At a glance
Revenue attributed to Google Ads conversions in the period, the outcome number that pairs with gads_total_spend to form the ROAS calculation. This is Google Ads telling you what it thinks it earned for you, which is a different question from what your commerce platform recognises as revenue from paid traffic. Reconciling this card against Shopify/BigCommerce/Adobe Commerce revenue from paid sources is one of the most common, and most legitimately divergent, conversations in DTC marketing operations.
| What it counts | SUM(metrics.conversions_value) across every campaign in the account during the period. The conversions_value field reflects the Google Ads attribution model’s view of revenue attributable to ad-driven conversions, in the account’s billing currency. |
| Conversion attribution model | Determined by the account’s settings in Google Ads → Tools → Measurement → Conversions → Attribution model. Defaults are data-driven attribution for accounts with sufficient conversion volume, last-click attribution for smaller accounts. The Vortex IQ card surfaces whatever Google’s API returns, so the attribution model is implicit. Brands evaluating ROAS across channels need to know which model is in play because data-driven attribution credits Google Ads for conversions that last-click would credit elsewhere. |
| Attribution window | Default is 30-day click + 1-day engaged-view for most account types. Configurable per conversion action. Conversions outside the window do not count. The window matters more than most merchants realise: a 7-day click window and a 30-day click window can produce 15-25 percent revenue gaps for the same actual customer behaviour. |
| Currency | Account billing currency. Multi-account brands sum each account in its own currency; this card does not perform FX conversion. |
| VAT / tax treatment | Tax-inclusive when the conversion source includes tax. Most ecommerce conversion tracking (Shopify, BigCommerce, custom GTM tags) sends the full transaction value including tax. The revenue surfaced here is therefore tax-inclusive in most configurations. Brands wanting tax-exclusive ROAS should configure conversion tracking to send the pre-tax amount, which is a one-time setup change in the conversion-action definition. |
| Cross-device conversions | Counted by default. Google Ads identifies cross-device conversions (a click on mobile, a purchase later on desktop) and attributes the revenue to the original click. This inflates conversions_value vs same-device-only attribution, which is the right behaviour but the merchant should be aware. The gads_conversions_by_device card surfaces the device breakdown. |
| View-through conversions | Counted by default for engaged views (10+ second video views or YouTube ad clicks). A user who watches a YouTube ad for 11 seconds, does not click, but later searches for the brand and converts, can have the conversion attributed to the YouTube ad. Brands evaluating YouTube ROAS should distinguish click-through vs view-through revenue; the gads_all_conversions card includes engaged-view conversions explicitly. |
| Imported offline conversions | Counted if uploaded. Brands using Google Ads’ offline conversion import (CSV upload, Google Tag for offline events, Salesforce integration) see post-purchase upsell revenue, B2B contract closes, or in-store conversions counted in this metric. The conversion timestamp determines the period; a conversion uploaded in May for a click in April counts in April’s window. |
| Bot / invalid traffic | Google’s MFA/IVT (Made For Advertising / Invalid Traffic) filters operate on clicks, not conversions. A click filtered as invalid (and credited back) does not contribute to spend; if a conversion was attributed to that invalid click, the conversion stays attributed but the spend is reduced. Net effect: ROAS can rise after invalid-click credits without revenue changing. |
| Refunds and cancellations | NOT deducted by default. Google Ads tracks the conversion event (the order placed) but not subsequent refunds or cancellations. Brands needing refund-net ROAS must implement post-conversion adjustments via the Google Ads API’s conversion adjustment endpoint, which is a non-trivial engineering setup. The gads_conversion_actions card surfaces whether adjustments are configured for the account. |
| Subscription LTV vs first-purchase revenue | First-purchase revenue by default. Brands selling subscription products see only the first-purchase value attributed to the ad click, not the full lifetime value. For high-LTV subscription brands, configuring conversion-value-based bidding using LTV-adjusted conversion values is the single biggest ROAS optimisation because it tells Smart Bidding what the actual customer value is, not just the first-billing value. |
| Time window | T/7D/30D vsP (today, 7 days, 30 days vs prior period). The “today” view is incomplete because attribution windows extend past today (a click today can be credited with a conversion tomorrow). |
| Alert trigger | drop >15 percent vsP (a 30-day revenue figure that fell more than 15 percent vs the prior 30-day period). |
| Sentiment key | gads_revenue_trend |
| Roles | owner, marketing, finance |
Calculation
Calculated automatically from your Google Ads 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-based fashion brand on Shopify running a £40,000/month Google Ads programme alongside Meta Ads, organic SEO, email marketing, and a small Reddit Ads experiment. Snapshot for the 30-day window ending Wednesday 15 May 26.| Source of attribution | Google Ads conversions_value | Shopify revenue from paid_google | Gap |
|---|---|---|---|
| Brand search | £165,000 | £142,000 | +£23,000 (Google higher) |
| Non-brand search | £58,000 | £52,000 | +£6,000 |
| Shopping standard | £103,000 | £99,000 | +£4,000 |
| Performance Max | £148,000 | £121,000 | +£27,000 |
| YouTube remarketing | £9,800 | £4,200 | +£5,600 |
| Display retargeting | £4,200 | £2,100 | +£2,100 |
| Account total | £488,000 | £420,300 | +£67,700 (16% Google higher) |
- The £67,700 gap (16 percent Google higher) is the textbook reconciliation challenge in DTC paid marketing. Both numbers are correct; they answer different questions. Google Ads tells you “revenue we believe ad clicks generated using our attribution model”; Shopify tells you “revenue we recognised on orders where the last touch was a Google Ads UTM”. The gap is real and structural, not a tracking bug.
- Brand search shows the largest absolute gap (+£23,000). Brand search has the highest cross-device and cross-session activity (people search the brand on mobile, complete the purchase on desktop later) which Google’s data-driven attribution captures and Shopify’s last-touch UTM does not. The gap here is mostly assist value; the question is how much of it is genuinely incremental. Industry estimates put incremental brand-search ROAS at 8-12x of the headline 44x figure, which would shrink the £23,000 gap to perhaps £4,000-£8,000 of “real” incrementality.
- Performance Max shows the largest relative gap (+£27,000 on £148,000 = 22 percent). Performance Max actively expands the attribution surface (cross-device, view-through, audience-signal-driven) and consistently over-reports revenue vs last-click reconciliation. Brands relying on Performance Max should anchor their P&L on commerce-platform revenue (Shopify in this example) and use Google’s revenue figure only for in-Google optimisation decisions. Reporting Performance Max revenue at the Google figure to the board overstates contribution by 20-30 percent typically.
- YouTube and Display gaps are relatively small in absolute terms but large in proportion. YouTube’s £9,800 vs £4,200 (130 percent gap) reflects the upper-funnel attribution behaviour: YouTube is generating brand awareness that converts later through other channels, and Google credits YouTube for the awareness contribution. Whether the merchant should value that depends on the brand’s stage; emerging brands (year 1-2) typically should value upper-funnel; mature brands (year 5+) typically should not.
- The 16 percent blended gap is in the normal range. Industry data suggests 10-20 percent gaps between Google Ads attributed revenue and commerce-platform last-touch revenue are typical. Gaps below 5 percent suggest the merchant is using last-click attribution in Google Ads (under-reporting) or has cross-device tracking disabled. Gaps above 25 percent suggest aggressive Performance Max usage or YouTube-heavy spend mix.
- The Vortex Mind Customer Recovery Opportunity report quantifies the assist component. Rather than litigating which attribution model is “right”, the report runs both views (last-click and data-driven) and surfaces the cross-channel cohort: customers who saw a Google Ad, then engaged with email or organic, then converted. This is where the genuine incremental value lives.
- Check whether spend dropped proportionally. If
gads_total_spendalso dropped 15 percent, the campaign portfolio is shrinking (budget cuts, paused campaigns) and the revenue drop is expected. If spend held steady, ROAS is degrading and the diagnosis runs deeper. - Decompose by campaign type.
gads_revenue_by_campaignsurfaces which campaigns drove the drop. Search vs Shopping vs Performance Max patterns suggest different fixes. - Cross-reference
gads_conversion_rate_trend. A revenue drop with steady conversion rate means traffic dropped (impression share, CPC pressure pricing the merchant out); a revenue drop with falling conversion rate means traffic is converting worse (landing page issue, product mix shift, audience quality drift). - Check for
gads_alert_conversion_tracking_broken. A common cause of “revenue dropped” is conversion tracking actually broke; a Google Tag fails to fire, conversions stop being recorded, and the API returns artificially low conversions_value. Confirm tracking is healthy before assuming the drop is real. - Pair with the upstream commerce platform revenue. If Shopify total_revenue is steady but Google Ads revenue dropped, the issue is attribution-side (model change, tracking failure, conversion-action definition change). If both dropped, the issue is real demand-side weakness.
| Time horizon | Action |
|---|---|
| First 1 hour after alert | Verify the Google Tag is firing on the order-confirmation page. The fastest broken-tracking check. |
| First 4 hours | Cross-reference with Shopify/BC/Adobe revenue from paid_google source. If they agree the drop is real; if not the gap is attribution-side. |
| First 24 hours | Decompose by campaign type; identify whether the drop concentrates in Search, Shopping, Performance Max, or upper-funnel. |
| First week | If sustained, brief leadership with the decomposition. The Vortex Mind Google Ads Revenue Intelligence report runs the same decomposition automatically and adds the incrementality view. |
Sibling cards merchants should reference together
| Card | Why merchants reach for it |
|---|---|
gads_total_spend | The denominator alongside revenue’s numerator. The pair drives ROAS. |
gads_roas | The headline efficiency figure derived from this card and total_spend. |
gads_all_conversions | Includes view-through, engaged-view, and cross-device conversions explicitly counted. The fuller attribution view. |
gads_conversions_trend | The conversion-count view alongside conversion-value. Pair to size whether revenue moved because conversions moved or because basket size moved. |
gads_revenue_by_campaign | The campaign-level decomposition. Required for any revenue-shift investigation. |
gads_landing_page_revenue | Revenue by landing page URL. Useful for product-page vs category-page performance comparisons. |
gads_top_keywords_conversions | Revenue and conversions by keyword. The portfolio-management view. |
gads_conversion_rate_trend | The conversion rate that links revenue to clicks. A revenue drop with steady conversion rate means traffic dropped; with falling conversion rate means quality dropped. |
gads_conversion_lag | The time delay between click and conversion. Affects how the period-end revenue should be interpreted. |
gads_alert_conversion_tracking_broken | The alert that fires when conversion tracking breaks. Always check this card before treating a revenue drop as real. |
gads_xc_revenue_share | Cross-channel view of paid revenue contribution alongside email, SEO, organic social, and direct. |
gads_xc_email_overlap | The cross-channel attribution view comparing Google Ads-attributed revenue with Klaviyo email-attributed revenue when both touched the same customers. |
GA4 ga_revenue_by_channel | The GA4 view of paid_google revenue. Should approximate this card after attribution-window normalisation. |
Shopify total_revenue filtered to paid_google | The commerce-platform last-touch view. Reconciliation against this is the most common merchant question. |
BigCommerce total_revenue | Same logic for BigCommerce stores. |
Adobe Commerce total_revenue | Same logic for Adobe Commerce stores. |
Meta Ads total_revenue | The Meta parallel for cross-platform paid-mix decisions. |
Reconciling against the vendor’s own dashboard
Where to look in Google Ads’s own dashboard:- Google Ads → Campaigns with the “Conv. value” column added. Set the date picker to match the Vortex IQ period.
- Google Ads → Tools → Measurement → Conversions (ads.google.com/aw/conversions) for the conversion-action-level view. Critical when investigating whether a specific conversion action is driving the revenue shift.
- Google Ads → Tools → Measurement → Attribution → Model comparison to see how the same revenue would be attributed under different models. Helps merchants understand the gap between data-driven and last-click views.
| Reason | Direction | What to do |
|---|---|---|
| Time zone. Google Ads dashboard uses the account’s configured time zone; Vortex IQ uses UTC for period boundaries. | Boundary days differ | Largest impact on T (today) and 7D windows; for 30D the drift averages out. |
| Refresh lag. Google reports conversions with a 24-72 hour delay (longer for offline conversions); the Vortex IQ refresh cadence (every 6 hours) compounds this. | Vortex IQ lower for the most recent 24-72 hour window | Wait for next refresh; check last_synced_at. The dashboard catches up earlier for engaged-view and view-through conversions. |
| Conversion adjustments. Refunds and cancellations uploaded via the conversion-adjustment API reduce the historical revenue figure retroactively. The current period’s revenue figure may shrink as adjustments arrive. | Vortex IQ moves down as adjustments arrive | Brands using conversion adjustments should expect the period revenue to drift downward by 2-5 percent over the 30 days following the period end. |
| Attribution model change. A model change in the account (last-click → data-driven, or vice versa) re-calculates historical revenue. Vortex IQ shows the current attribution model’s view; comparison with a screenshot from before the change won’t match. | Either direction | The Google Ads dashboard’s “Attribution” tab shows the model history. |
| Conversion-action enable/disable. A conversion action that was disabled mid-period stops contributing prospectively but historical attributions remain. A newly-enabled conversion action’s value appears only after the enable timestamp. | Either direction | The conversion-actions list shows enable/disable history. |
| Comparison | Expected relationship | When divergence is legitimate |
|---|---|---|
gads_total_revenue ↔ Shopify total_revenue (filtered to paid_google) | Google typically higher by 10-20 percent | Google’s data-driven attribution credits cross-device, view-through, and assist conversions that Shopify’s last-touch UTM does not. The 10-20 percent gap is the structural attribution difference; gaps above 25 percent suggest aggressive Performance Max usage; gaps below 5 percent suggest tracking is misconfigured. |
gads_total_revenue ↔ BigCommerce total_revenue (filtered to paid_google) | Same logic, BC parallel | Same. |
gads_total_revenue ↔ Adobe Commerce total_revenue (filtered to paid_google) | Same logic, Adobe parallel | Same. |
gads_total_revenue ↔ GA4 ga_revenue_by_channel paid_google row | Should approximate within 5 percent after attribution-window normalisation | GA4 and Google Ads are the same Google ecosystem; the attribution should align closely if both are configured correctly. Divergence usually indicates a configuration drift (different attribution model in GA4 vs Google Ads) rather than a tracking failure. |
gads_total_revenue ↔ Meta Ads total_revenue | Independent metrics; sum may overlap | Cross-platform attribution overlap is real (a customer who saw a Meta ad and a Google ad gets credited to both platforms). Brands running both should size the overlap using cross-channel attribution; treating Google + Meta as additive overstates true paid contribution by 15-30 percent. |
Known limitations / merchant FAQs
Why is my Google Ads revenue higher than my Shopify revenue from paid_google traffic? Structural attribution difference, not a tracking bug. Google Ads uses data-driven attribution (or last-click for smaller accounts) with cross-device tracking, view-through windows, and engaged-view conversions; Shopify uses the last-touch UTM on the order. Google’s view captures customers who clicked an ad on mobile and bought on desktop later, who saw a YouTube ad and converted via direct traffic, or who clicked a Search ad, browsed, came back via email, and converted. Shopify only sees the final UTM. The 10-20 percent gap is normal; above 25 percent suggests Performance Max is doing more attribution-expansion than the brand realises. Should I report Google Ads revenue or Shopify paid-google revenue to the board? For board reporting, anchor on the commerce platform’s revenue (Shopify, BigCommerce, Adobe Commerce). The commerce platform is the system of record for “what we sold and recognised as revenue”. Google Ads’ figure is useful for in-Google optimisation decisions (which campaigns are working) but overstates contribution to the P&L. Best practice is to report both in the marketing review with a brief note explaining the gap, and to anchor only on the commerce-platform figure in the financial review. My Google Ads revenue dropped 25 percent overnight. What happened? Possibilities, in order of likelihood. (1) Conversion tracking broke: a Google Tag failed to fire on the order-confirmation page, conversion events stopped being recorded, and the API returned artificially low conversions_value. This is the single most common cause and the first thing to check. (2) Attribution model changed: someone in the account switched from data-driven to last-click (or vice versa). The “Attribution” tab shows model history. (3) Conversion-action disabled: a conversion action that was contributing significantly was disabled, removing its revenue from the figure prospectively. (4) Google’s data-driven attribution model retrained and reweighted contributions. The retraining typically happens monthly and can shift attribution by 5-15 percent on a single retraining day. (5) Genuine demand drop, less common as a 25 percent overnight move but possible during major external events. Why does Performance Max revenue look so high vs the spend? Performance Max actively expands the attribution surface (cross-device, view-through, audience-signal-driven attribution). It is designed by Google to capture conversions that other campaign types would miss, and the same algorithmic decisions credit Performance Max with conversions that other channels would otherwise claim. This is partly real (Performance Max is genuinely driving incremental conversions) and partly attribution-shift (Performance Max is taking credit for conversions that would have happened anyway). Industry estimates put the genuine incremental component at 30-50 percent of the headline; the rest is attribution-shift. The Vortex Mind Customer Recovery Opportunity report runs an incrementality analysis that quantifies this. Can I get a refund-net revenue figure? Only if the brand has implemented Google Ads’ conversion-adjustment API. The setup is non-trivial: a webhook from the commerce platform to Google when an order is refunded, with the appropriate conversion-action and conversion-value adjustment. Most brands do not implement this and instead reconcile separately at month-end using the commerce-platform refund data. The Vortex IQ card reflects whatever Google’s API returns; if conversion adjustments are configured the refund-net figure flows through, otherwise it does not. Why does the “today” revenue figure keep going up even after midnight? Two reasons. (1) Conversion lag: a click that happened today can be credited with a conversion tomorrow, next week, or up to 30 days from now (depending on the attribution window). The figure for “today” continues to grow as those delayed conversions arrive. (2) Cross-device attribution: Google identifies cross-device conversions over time as user-graph data refreshes; a click from yesterday with a conversion from today on a different device may be linked retroactively. The “today” figure is a moving target for the next 30 days; brands needing fixed period reporting should freeze the figure at month-end + 5 days as a working compromise. My YouTube revenue is much higher in Google Ads than in any other tool. Why? YouTube benefits from Google’s view-through attribution, which credits YouTube ads with conversions where the user watched 10+ seconds of the ad without clicking, and later converted via any path (organic search, direct, email). Other tools (GA4, the commerce platform) use click-based attribution and do not credit YouTube for these view-through conversions. The Google Ads view is therefore systematically higher than third-party tools’ view of YouTube performance. Whether to value this depends on the brand’s stage; emerging brands typically should value upper-funnel awareness; mature brands typically should not weight it heavily in last-click ROAS comparisons. My subscription product’s first-purchase revenue is showing in Google Ads. Should I configure LTV-based bidding? Yes, if subscription LTV is significantly higher than first-purchase value (typically true for subscription brands). Configuring conversion-value-based bidding using LTV-adjusted conversion values tells Smart Bidding what the actual customer value is. Setup: create a conversion action that sendsLTV_estimate × first_purchase_indicator instead of just first-purchase value; Smart Bidding will then bid more aggressively for high-LTV customer profiles. The implementation is a one-time engineering setup; the impact on ROAS is typically a 20-40 percent improvement over 60-90 days as Smart Bidding learns the new value signal.
Can Vortex IQ change my conversion tracking or attribution model?
Read-only by design. Vortex IQ surfaces revenue and attribution patterns; the merchant’s marketing or measurement team executes inside Google Ads. The Vortex Mind Google Ads Revenue Intelligence report generates merchant-side Actions when revenue patterns suggest tracking issues or attribution-model misconfiguration, but the configuration changes themselves sit with the merchant.