Where in the GA4 funnel users drop off, joined to BC’s Incomplete population at the payment step. Powers report-checkout-conversion-failure, identifies the largest leak with a fix recommendation.
At a glance
The drop-off rate at each step of the BigCommerce checkout funnel, joined from GA4 ecommerce events (view_item→add_to_cart→begin_checkout→add_payment_info→purchase) to BC’s order-creation outcome (Incomplete vs Captured). Identifies the single largest leak with a per-step fix recommendation.
| What it counts | Per-step counts from GA4 funnel events, joined at the payment step to BC paymentStatus to distinguish “GA4 saw begin_checkout but never purchase” (drop) vs “GA4 saw purchase but BC shows Incomplete” (gateway-side failure). |
| VAT / tax treatment | n/a (counts of events). The dollar-impact per step uses BC total_inc_tax (tax-inclusive). |
| Shipping | n/a. |
| Discounts | n/a. |
| Refunds | Excluded; refunds are post-funnel. |
Incomplete / Declined orders | Surfaced as the payment-step failure population. The card’s whole point is to disambiguate “customer abandoned mid-funnel” (UX issue) from “customer hit Place Order but payment failed” (gateway issue). |
| Cancelled orders | Excluded. |
| Currency | n/a (counts metric). |
| Channels / sources | Web only (channel_id = 1). GA4 doesn’t track marketplace funnels. |
| Funnel steps surfaced | view_item, add_to_cart, begin_checkout, add_shipping_info, add_payment_info, purchase. The BC Incomplete status is mapped to “purchase event fired but payment never captured”, a sub-stage of the final step. |
| Tracking gap caveat | GA4 misses 10-25% of events to ad blockers / cookie rejection; the funnel counts are systematically underrepresented. Read step-to-step ratios, not absolute counts. |
| Time window | 30D |
| Alert trigger | any step drop >50%, fires when a single step in the funnel loses more than half the users from the previous step. Healthy stores see 10-30% step-to-step drop. |
| Roles | owner, marketing, operations |
Calculation
Calculated automatically from your BigCommerce 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 homewares brand on BigCommerce Enterprise with GA4 connected. The 30-day window covers 14 Mar 26 to 12 Apr 26.| Step | Sessions | Drop from prior step | Healthy benchmark | Verdict |
|---|---|---|---|---|
view_item | 184,200 | n/a | n/a | Top of funnel |
add_to_cart | 21,680 | -88.2% | -75 to -85% | Slightly elevated |
begin_checkout | 14,920 | -31.2% | -25 to -35% | Healthy |
add_shipping_info | 11,940 | -20.0% | -10 to -20% | Healthy |
add_payment_info | 8,420 | -29.5% | -10 to -25% | Slightly elevated |
purchase (GA4) | 3,540 | -58.0% | -10 to -20% | Broken |
BC Captured orders | 2,840 | -19.8% | -5 to -15% | Slightly elevated |
BC Incomplete orders | 414 | (gateway-side) | <8% of begin_checkout | Material leak |
- The biggest drop is
add_payment_info→purchaseat -58%. This is double the healthy benchmark and the alert fires here. The customers got to the payment page, entered details, and 58% of them never completed. This is the iframe / 3DS / payment-method-failure zone, the single highest-leverage fix on the store. - The
purchase→Captureddrop of 19.8% reveals the gateway-side leak. Of customers GA4 thinks completed, ~20% had BC mark them asIncomplete(gateway never returned success). This is the 414 Incomplete orders we already saw in BC Incomplete Rate. view_item→add_to_cartat -88% is normal for browse-heavy categories. Homewares customers compare extensively before adding; -88% is the top end of healthy. Below -90% would suggest product-page issues; this isn’t the priority.- Action priority is unambiguous: fix the payment step. The cumulative impact of the -58% leak at
add_payment_info→purchaseis roughly 4,800 lost orders per month at average AOV 624,000 of leaked annualised revenue. This dwarfs every other funnel optimisation.
- Read step-to-step drops, not absolute counts (GA4 tracking gaps make absolute numbers untrustworthy).
- Identify the single biggest above-benchmark drop and concentrate fix work there. The funnel is rarely broken in multiple places simultaneously; usually one step dominates.
- Pair with the per-device breakdown (Vortex Mind funnel report has device-class drill-in). The -58% payment step here is almost certainly concentrated in iOS Safari / Instagram in-app browser.
- Re-measure 14 days after a fix. If the targeted step’s drop returns to benchmark, the fix worked; if not, the diagnosis was wrong.
Sibling cards merchants should reference together
| Card | Why pair it with Checkout Funnel Drop |
|---|---|
| BC Incomplete Rate | The BC-side payment-step failure rate. Funnel drop diagnoses where; Incomplete Rate diagnoses how often at the final step. |
| BC Decline Rate | The other side of payment failure (decline vs incomplete). |
| BC XC Paid Traffic Waste | The dollar cost of funnel drops on paid sessions. |
| BC Failed Orders Value | The dollar value of the Incomplete + Declined population this card identifies. |
| BC Size of the Prize | The recoverable-opportunity view; funnel-fix work directly shrinks the prize. |
google_analytics.ga_ecommerce_conversion_rate | The aggregated funnel conversion this card disaggregates by step. |
google_analytics.ga_funnel_visualization | GA4 native funnel report; cross-checks the GA4 side of this card. |
| BC Repeat Failure Customers | Customers who keep hitting the funnel and failing; concentrated in the same step that this card identifies. |
Reconciling against the vendor’s own dashboard
Where to look in BigCommerce Control Panel: BigCommerce does not surface a checkout funnel natively. The funnel data lives in GA4; BC supplies the order-creation outcome at the final step. To partially verify:- GA4 → Reports → Engagement → Funnel exploration shows the GA4 funnel.
- BC Insights → Customer behaviour → Conversion on Plus / Pro plans shows partial funnel data (with caveats).
- BC’s Storefront → Abandoned carts shows pre-checkout abandonment but doesn’t disaggregate by step.
| Reason | Direction |
|---|---|
| GA4 tracking gaps. 10-25% of users blocked. The funnel counts are systematically under. | Vortex IQ counts LOWER than ground truth |
| GA4 sampling. GA4 free / standard tier samples sessions on high-traffic stores; figures may differ between report views. | Marginal |
| Time zone. GA4 in store-local time, BC in UTC, joins at the order layer use UTC. | Boundary effects |
| Event configuration. Some BC themes don’t fire all standard ecommerce events. | Funnel may show holes |
| Customer-level dedup. Multi-session customers are deduplicated at the order layer (BC) but not at the funnel step layer (GA4). | GA4 step counts inflate vs unique-customer view |
| Card | Expected relationship | Notes |
|---|---|---|
google_analytics.ga_funnel_visualization | The GA4-native funnel; this card adds the BC payment-step join | Should match GA4 numbers within 5% |
google_analytics.ga_ecommerce_conversion_rate | The aggregated outcome | This card disaggregates the same number |
| BC Incomplete Rate | The BC-side leak quantification | Should align with the purchase → Captured drop in this card |
| BC Total Revenue | Context for prioritisation | Helps size the dollar impact per fix |
Known limitations / merchant FAQs
My funnel shows huge drops at every step, is the whole checkout broken? Probably one step is dominating and the others are normal. Re-read the table: identify the single step with the biggest above-benchmark drop. That’s where to focus. Every step has a “normal” drop range; below benchmark is fine, above benchmark is the leak. Don’t try to fix every step at once, the gains aren’t additive in proportion. Why does GA4 show fewer purchases than BC has orders? GA4 misses 10-25% ofpurchase events to ad blockers, cookie rejection, and tag-fire failures. BC sees every order regardless. GA4 is always lower than BC at the order layer. This is structural, not fixable. Use BC for revenue truth and GA4 for funnel-stage truth.
The card flagged the add_to_cart → begin_checkout step, what does that usually mean?
Cart-stage friction: shipping cost shock, account-creation requirement, login wall, cart-summary confusion. Industry pattern: customers see the cart total with shipping/tax added and abandon. Fix by surfacing shipping estimates earlier (on PDP), removing forced account creation, and letting guest checkout proceed without registration.
The card flagged add_payment_info → purchase, where do I start?
Almost always one of: (1) Payment iframe / 3DS issue (BC Incomplete will be elevated), (2) Trust signals missing (no security badges, no trust marks at payment), (3) Form-validation friction (CVV / postal code mis-validation). Run a session recorder (FullStory, Hotjar) on customers who hit this step and abandon; the cause becomes obvious in 30 minutes.
My GA4 events are configured wrong, can the card still work?
If essential events (view_item, begin_checkout, purchase) are missing or mis-fired, the funnel has gaps and the card produces noisy or incomplete output. Audit GA4 ecommerce events first if the card looks weird. BC’s standard themes fire correct events; custom themes often need event-tracking implementation.
Should I worry about mobile vs desktop differences?
Yes, materially. Mobile funnels typically have 1.5-2.5x the drop rate at every step. The Vortex Mind funnel report has a device-class drill-in; always look at the mobile-only funnel as a separate view, mobile is where most checkout work pays off.
My checkout funnel looks fine in this card but Total Revenue is dropping, what now?
The leak is upstream of the funnel. Check ad-spend efficiency, organic traffic levels, brand search volume. The funnel is the conversion machine; if conversion is fine but revenue is down, fewer customers are entering the funnel in the first place.
Should I rebuild my checkout because the card said add_payment_info → purchase is broken?
No, fix the targeted issue first. A full checkout rebuild is a 6-month project that introduces new risks. The targeted fix (3DS configuration, iframe cookie policy, trust-mark visibility) is usually 1-3 weeks and gives you 80% of the gain.
Multi-currency stores: does the funnel split by currency?
Per-currency funnel views are available via Vortex Mind drill-in but the headline card is currency-agnostic. EU/UK funnels typically show worse add_payment_info → purchase performance than US (3DS / SCA friction); the difference is structural, not a defect in your store specifically.
Why doesn’t the card show pre-view_item traffic (homepage, category pages)?
Because pre-view_item is a category-engagement question, not a checkout-conversion question. The Vortex Mind landing-page report covers pre-PDP engagement; this card focuses on the conversion-critical funnel from product view onward.