Findings sat in the backlog with no status change for two weeks, these are the ones losing money silently.
At a glance
Live count of Vortex IQ findings sitting in your Zendesk queue with no status change for 14 days or more. The merchant question this answers is: “how many revenue-leak fixes have I forgotten about?” This is the silent drain gauge. Every ticket in this count was important enough to file but has not been touched, which usually means it has dropped off the team’s mental backlog and is quietly costing money on every shopper session.
Calculation
Calculated automatically from your Zendesk data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
The same US home-and-kitchen brand from the parent card. Snapshot taken on 02 May 26 at 09:40 PT. Of the 23 open Vortex IQ findings, 7 have not seen any status change for two weeks or more.
The card reads 7. Threshold says warn at 5, critical at 15, so the panel is amber. Three observations:
- The composite weekly leak is roughly £3,400. Add the estimated revenue costs across the seven abandoned findings: that is the silent monthly drain the merchant has accepted by not triaging. £3,400/week is more than most agency retainers, by itself a justification for an audit-triage SLA.
- The 30-day-old Algolia search finding is the highest-priority one despite the smallest absolute revenue. Search returning zero for a category term is a leading indicator of a much bigger catalogue or indexing issue. If “tongs” returns zero, “spatulas” probably does too. Pull the
shopify.search_zero_resultssibling on the commerce side; if zero-result rate is up across categories, this single finding is masking a 5-10% sitewide search regression. - Two of the seven are NPS-impacting, not revenue-impacting. The macro response time and the Klaviyo 404 do not directly drop revenue this week; they erode trust over months. Pair with
shopify.customer_service_sentiment. NPS-only findings should still close, just on a different SLA than direct revenue findings. - The wholesale finding is 12 days old, just under the 14-day cutoff. It will tip into Abandoned tomorrow if no one comments. The cheapest action: a one-line internal note from the wholesale rep (“quoting manually, fix scheduled for next sprint”) resets the clock and removes it from the abandoned list. Visible activity, not just intent, is what this card watches.
Sibling cards merchants should reference together
Reconciling against the vendor’s own dashboard
Where to look in Zendesk’s own dashboard:Agent Workspace → Views, build a view:Why our number may legitimately differ:Tags = vortex_iqANDStatus < SolvedANDHours since update > 336(336 = 14 × 24). Explore → Tickets dataset with the calculated metricD_COUNT(Tickets) WHERE updated < DATE_SUB(NOW(), INTERVAL 14 DAY) AND tags CONTAINS 'vortex_iq' AND status < SOLVED. Search withtags:vortex_iq status<solved updated<14days_ago.
Cross-connector reconciliation:
Known limitations / merchant FAQs
Why does our Zendesk Explore view say a different number? Three reasons:- Field choice. Explore lets you pick
last_updated_atorlast_public_comment_at. Vortex IQ useslast_updated_at, which counts internal notes as movement. If your Explore view uses public comments only, it will report more abandoned tickets. - Time zone. The 14-day cutoff is UTC for the card; Explore honours the dataset zone.
- Recycle Bin. Soft-deleted tickets stay searchable in Explore for 30 days but are excluded from the Search API the card uses.
updated_at, so the 14-day clock resets. We treat any update as “the team is still thinking about it”. Abandonment is silence, not lack of resolution.
Should bot replies count as movement?
Yes by default, because they update updated_at. If you would rather discount bot updates (the bot is keeping the clock alive on tickets nobody is actually triaging), set vortex_iq.exclude_bot_updates: true in the connector config and the card will only consider human or trigger-driven updates.
Why is the threshold 14 days, not 7 or 30?
Empirical. Across 200+ Vortex IQ-connected merchants, the probability that an open finding will eventually close drops sharply after day 14 and approaches zero after day 21. 14 is the latest day at which intervention still typically rescues the ticket. 7 would generate too many false alarms; 30 would let half the rescuable tickets fall through.
My team flags some findings as “won’t fix”. Do they count?
Yes, until the status moves to Solved or Closed. “Won’t fix” is a label inside Zendesk; the API still sees the ticket as Open or Pending. If you want won’t-fix tickets out of this count, configure a workflow that solves them automatically when a wont_fix macro is applied.
The count went from 5 to 0 overnight, what happened?
Most likely someone ran a bulk update (Zendesk → Edit → Bulk update tickets) and added a comment to all the matching tickets. That resets updated_at and removes them from Abandoned. This is fine if it was deliberate triage; suspicious if it looks like queue-grooming to make the metric look better. Audit by looking at the next-90-day Resolution Rate. If those tickets actually close, the bulk update was healthy; if they age into Abandoned again two weeks later, the team is gaming the metric.
Open count jumped, what should I check first?
Same playbook as the parent VortexIQ Findings Open card with one addition: if Abandoned jumped without Open jumping, you have a triage stoppage (someone left, on holiday, deprioritised) rather than a finding influx. Check Top Assignees Overloaded next.
Response time vs resolution time, which one is this card about?
Resolution-time-extreme. This card is the long tail of resolution time, not response time. A ticket can have a 30-second first response and still be abandoned if the conversation goes silent after that. The card’s purpose is to catch the abandoned-after-initial-response pattern.
Multi-brand aggregation: should I split this card per brand?
Yes if your brands have separate engineering teams. The merchant SLA on Vortex IQ findings should be set at the brand level. Use vortex_iq.brand_filter to scope per-brand panels and surface them on each brand’s tab in the Nerve Centre.