **My customer count seems lower than my CRM, why?** The card counts customers who placed an order in the trailing 30 days. Your CRM probably contains all-time-registered customers, including dormant or churned. For a like-for-like, filter your CRM to "ordered in last 30 days". **Why use email rather than `customer_id` for distinct counting?** Adobe Commerce stores `customer_email` on every order regardless of guest vs registered status. `customer_id` is null for guest orders. Using `customer_email` captures both. The trade-off: a guest who later registered with the same email is counted once across both order types (correct behaviour); a guest who used different emails on different orders counts as multiple customers (overcount). **Adobe Commerce vs Magento Open Source: difference?** None at the calculation. The B2B Companies module on the paid edition lets the card group by Company; Open Source merchants without the module count by buyer-email. For Open Source merchants who want B2B Company aggregation, custom attributes can be configured but it's manual work. **My multi-store Adobe Commerce, can the same customer count differently per Store View?** Yes if they registered separately on each Store View (Adobe Commerce historically created per-Store-View customer entities; modern installations use `customer_share_account_information` to share across websites). The card dedupes by email regardless. If your historical data has duplicate registrations, the card's count is more accurate than the Admin customer-grid count. **B2B Company has 5 buyer emails, do I count it as 1 or 5?** Depends on the question. For "how many decision-making units do we serve", group by Company (count = 1). For "how many people log in and order", count by email (count = 5). The card defaults to grouping by Company on the B2B segment; configurable per the use case. **Why doesn't this card include cancelled orders?** A customer whose only order was cancelled is functionally equivalent to a customer who never ordered. Counting them inflates customer count without reflecting purchasing behaviour. The exception: Adobe Commerce auto-cancellations from `pending_payment` timeout where the customer would have been a real customer if the gateway worked. Those are excluded too, which understates "intent to be a customer" slightly. For a count-of-intent metric, see Quote-Create count via [Cart-Abandonment Spike Alert](/nerve-centre/kpi-cards/adobe-commerce/cart-abandonment-spike-alert). **My customer count grew but revenue is flat, what's happening?** Likely AOV contraction. New customers are smaller-basket than existing customers; if customer count grew faster than revenue, the new customers are buying less per visit. Cross-check [AOV](/nerve-centre/kpi-cards/adobe-commerce/average-order-value) and [New Customers](/nerve-centre/kpi-cards/adobe-commerce/new-customers). This is the "successful acquisition, weak retention" pattern that needs an early-customer cadence intervention. *** ### Tracked live in Vortex IQ Nerve Centre *Unique Customers* 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.