At a glance
Frustration Signals vs Cart Abandonment overlays the dead clicks and rage clicks Microsoft Clarity detects with the cart abandonment rate your ecommerce platform records. When a spike in frustration signals lines up with rising abandonment, you have visual evidence of where shoppers are giving up and why. For merchants, it connects on-page friction directly to lost carts and lost revenue.
| What it counts | Clarity dead-click and rage-click frustration signals plotted against the platform’s cart abandonment rate over the window. |
| Sample type | Behavioural session data from Microsoft Clarity (heatmaps and session recordings), refreshed on the standard data refresh. |
| Why it matters | Frustration that co-occurs with abandonment pinpoints checkout and cart friction that is actively costing orders. |
| Reading the value | Lines moving together upward mean friction and abandonment are rising in step; a co-occurring spike is the signal to act. |
| Currency | percent |
| Time window | 30D |
| Alert trigger | dead-click spike co-occurs with abandonment |
| Sentiment key | clr_xc_session_quality_vs_cart_abandonment |
| Roles | owner, marketing |
Calculation
Vortex IQ overlays the dead-click and rage-click frustration signals Microsoft Clarity captures from behavioural data with the cart abandonment rate recorded by your ecommerce platform, plotting both on a dual axis over the selected window. The frustration side reflects what Clarity observes; the abandonment side comes from your store platform, not Clarity. See At a glance for the headline definition and the worked example below for a representative reading.Worked example
A representative reading of Frustration Signals vs Cart Abandonment for a typical merchant on Microsoft Clarity. Over the 30 days to 12 Mar 26, the chart might show dead clicks on the cart page jumping sharply around the same date that cart abandonment climbs from 68% to 79%. That co-occurrence suggests a broken or unresponsive element, perhaps a coupon field or a disabled checkout button, is pushing shoppers to abandon. Use Vortex Mind to trace the spike to the specific element and date, then ask Ask Viq in plain English to confirm which step in the cart drew the frustration clicks.Sibling cards merchants should reference together
| Card | Why merchants reach for it |
|---|---|
clr_rage_click_rate | Isolates the rage-click component of the frustration signal driving abandonment. |
clr_dead_click_rate | Isolates dead clicks, the most common sign of an unresponsive checkout element. |
clr_checkout_path_frustration_signals | Focuses the frustration view specifically on the checkout path. |
clr_cart_abandonment_rate | The platform abandonment figure this card compares the frustration signals against. |
clr_xc_funnel_vs_ecom_conversion | Shows how cart friction flows through to the wider conversion gap. |
Reconciling against Microsoft Clarity
Where to look in Microsoft Clarity’s own dashboard: Review the Dashboard insights for dead and rage clicks and the recordings filtered to the cart pages to confirm the frustration side, but note the cart abandonment figure comes from your store platform’s reporting, not Clarity. Confirm the period and any device, channel, or bot filters match the Vortex IQ profile before comparing. Why the Vortex IQ value may legitimately differ:| Reason | Direction | What to do |
|---|---|---|
| Period boundary. Vortex IQ uses rolling windows by default; Clarity may use calendar periods. | Variable | Match the period range. |
| Sampling. Clarity may sample sessions on high-traffic sites; Vortex IQ reads what Clarity exposes. | Variable | Allow for sampling on busy stores. |
| Filter scope. Profile-level filters (device, channel, bot exclusion) may narrow the Vortex IQ view. | Variable | Match filter settings. |