> ## 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. # Email-Attributed Revenue Share, Google Analytics 4 > Healthy DTC email programmes drive 15-25% of revenue. Below 8% means either bad list health or broken attribution, both recoverable. How to read it, why i... **Metrics type:** [Cross-Platform Metrics](/nerve-centre/overview#metrics-types-explained) • **Category:** [Analytics](/nerve-centre/connectors#connectors-by-type) > Healthy DTC email programmes drive 15-25% of revenue. Below 8% means either bad list health or broken attribution, both recoverable. ## At a glance > The percentage of GA4-measured revenue that GA4 attributes to the **Email** channel. **Healthy DTC programmes sit at 15, 25%**; below 8% means the email programme is genuinely underperforming OR the email links aren't UTM-tagged correctly. Compare against your ESP's own claim (Klaviyo, Dotdigital, Mailchimp) to triangulate which problem you have. | | | | -------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **What it counts** | `(GA4 totalRevenue WHERE sessionDefaultChannelGroup = 'Email') ÷ (GA4 totalRevenue total)` over the 30-day window, expressed as a percentage. The "share of GA4 revenue that GA4 attributes to email" rate. | | **Sample basis** | Sessions with revenue. The numerator is sessions where the channel classification is Email (driven by sessionMedium = email OR utm\_medium = email OR known-email-source matching). The denominator is total revenue. | | **Sampling threshold** | None for the 30D window. GA4 samples on date ranges >14 months or with high-cardinality dimensions; sessionDefaultChannelGroup is a 9-value dimension that never triggers sampling. | | **Bot traffic filter** | GA4's built-in IAB Tech Lab filter applied. Email-channel traffic is rarely bot-affected (bots don't open marketing emails); the filter mostly affects Direct/Referral channels. | | **Channel classification rules** | GA4's auto-classification uses: utm\_medium = `email` OR `e-mail` OR `e_mail`, OR utm\_source matching a known ESP list. **If your ESP doesn't append utm\_medium=email**, the traffic ends up in Referral or Direct, NOT Email. This is the most common cause of artificially-low email-share readings. | | **Time zone** | The GA4 property's timezone, NOT UTC. Email sends typically span timezones; revenue is bucketed in property zone. | | **Currency** | The GA4 property's reporting currency, FX-converted at event time. Email-channel revenue is in the same units as the rest of GA4 revenue. | | **Refunds** | NOT subtracted. GA4's `totalRevenue` is gross-of-refunds. | | **Tracking-gap framing** | The aggregate GA4 tracking gap (10, 25%) affects email-channel revenue equally. The **share** (this card) is robust because the gap shrinks symmetrically across channels. **The number to watch is the share, not the absolute email revenue.** | | **Time window** | `30D` (single window; no vsP comparison because email programmes have weekly cycles that smooth at 30D). | | **Alert trigger** | `<8% of GA4 revenue`. The 8% floor is the lowest healthy DTC programme reading; below it, either the programme has list-health issues OR the UTM tagging has broken. | | **Roles** | owner, marketing | ## Calculation Calculated automatically from your Google Analytics 4 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 UK skincare brand on Shopify, running Klaviyo for email. 30-day window ending 02 May 26. | Source | Email-attributed revenue | Share | Notes | | --------------------------- | ----------------------------- | ---------------------- | ----------------------------------------------- | | **GA4 (this card)** | £42,300 of £308,400 GA4 total | **13.7%** | Just below the 15, 25% healthy band | | **Klaviyo own attribution** | £71,800 (5-day last-touch) | 21.2% of Shopify total | Higher because of attribution-window difference | | **Shopify Total Revenue** | £338,500 | 100% (truth side) | All channels | Three numbered observations: 1. **GA4 says 13.7%; Klaviyo says 21.2%, both can be right.** GA4 uses *last-non-direct click* attribution within the session: only purchases where the *last attribution touchpoint* was Email get credited. Klaviyo uses *last-touch within 5 days*: any purchase within 5 days of an email open/click gets credited. The two attribution models give different numbers for the same underlying behaviour. The 7.5 pp gap is normal; **the consistency between the two over time is what matters**. 2. **The brand's email share is below the healthy floor.** 13.7% in GA4 means email is contributing less than peer DTC brands. Three diagnoses: (a) **list health**: open rates declining, list growing slowly, lots of inactive subscribers. Check Klaviyo's [Email Opens Trend](/nerve-centre/klaviyo/klv_email_opens). (b) **UTM tagging gap**: some campaigns may not append utm\_medium=email correctly (Klaviyo Flows often don't UTM-tag by default), driving traffic into Direct/Referral instead of Email. (c) **Programme cadence**: too few sends, or sending at suboptimal times. The fix is programme-side; this card is the detector. 3. **The gap between GA4 and Klaviyo is stable at \~7 pp, that's the test.** If next month GA4 shows 13% but Klaviyo claims 30%, something diverged. Either Klaviyo's attribution window expanded, OR (more commonly) UTM tagging broke and email traffic disappeared from GA4's Email channel. **The test of attribution health is not the absolute numbers; it's the stability of the gap.** 4. **What WOULD trip the \<8% alert?** A common scenario: a marketing-team migration to a new ESP that ships templates without utm parameters by default. Suddenly GA4 Email channel revenue drops to 4%, but total revenue is unchanged because the same customers still bought, they just appear in Direct or Referral now. The alert fires; the fix is to update the ESP's UTM defaults. Within 7 days the share returns to 15%+. 5. **Server-side tagging doesn't change this card.** Server-side tagging recovers *purchase-event* loss; it doesn't affect *channel attribution* (which depends on URL parameters, not on event firing). A merchant with perfect server-side tagging can still have a broken email-share reading. **Rule of thumb.** Stable share in 15, 25% range = healthy email programme. Below 8% = either bad UTM tagging OR underperforming programme; check Klaviyo (or ESP) for diagnosis. Above 30% sustained = either email is doing exceptionally well OR your other channels are broken (paid, organic, social) and email is becoming a larger share by elimination. ## Sibling cards merchants should reference together | Card | Why pair it with Email-Attributed Revenue Share | | ----------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | [GA4 Revenue by Channel](/nerve-centre/kpi-cards/google-analytics/revenue-by-channel) | The full channel breakdown; Email is one row. Compare Email's share against Direct, Organic, Paid Search to see relative health. | | [GA4 Source/Medium](/nerve-centre/kpi-cards/google-analytics/source-medium) | The granular detail: which source/medium pairs are classified as Email and which fall into Referral/Direct. Use to spot UTM-tagging issues. | | [GA4 Sessions by Channel](/nerve-centre/kpi-cards/google-analytics/sessions-by-channel) | The volume side. Email share of sessions vs share of revenue tells you Email's relative conversion strength. | | [Klaviyo Email-Attributed Revenue](/nerve-centre/kpi-cards/klaviyo/email-attributed-revenue) | The truth side of email attribution from the ESP. The two should track together with a stable gap. | | [Klaviyo Email Opens](/nerve-centre/klaviyo/klv_email_opens) | The funnel-top metric. Email share dropping AND opens dropping = list-health issue, not attribution. | | [Klaviyo Email Clicks](/nerve-centre/klaviyo/klv_email_clicks) | The intermediate funnel step. Opens healthy + clicks down = creative or offer fatigue; both healthy + GA4 share down = UTM tagging issue. | | [GA4 Property Health](/nerve-centre/kpi-cards/google-analytics/ga4-property-health) | When this card and Property Health both alert, the email-share drop is part of a wider GA4 measurement regression, not an email-specific issue. | | [Cross-platform: Traffic to Revenue Divergence](/nerve-centre/kpi-cards/google-analytics/traffic-to-revenue-divergence) | If the GA4 ↔ commerce gap is widening at the same time email share drops, the two are related: a tag regression hits all channels, but Email's UTM dependency makes it most visible. | ## Reconciling against the vendor's own dashboard **Where to look in GA4:** [Reports → Acquisition → Traffic acquisition](https://analytics.google.com/) and filter the channel column to "Email". The "Total revenue" column for the Email row, divided by the report total, is this card's number. > **Reports → Acquisition → Traffic acquisition → Default channel group = "Email"** for the headline. > > **Explorations → Free form → dimension: Session source/medium, metric: Total revenue, filter: medium = email** for the granular view of which campaigns are firing. Other GA4 views that *look* like email attribution but aren't: * **Reports → Advertising → All channels**: GA4's data-driven attribution model assigns *fractional* credit to multiple touchpoints. The "Email" row in this report can be lower than the Traffic acquisition view because GA4 has redistributed credit to upstream touches. * **User acquisition (vs Traffic acquisition)**: User acquisition shows *first* touch source/medium per user. A user whose first GA4 session was Direct but whose 4th was Email-driven would not appear in user-acquisition Email even though their purchase did. * **Realtime → Traffic source**: 30-min lookback only. **Why our number may legitimately differ from GA4 itself (rare):** | Reason | Direction of divergence | | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------- | | **Channel classification updates**. GA4 occasionally updates its default channel group rules (most recent: late-2024 reshuffle of "Organic Shopping" / "Paid Shopping"). If you read a saved GA4 report from before the rule update, the Email row may differ. | Up to ±2 pp | | **Custom channel groups**. If your GA4 property has a custom channel group definition that overrides the default, Vortex IQ uses the default. Switch GA4 to default groups for direct comparison. | Variable | | **Late-arriving event ingestion**. Up to 4-hour delay. We snapshot at sync time. | Marginal on most recent 24h | | **Sampling on Explorations**. The standard Traffic acquisition report doesn't sample; custom Explorations on the same data can. | Don't compare to Explorations | **Cross-connector reconciliation, the IMPORTANT one:** This card lives at the intersection of GA4 and your ESP. Expected relationships: | Card | Expected relationship | What causes the divergence | | ---------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------- | | [`klaviyo.email_attributed_revenue`](/nerve-centre/kpi-cards/klaviyo/email-attributed-revenue) | **Klaviyo > GA4 Email channel typically by 5, 12 pp of total revenue.** Klaviyo claim ÷ Shopify total > GA4 Email share ÷ GA4 total. | Klaviyo: 5-day last-touch attribution. GA4: last-non-direct click within session. The wider attribution window in Klaviyo captures more purchases. | | [`dotdigital.email_attributed_revenue`](/nerve-centre/dotdigital/dotdigital_total_revenue) | Same shape. Dotdigital uses similar 7-day last-touch. | Same shape. | | [`shopify.total_revenue`](/nerve-centre/kpi-cards/shopify/total-revenue) | GA4 Email share × GA4 total = email-attributed revenue from GA4's view. Use this against the commerce truth side. | The structural GA4 tracking gap (10, 25%) shrinks email-attributed-revenue absolute numbers but not the share. | | [`bigcommerce.total_revenue`](/nerve-centre/kpi-cards/bigcommerce/total-revenue) | Same | Same | | [`adobe_commerce.total_revenue`](/nerve-centre/kpi-cards/adobe-commerce/total-revenue) | Same | Same | **Use this card alongside Klaviyo's own attribution.** GA4 gives you the conservative last-non-direct-click view; Klaviyo gives you the generous last-touch-within-5-days view. Truth is probably between them. **Neither GA4 nor Klaviyo is "the" source of truth for email attribution; they're two different lenses on the same behaviour.** **For attribution audits:** export both GA4 and Klaviyo at the same date range monthly, plot the gap. Stable gap = healthy. Diverging gap = either a UTM-tagging change OR a deliverability change (Klaviyo would also show open-rate drops in that case). ## Known limitations / merchant FAQs **Why is GA4 saying my email programme drives only 12% of revenue but Klaviyo says 22%?** Different attribution models. GA4 uses *last-non-direct click within session*: only purchases where the most recent attribution touchpoint was an email click get credited. Klaviyo uses *last-touch within 5 days*: any purchase within 5 days of an email open or click gets credited. Klaviyo's window is wider, so it claims more revenue. **Both are valid views of the same behaviour; GA4 is the conservative bookkeeper, Klaviyo is the optimistic salesperson.** Neither is "right". **My email share suddenly dropped from 18% to 5%. Did the programme die?** Almost certainly a UTM-tagging regression, not a programme collapse. Check (1) did your ESP push a template update that dropped UTM parameters from links? Klaviyo Flows often need explicit UTM-tagging configuration that's per-flow, not global, (2) did anyone publish a new email template that didn't inherit the brand's UTM defaults? (3) did your ESP migrate to a new link-tracking system (e.g. Klaviyo's "smart sending" or "click tracking v2")? **Check Klaviyo's own attribution to confirm: if Klaviyo's claim held steady at 22% but GA4's dropped to 5%, the programme is fine, the UTM plumbing is broken.** **What UTM parameters does GA4 require to classify a session as Email?** At minimum, `utm_medium=email` (or `utm_medium=e_mail`). Without that, GA4 falls back to channel classification by source (Klaviyo URLs go to "Referral", Mailchimp links may go to "Direct" if the link is bare). **The single most important fix for under-counted email is ensuring every email link includes `?utm_medium=email&utm_source=&utm_campaign=`.** Most ESPs have a global setting for this; if not, configure it per-template. **Does Apple Mail Privacy Protection (MPP) affect this card?** Less than you might think. MPP affects *open* tracking (it pre-loads tracking pixels, inflating open rates). MPP does NOT affect *click* tracking, when a recipient clicks a link, the URL with UTM parameters loads in their real browser. GA4's email-channel classification uses the click event, so MPP doesn't move this card directly. (MPP does affect Klaviyo's open-rate metrics, but not its click-attributed revenue.) **Why is GA4 sometimes higher than Klaviyo on email share?** Rare but possible. Two scenarios: (a) a customer clicks an email link, navigates around the site, leaves, comes back via a Klaviyo SMS instead, GA4 may still credit the original email click as last-non-direct, while Klaviyo credits the SMS as last-touch. (b) Klaviyo's 5-day window has expired but the customer's session-level GCLID-equivalent (GA4's session storage) is still intact. The two attribution models drift in different directions for different customer journeys. **My email share is healthy at 22% but my email revenue is dropping in absolute terms. What's happening?** This usually means total revenue is *also* dropping. The share is a ratio: if both numerator and denominator drop together, the share holds steady. Check [GA4 Revenue Trend](/nerve-centre/kpi-cards/google-analytics/revenue-trend) and your commerce-platform total revenue. If both are down, the issue is broader (acquisition channel collapse, seasonality, paid-ad performance dive); email is just maintaining its share of a shrinking pie. **Does this card include SMS / Klaviyo SMS?** No. GA4's "Email" channel is strictly utm\_medium=email. SMS clicks need utm\_medium=sms or fall into Direct. We're working on a separate SMS-attribution cross-platform card; for now, see your ESP's SMS revenue claim. **Does this card include transactional email (order confirmations, shipping)?** Yes if the customer clicks links in those emails AND the links carry utm\_medium=email. Most order-confirmation emails don't UTM-tag (they're not marketing), so transactional click revenue mostly falls into Direct. This is the right behaviour, transactional revenue isn't programme-driven. **Can I trust the share for "Today" or "This week"?** Less than the 30D window. Email programmes have weekly cycles (Tuesday and Thursday morning sends typically dominate); reading a 1-day or 3-day window picks up cycle noise. The 30D window smooths to a stable signal. If you need shorter-window visibility, use Klaviyo's own attribution dashboard, which is designed for short-window programme-side reads. *** ### Tracked live in Vortex IQ Nerve Centre *Email-Attributed Revenue Share* is one of hundreds of KPI pulses Vortex IQ tracks across Google Analytics 4 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. 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