Findings sat in the backlog with no status change for two weeks, these are the ones losing money silently.
At a glance
Open Vortex IQ-tagged LiveChat tickets that have had no team-side activity in 14+ days. The silent-leak subset of the open backlog: findings filed, never picked up, quietly compounding revenue risk while the team focuses on live chat conversations. On LiveChat-using merchants this card is particularly important because LiveChat’s tickets module is secondary to the live-chat module in agent attention; without this card, the abandoned bucket grows unnoticed inside an ancillary module.
| What it counts | Open LiveChat tickets tagged vortex_iq whose last_modified_at (any field change) is older than 14 days. |
| What counts as movement | Any of: agent reply (private message or to-customer), status change, assignee change, tag change, priority change, applied automation rule. Customer reply does NOT count (the card focuses on team progress); ChatBot auto-reply does NOT count by default. |
| Project / board scope | All tickets across all groups the connector token reads. Multi-group merchants see the blended count by default; set vortex_iq.group_filter to scope. |
| Status filter | open only (LiveChat ticket states: open, pending, resolved, closed). The card also includes pending because in LiveChat’s data model pending typically means “waiting on internal action”, which matches the abandonment-risk profile. |
| Issue type filter | All Vortex IQ-tagged tickets included regardless of LiveChat ticket type. |
| Resolution counts | N/A; abandonment is about the open population only. |
| API endpoint | POST /v3.5/agent/action/list_archives with filter tags=vortex_iq AND status IN [open, pending] AND last_modified_at<now-14d. Cursor-based pagination. The 14-day staleness clock evaluates on every webhook event and on a 5-minute scheduled refresh. |
| Time window | RT |
| Alert trigger | >5 warn, >15 critical. The warn threshold catches early stagnation; the critical threshold reflects systemic execution failure on LiveChat-using teams (typically smaller-volume CX teams). |
| Sentiment key | Threshold-based, {warn: 5, critical: 15}. |
| Time zone | Account timezone in Settings, Account. The 14-day cutoff aligns to the account timezone so the abandonment boundary matches the team’s working calendar. |
| Roles | owner, operations |
Calculation
Calculated automatically from your LiveChat 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 boutique cosmetics brand on Shopify running LiveChat Business plan, 6-person CX team. Single LiveChat group. Snapshot taken on 02 May 26 at 10:15 BST.| Bucket | Open Vortex IQ tickets | Abandoned (>14d no movement) | Notes |
|---|---|---|---|
| Active (last 14 days) | 8 | 0 | Team is actively triaging recent findings. |
| Stale (14 to 30 days) | 4 | 4 | Mostly chat-widget UX findings, queued behind live-chat work. |
| Long-stale (>30 days) | 2 | 2 | Returns-policy URL drift; re-flagged repeatedly but never picked up. |
| Total open | 14 | 6 | At warn (>5), below critical (>15). |
- Abandoned doubled vs 30D average and tipped over warn. The CX team is keeping pace with recent findings (8 active, 0 abandoned in the last 14 days) but the older bucket is accumulating. This is the LiveChat-typical pattern: team prioritises live-chat module over tickets module, so older tickets get buried.
- The 4 chat-widget UX findings stagnant in the 14 to 30 day band are the tractable cluster. Chat-widget UX findings on LiveChat-using merchants are particularly important because the widget IS the merchant’s primary support channel; widget regressions degrade the team’s own tools. Triage these first; the agents themselves are the immediate beneficiaries of the fix.
- The 2 long-stale (>30 days) returns-policy URL drift findings are the highest-revenue-risk subset. Returns-policy mismatches are conversion killers. These findings have been re-flagged repeatedly (the audit signal cleared briefly then re-flagged each cycle) without the team ever closing them. Action: assign one ops lead today; this is the kind of finding that quietly costs more revenue per week than the entire LiveChat license.
- Pair with
liv_open_tickets. If global LiveChat ticket backlog is also elevated, the team is overloaded across the board (likely a promotional push or a shipping spike); the audit programme is being deprioritised under load. If global tickets are flat but Vortex IQ abandoned is rising, it is specifically the audit work being deprioritised. - The right action is a weekly 30-minute “abandoned review”. Run it with the CX lead. For each finding: if no real merchant impact, close (LiveChat’s
closedis terminal). If real merchant impact, reassign and add a note. We see LiveChat merchants close 30 to 50% of abandoned findings on this triage; the remainder being correctly prioritised is the win. - LiveChat’s automation rules can help. Build a rule:
IF tags CONTAINS 'vortex_iq' AND last_modified_at > 21 days AND priority NOT IN [high, critical] THEN close ticket AND apply tag 'auto_closed_low_impact'. Auto-closes the bottom-tier abandoned findings on a 21-day timer.
Sibling cards merchants should reference together
| Card | Why pair it with Abandoned Findings | What the combination tells you |
|---|---|---|
| VortexIQ Findings Open | Abandoned is a subset of open. The ratio is the steadier read. | Abandoned ÷ Open above 35% on LiveChat-typical small queues = the queue is stagnating. |
| Finding Resolution Rate (90d) | Resolution rate drops first; abandoned count rises second. | The textbook capacity-collapse sequence. |
| Open Tickets (all) | Total LiveChat ticket-module backlog. | Both elevated = team overloaded across the board; abandoned in isolation = audit deprioritised specifically. |
| Avg Chat Response Time | LiveChat’s headline customer-facing metric. | Chat response time rising + abandoned rising = team focused on live chat at the expense of tickets module. |
| Tickets by Assignee | Tells you whether abandonment concentrates on one person. | If 70% of abandoned findings sit on one assignee, the fix is reassignment. |
| Shopify / BigCommerce Conversion Rate | The downstream truth metric, especially for chat-widget findings. | Abandoned widget-UX findings + falling conversion rate = direct causal evidence; the widget is becoming a friction point. |
| Refund Rate (Shopify / BigCommerce) | Returns / refund-flow finding cluster. | Abandoned on returns clusters drives refund rate up over a 4 to 8 week window. |
| Customer Service Sentiment | NPS-side outcome. | Sustained abandoned predicts CSAT drop within a quarter. |
Reconciling against the vendor’s own dashboard
Where to look in LiveChat’s own dashboard:LiveChat Agent App, Tickets section, filterLiveChat does not ship a built-in “abandoned” view; this card is closest to the saved-filter pattern. Why our number may legitimately differ from a saved LiveChat view:tag:vortex_iq AND status:open OR pendingand sort byLast activity ascending. Tickets at the top are the most stale. Manually scan for those last touched >14 days ago. Reports, Tickets, Tag breakdown for trend visibility. Save the filtered view via Save filter as for repeat use.
| Reason | Direction | Why |
|---|---|---|
| Time zone | Boundary day off | LiveChat reports use account timezone; agent UI uses each agent’s profile timezone. The card uses account timezone. |
| Pending-state inclusion | Either | The card includes pending (in LiveChat’s data model pending typically means “waiting on internal action”); some saved filters scope to open only. |
| Customer-reply movement | Ours stricter | The card excludes customer replies as movement. LiveChat’s “last activity” includes them. A ticket where a customer replied 10 days ago counts as abandoned in this card if the team has not responded. |
| ChatBot-reply movement | Ours stricter | ChatBot auto-replies do NOT count as movement on Vortex IQ tickets. LiveChat’s last_modified_at updates on bot replies. |
| Tag drift | Ours stricter | We require literal vortex_iq. Legacy tags drop out. |
| Group scope | Either | Card aggregates across all groups; LiveChat UI typically scopes to the agent’s group. |
| Webhook delay | Up to 60s stale | A movement event from the last minute may not have reached the card. |
| Card | Expected relationship | What causes the divergence |
|---|---|---|
shopify.refund_rate / bigcommerce.refund_rate | Inverse correlation. Higher abandoned rate predicts a refund rate rise over a 4 to 8 week trailing window. | Abandoned on returns / refund-flow findings drives refunds up. |
shopify.ecommerce_conversion_rate | Inverse correlation; tighter on chat-widget-heavy stores. | Abandoned widget-UX findings + falling conversion rate = the widget is becoming a friction point. |
shopify.customer_service_sentiment | Inverse correlation; 2 to 4 week lag. | Sustained abandoned predicts CSAT drop. |
Known limitations / merchant FAQs
LiveChat shows my ticket was modified yesterday but the card says abandoned. What is wrong? Almost always one of these. (1) The “modification” was a customer reply; the card excludes customer replies as movement. (2) The “modification” was a ChatBot auto-reply; the card excludes ChatBot replies on Vortex IQ tickets. (3) Webhook delay. Open the ticket and check the activity feed for an explicit human-team-member action in the last 14 days. What counts as movement? Any of: agent reply (private message or to-customer), status change, assignee change, tag change, priority change, applied automation rule. Customer replies do NOT count. ChatBot auto-replies on Vortex IQ-tagged tickets do NOT count. The 14-day window feels arbitrary. Can we tune it? Yes, in Settings, Connectors, LiveChat, Abandonment threshold (days). Default is 14 days. Smaller LiveChat-using merchants (under 50 daily total tickets) often tune up to 21 days because their cycle time is naturally slower; larger merchants tune down to 10 days. Multi-group: my account spans multiple LiveChat groups. Why does this card show one number? The card aggregates across groups by default. To break out by group, setvortex_iq.group_filter in connector config or build a Stacked Panel in Vortex IQ Nerve Centre with one panel per group.
Velocity dropped, abandoned count rising. What changed?
Standard playbook. (1) Open Tickets by Assignee and look for sudden concentration changes. (2) Open Avg Chat Response Time; if it rose sharply, the team is being pulled into live chat at the expense of tickets. (3) Open Open Tickets; if the global ticket-module backlog is also up, the team is overloaded across the board. (4) Cross-check against any global-incident pattern; a returns surge or shipping disruption pulls the team off audit work for days.
The abandoned count appears suddenly higher overnight. Why?
Because the 14-day clock keeps ticking. If five findings were last touched on the same day exactly 14 days ago, all five become abandoned at the same time the next day. Normal and self-corrects within 24 hours of the team picking the queue back up.
Should I close abandoned findings or fix them?
Both, depending on triage. Run a weekly 30-minute “abandoned review” with the CX lead. For each: if no real merchant impact, close (LiveChat’s closed is terminal). If real merchant impact, reassign and add a note. We see LiveChat merchants close 30 to 50% of abandoned findings on this triage; the remainder being correctly prioritised is the win.
Why doesn’t LiveChat ship an “abandoned” view natively?
LiveChat’s tickets module is auxiliary to its live-chat module; the product team has historically prioritised live-chat features over tickets-module features. The card’s added value: cross-group aggregation, customer-reply / ChatBot-reply exclusion, threshold-based alerts, historical trend.
Is this card the right primary watch metric for LiveChat-using merchants?
Yes. Findings Open tells you the queue size; this card tells you the queue health. On LiveChat-using merchants the abandoned card is particularly important because the tickets module is secondary in agent attention; without explicit watch, abandoned findings accumulate.
A finding important enough to fix manually but we never used LiveChat to track it. Do we close the ticket?
Yes. Close the ticket in LiveChat once the work is done. Otherwise it stays in the abandoned bucket. Vortex IQ does not auto-close findings just because the underlying audit signal cleared.
Can LiveChat’s Automation engine auto-close low-impact abandoned findings?
Yes. Build an automation: IF tags CONTAINS 'vortex_iq' AND last_modified_at > 21 days AND priority NOT IN [high, critical] THEN close ticket AND apply tag 'auto_closed_low_impact'. Auto-closes the bottom-tier abandoned findings on a 21-day timer, leaving high-impact ones for human triage. Most LiveChat merchants who adopt this see abandoned-bucket size drop 40 to 60% within a month.
My team uses LiveChat but we route all important work through Jira. Why are findings landing in LiveChat?
Check the connector routing setup. If LiveChat is listed before Jira in the outbound priority, findings file in LiveChat first. For engineering-led merchants on LiveChat, the typical routing is Jira primary, LiveChat secondary (for chat-widget-specific findings only). Override in Settings, Connectors, Routing.
Does the card include pending tickets?
Yes, by design. In LiveChat’s data model pending typically means “waiting on internal action” (e.g. waiting on developer to fix the underlying widget bug); this matches the abandonment-risk profile because the team is not actively working the ticket. If your team uses pending to mean “waiting on customer reply”, build a custom view via the connector to exclude pending from the count.
Why is the alert threshold >5 / >15 and not higher?
LiveChat-using merchants typically run smaller-volume CX teams than Zendesk-using merchants; the abandoned threshold is calibrated to that scale. A 5-finding warn threshold reflects roughly 30 to 40% of a typical small-team Vortex IQ open backlog. Tunable per organization in connector settings.