> ## 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. # Conversion Rate, Salesforce Commerce Cloud > Orders / sessions. Below 1.5% usually = checkout / page-speed issue, not traffic. How to read it, why it matters, and how to act on it. **Metrics type:** [Key Metrics](/nerve-centre/overview#metrics-types-explained) • **Category:** [Ecommerce Platform](/nerve-centre/connectors#connectors-by-type) > Orders / sessions. Below 1.5% usually = checkout / page-speed issue, not traffic. ## At a glance > Share of Salesforce Commerce Cloud sessions that resulted in a confirmed order in the period. Computed as `COUNT(orders) ÷ COUNT(sessions)`. The single best canary for checkout-funnel health and the first metric to check after a site release, an indexer rebuild, or a payment integration change. | | | | ----------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **What it counts** | `COUNT(distinct order_no) ÷ COUNT(distinct session_id)` per site, then aggregated. SFCC stamps each visit with a `session_id` via cookie; a returning customer who visits three times and buys once contributes 3 to the denominator and 1 to the numerator. | | **Numerator (orders)** | Confirmed orders by default. Cancelled / failed / replacement rows can be filtered out for a strict realised-cash CR. | | **Denominator (sessions)** | SFCC server-side session count where available, with a fallback to ingested SCAPI / OCAPI session-event data. Using server-side counts (not GA4) means ad-blocker / consent rejection does not deflate the CR. | | **VAT / tax treatment** | n/a, this is a ratio. | | **Shipping** | n/a, ratio metric. | | **Discounts** | n/a, ratio metric. | | **Refunds** | **NOT subtracted from the numerator.** A refunded order still counts in CR; the conversion event happened. Refund leakage is a separate dial. | | **Cancelled / voided orders** | Excluded by default for CR. The `confirmation_status = CONFIRMED` filter is the right denominator-aware view. | | **Currency** | n/a, ratio metric. | | **Channels / sources** | **Multi-site by design.** Each `siteId` has its own CR. Realm-wide CR is a traffic-weighted average of every site, dominated by the highest-traffic site. Per-site is the right operational read. | | **B2B portals** | Counted with the same definition. B2B CR runs 5 to 25% because trade portals are mostly logged-in account holders with purchase intent; this skews the realm-wide CR upward when B2B traffic is meaningful. | | **Time window** | `30D vsP` (default 30 days vs prior 30 days) | | **Alert trigger** | `<1.5%` (DTC default), driven by `sentiment_key: conversion_rate_trend`. Raise to `<3%` for B2B-dominated sites and lower to `<1%` for content-heavy / awareness-stage sites. | | **Roles** | owner, marketing | ## Calculation Calculated automatically from your Salesforce Commerce Cloud 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 Fortune-500 fashion retailer running on Salesforce Commerce Cloud, multi-site realm. Window covers 14 Mar 26 to 12 Apr 26. | `siteId` | Site | Sessions | Orders | CR | vs prior 30D | | --------------------------------- | ------------------ | -------------- | ----------- | --------- | ------------------- | | `RefArch-US` | US DTC | 8,420,000 | 184,200 | 2.19% | 2.34% (down 0.15pp) | | `RefArch-UK` | UK DTC | 2,840,000 | 62,400 | 2.20% | 2.18% (flat) | | `RefArch-DE` | DE DTC | 2,210,000 | 41,800 | 1.89% | 1.94% (down 0.05pp) | | `RefArch-JP` | JP DTC | 1,980,000 | 28,600 | 1.44% | 1.48% (down 0.04pp) | | `RefArch-B2B` | B2B trade portal | 18,400 | 1,420 | 7.72% | 7.41% (up 0.31pp) | | `Headless-Subbrand` | Sub-brand on SCAPI | 1,420,000 | 12,800 | 0.90% | 0.84% (up 0.06pp) | | **Realm-wide (traffic-weighted)** | | **16,888,400** | **331,220** | **1.96%** | **2.06%** | What's interesting: 1. **The realm-wide CR is 1.96%, above the `<1.5%` alert threshold.** The card stays quiet. But the real story is in the per-site spread: US is down 0.15pp, JP sits at 1.44% (below threshold for any DTC view), and the headless sub-brand sits at 0.90% (well below). **Read CR per-site on SFCC realms.** 2. **The headless sub-brand on SCAPI runs structurally lower CR (0.90%).** Three usual reasons: (a) it is a newer site with marketing programs still maturing, (b) the React PWA checkout has fewer cross-sell / trust signals than ISML, (c) some session events from the headless front-end are lost to ad-blockers (server-side counts close most of this gap, but not all). Pair with [Total Orders](/nerve-centre/kpi-cards/salesforce-commerce-cloud/total-orders), the sub-brand's order count is up 5.6% on the prior period; CR rose 0.06pp despite the structural drag. The trend is healthy. 3. **B2B portal CR is 7.72%, 4× DTC.** This is normal, trade portals filter top-of-funnel browsing because nearly all visitors are logged-in account holders. The `<1.5%` alert default would never fire on a B2B site; raise the threshold to `<3%` or `<5%` for the B2B panel. 4. **JP CR sits at 1.44%, below the `<1.5%` alert threshold.** Common pattern on multi-locale realms: non-home markets have less localised pricing, less local payment-method coverage (no Konbini / no Bank Transfer), and slower CDN performance from the home region. Use [Conversion Rate by Market](/nerve-centre/kpi-cards/salesforce-commerce-cloud/conversion-rate) (when added) to confirm this is a localisation issue rather than a checkout outage. JP customers in apparel typically convert lower than US customers across all platforms; this is structural, not a bug. 5. **The 0.10pp realm-wide CR drop is the kind of move worth investigating proactively.** No site triggered the alert individually; the realm-wide drop is below threshold; but the trend is consistently down across US, DE, and JP. Pair with checkout-error rates (BM Reports & Dashboards → Errors) and the PSP's authorisation rates to rule out a payment integration regression. ## Sibling cards merchants should reference together | Card | Why pair it with Conversion Rate | | ------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | [Total Orders](/nerve-centre/kpi-cards/salesforce-commerce-cloud/total-orders) | The numerator. CR moves are only meaningful in the context of total order volume. CR down + orders up = traffic-led growth, healthy. CR down + orders down = funnel problem. | | [Total Revenue](/nerve-centre/kpi-cards/salesforce-commerce-cloud/total-revenue) | The other half. Revenue can hold or rise even with CR drops if AOV moved. | | [Average Order Value](/nerve-centre/kpi-cards/salesforce-commerce-cloud/average-order-value) | Trades off with CR. Free-shipping thresholds raise AOV but slightly lower CR; the right balance is whichever moves total revenue. | | [Top Products](/nerve-centre/kpi-cards/salesforce-commerce-cloud/top-products-by-revenue) | A CR drop concentrated on a specific category often points to a single broken PDP, removed price, or stale recommendation panel. | | [Out-of-Stock Products](/nerve-centre/kpi-cards/salesforce-commerce-cloud/out-of-stock-products) | OOS spikes drop CR cleanly. A 5% CR drop with a 12% OOS share is usually the same story. | | [Refund Rate](/nerve-centre/kpi-cards/salesforce-commerce-cloud/refund-rate) | The downstream view. A CR rise driven by aggressive promotion often shows up as a refund-rate rise 14 to 30 days later. | | [`adobe_commerce.conversion_rate`](/nerve-centre/adobe_commerce/conversion_rate) | Closest enterprise-tier peer, documentation cross-link only. | | [`google_analytics.ga_conversion_rate`](/nerve-centre/kpi-cards/google-analytics/conversion-rate) | The browser-side view, useful for understanding traffic-source quality even when SFCC server-side CR is the truth. | ## Reconciling against the vendor's own dashboard **Where to look in Business Manager:** SFCC's admin tool is **Business Manager** at `https://.business.demandware.net`. The closest like-for-like view is **Merchant Tools, Site, Reports & Dashboards, Conversions** for any single site. Set the same date range, ensure the site filter matches Vortex IQ's per-site selection, and read the **Conversion Rate** column. The cross-site rollup view is **Reports & Dashboards, Site Performance** which weights each site by sessions; the realm-wide CR there should match this card's realm-wide read within timezone rounding. Other Business Manager views that *look* like the same number but aren't: * **Reports & Dashboards, Sales (per-site)**: shows order count, not CR. * **Einstein Recommendations dashboard**: CR attributed to recommendation impressions only, narrower than this card. * **Marketing Cloud Personalisation (formerly Evergage / Interaction Studio)**: CR within a personalisation segment, not site-wide. **Why our number may legitimately differ from Business Manager:** | Reason | Direction | Why | | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------ | ----------------------------------------------------------------------------------------------------- | | **Session counting**. BM uses SFCC's server-side `session_id`. Vortex IQ uses the same source where available. | Should match closely | Largest gaps come from custom session-handling cartridges that override the default cookie behaviour. | | **Time-zone**. BM uses the site's configured time zone; Vortex IQ runs on UTC. | Boundary days off | Averages out for 30-day windows. | | **Order-status filter**. BM may filter to `COMPLETED` only; Vortex IQ uses `confirmation_status = CONFIRMED` by default which includes `OPEN` orders awaiting fulfilment. | Vortex IQ slightly higher | Set BM to "All confirmed" to match. | | **Bot / scraper sessions**. BM has bot filters; Vortex IQ relies on SFCC's upstream bot exclusion. | Either, drift is small | Spikes during scraper attacks can deflate CR until SFCC's WAF blocks the source. | | **B2B logged-in sessions**. Some BM views exclude B2B trade-portal sessions from the headline; Vortex IQ includes every `siteId`. | Vortex IQ higher when B2B is present | Filter to DTC sites only. | | **Page-impression filtering**. Some BM reports count only sessions that hit a "purchasable" page (PDP, cart, checkout); Vortex IQ counts every session. | Vortex IQ slightly lower | This narrows the denominator and raises BM's CR; not always desirable. | **Internal identity (within SFCC):** `sfcc.conversion_rate = sfcc.total_orders ÷ sfcc.total_sessions` (per-site) If realm-wide CR doesn't equal `sum(orders) ÷ sum(sessions)` across sites, you're looking at a per-site averaged CR, not a traffic-weighted realm CR. Vortex IQ uses the traffic-weighted version. **Cross-connector reconciliation:** | Card | Expected relationship | What causes legitimate divergence | | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | [`google_analytics.ga_conversion_rate`](/nerve-centre/kpi-cards/google-analytics/conversion-rate) | GA4 CR ≈ SFCC CR × (1 − tracking gap), GA4 typically 10 to 25% lower | GA4 misses 10 to 25% of orders due to ad-blockers and consent rejection, AND misses some sessions. The ratio of the two losses determines whether GA4 CR runs higher or lower than SFCC. **Treat SFCC as the source of truth for CR.** | | [`google_analytics.ga_total_transactions`](/nerve-centre/google_analytics/ga_total_transactions) ÷ [`google_analytics.ga_total_sessions`](/nerve-centre/google_analytics/ga_total_sessions) | Should approximate `sfcc_total_orders ÷ sfcc_total_sessions` | Both sides have measurement gaps, but SFCC's are smaller. Use GA4 for traffic-source decomposition, SFCC for the headline. | A persistent gap > 30% between SFCC CR and GA4 CR usually means GA4's UTM hygiene is poor or the tag-manager configuration is outdated. The fix is on the analytics side, not the SFCC side. ***
Same-metric documentation cross-reference (for agencies running multiple platforms) The same Conversion Rate definition lives on every commerce platform. This is **not a reconciliation**, your SFCC realm doesn't have a parallel store on another platform to compare against. Cross-links are for agency navigation only. * [`adobe_commerce.conversion_rate`](/nerve-centre/adobe_commerce/conversion_rate), closest enterprise-tier peer * [`shopify.ecommerce_conversion_rate`](/nerve-centre/shopify/ecommerce_conversion_rate) * [`bigcommerce.conversion_rate`](/nerve-centre/bigcommerce/conversion_rate)
## Known limitations / merchant FAQs **Why is my realm-wide CR misleading? Should I read it per-site?** Yes, almost always. SFCC realms typically host sites with very different traffic mixes (paid social-heavy DTC US, SEO-driven UK, trade-only B2B portal, headless sub-brand). Each has structurally different conversion behaviour. The realm CR is a weighted average of those, dominated by the highest-traffic site, and often hides material problems on smaller sites. Pin per-site CR panels for any operational read. **My CR dropped to 1.2% but traffic is up 30%. Should I be worried?** Almost always no. The relationship between CR and traffic volume is inverse on most acquisition campaigns: a wave of top-of-funnel paid traffic (broad social audiences, generic Google searches) brings lower-intent visitors who convert at half the rate of organic and direct visitors. The right question is whether *total orders* moved, not whether CR moved. Pair this card with [Total Orders](/nerve-centre/kpi-cards/salesforce-commerce-cloud/total-orders). If orders rose more than CR fell in proportion, the campaign worked. **My headless storefront shows CR of 0.8%, my ISML site shows 2.4%. Is the headless build broken?** Probably not, but worth investigating. Three usual reasons. (1) **Tracking gap.** Headless React storefronts often lose 10 to 20% of GA4 / Adobe Analytics events to ad-blockers and consent failures; the order count reaching SFCC is correct but the session denominator is undercounted on the analytics side. The card uses SFCC server-side session counts where available, which closes most of this gap. (2) **Audience.** Headless sub-brand sites often run with smaller, more fragmented marketing programs producing less qualified traffic. (3) **Checkout maturity.** New headless checkouts ship with fewer cross-sell, recovery, and trust signals; SFCC ISML sites have been tuned for years. **Does the card count B2B portal sessions and orders?** Yes if the B2B portal is configured as a `siteId` on the realm. B2B CR is typically higher than DTC (5 to 25%) because trade portals filter out top-of-funnel browsing; visitors are nearly all logged-in account holders with purchase intent. This pulls realm-wide CR up if B2B traffic is meaningful, another reason to read per-site. **My CR dropped overnight from 2.1% to 1.4% with no campaign change. What broke?** Three usual canaries to check, in order. (1) **Checkout error rate.** Open BM Reports & Dashboards → Errors and look for a spike on `Checkout-Submit` failures. A failed payment integration, expired API certificate, or PSP outage will surface there. (2) **Add-to-cart rate.** If ATC dropped, the issue is upstream (broken PDP page, removed price, a hero image failing to render). (3) **Site-search results.** If site-search return rate dropped, an indexer ran badly and customers cannot find products. SFCC's ConfigZero / Einstein search indexes update overnight; a bad index sinks CR cleanly. **Are sessions or visitors used as the denominator?** Sessions. SFCC stamps each visit with a `session_id`; this card divides confirmed orders by distinct sessions in the window. A returning customer who visits three times and buys once contributes 3 to the denominator and 1 to the numerator. If you want a per-visitor view (single denominator increment per unique customer), that is a different card. **The Salesforce account team's CR number is different. Why?** Salesforce's account-team reports often pull from Marketing Cloud Personalisation (formerly Evergage / Interaction Studio) or Einstein Recommendations, which can use different denominators (page views, recommendation impressions, personalisation segments). They are also commonly looking at one site only. Compare like-for-like: same site, same date range, sessions denominator. **What is a "good" CR on SFCC?** Highly variable by industry, traffic mix, and AOV. Useful benchmarks. (1) **DTC apparel** typically 1.5 to 2.5%. (2) **B2B trade portals** typically 5 to 25% (logged-in account holders convert at much higher rates). (3) **Multi-locale international DTC** typically 1.0 to 2.0% (the card pools locales by default; non-localised pricing depresses CR in non-home markets). The `<1.5%` alert threshold is a reasonable DTC default; raise it for B2B sites and lower it for content-heavy or top-of-funnel sites. *** ### Tracked live in Vortex IQ Nerve Centre *Conversion Rate* is one of hundreds of KPI pulses Vortex IQ tracks across Salesforce Commerce Cloud 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.