Tickets we created from audit findings that haven’t been resolved yet.
At a glance
Live count of Intercom tickets/conversations that Vortex IQ filed on your behalf from audit findings (broken checkout flows, refund spikes, ad-on-OOS, missing SEO fields) and which still sit in open state. Intercom blends live messaging with ticket-style triage; Vortex IQ findings file as Back-office tickets but the Inbox view shows them alongside live shopper conversations. The merchant question this answers: “how many revenue-protecting fixes have I asked the team to triage that haven’t been picked up?”
| What it counts | Intercom tickets/conversations created by the Vortex IQ integration (tagged vortex_iq in Intercom) whose state is open. |
| API endpoint | POST /tickets/search (or /conversations/search on legacy accounts) with body {"query": {"field": "tags", "operator": "=", "value": "vortex_iq"}, "filters": [{"field": "state", "operator": "=", "value": "open"}]}. Cursor-based pagination via pages.next. |
| State filter | open only. Intercom has open, snoozed, and closed. Snoozed tickets are excluded by default because the merchant intentionally deferred them (the snooze period expires and they auto-reopen, which puts them back in this card’s count). |
| Project / board scope | All Intercom workspaces the connector token reads. Multi-workspace merchants (rare) see a blended count by default; set vortex_iq.workspace_filter to scope. |
| Issue type filter | All Vortex IQ-tagged tickets included. Intercom’s “Type” field (Customer / Back-office / Tracker) is honoured; Vortex IQ findings always file as Back-office because they are not customer-initiated. |
| Resolution counts | N/A; this card is the open count, not a rate. |
| Multi-channel scope | Intercom has Email, Messenger (in-app + web), WhatsApp, SMS, and Phone. Vortex IQ findings always file via API to the Back-office ticket type, regardless of merchant channel mix. |
| Time window | RT, refreshed every 60 seconds. |
| Alert trigger | >20 open raises a warn-level alert. |
| Anomaly detection | If the count grows by >5 in 60 minutes, Vortex IQ raises an “Audit findings backing up” alert. |
| Time zone | Workspace timezone in Settings, Workspace, General. |
| AI Fin / Resolution Bot interaction | Intercom’s Fin AI agent and Resolution Bot can reply to tickets; their replies do NOT close the ticket by default. Configure with an exclusion: IF tag CONTAINS 'vortex_iq' THEN do_not_handle, otherwise Fin can auto-reply with generic content that resets the SLA clock without fixing anything. |
| Roles | owner, operations |
Calculation
Calculated automatically from your Intercom 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 SaaS-meets-DTC brand running Intercom Pro across both their B2C ecommerce site and their B2B account portal. Single workspace, two segmented Inboxes. Snapshot taken on 02 May 26 at 10:45 ET.| Inbox | Open Vortex IQ findings | Notes |
|---|---|---|
| B2C Storefront | 12 | Mostly checkout-error and Klaviyo-flow findings from the 18 Apr release. |
| B2B Portal | 6 | SSO callback and account-detail-page findings; high-stakes for enterprise clients. |
| Total | 18 | Below the 20-ticket alert threshold by 2. |
- Intercom’s hybrid model means the team must distinguish “ticket work” from “live messaging”. Vortex IQ findings file as Back-office tickets, but the default Inbox view shows them alongside live shopper conversations. Without an Inbox filter, the team triages by recency and live conversations dominate; findings sit unread. Build a saved Intercom view for
tags:vortex_iq AND type:back-office AND state:openand pin it for the team. This is the single highest-leverage Intercom config change for finding triage. - Fin AI agent should NOT auto-reply to Vortex IQ findings. Fin is excellent at refund-status and shipping-ETA replies on customer queries; it has no business replying to a finding like “checkout error rate spiked 18%”. Configure Fin with an exclusion:
IF tag CONTAINS 'vortex_iq' THEN do_not_handle. Otherwise Fin “responds” with a generic reply that resets the SLA clock without fixing anything. - The B2B portal cluster (6 findings) is the highest-revenue-risk subset. Six SSO and account-detail findings on a B2B portal can cost more revenue per finding than 12 B2C-storefront findings combined; a single SSO regression on an enterprise client breaks login for an entire seat-pool until fixed. Triage these first regardless of count.
- Intercom’s Inbox priority should put
tags:vortex_iqabove default. Use Inbox, Settings, View Priority to elevate Vortex IQ findings above default-priority shopper queries during business hours; the team sees them inline with normal triage rhythm. Some merchants split the queue: one ops lead owns Vortex IQ findings full-time during peak hours, frontline agents handle live conversations.
Sibling cards merchants should reference together
| Card | Why pair it with VortexIQ Findings Open | What the combination tells you |
|---|---|---|
| Abandoned Findings (>14d no movement) | The silently-leaking subset. | Open count steady but Abandoned rising = findings filed faster than triaged. |
| Open Tickets (all) | Total Intercom backlog. | Both elevated = inbox overloaded; findings get buried under live shopper queries. |
| Avg First-Response Time | Intercom’s headline merchant metric. Vortex IQ findings count toward it unless excluded. | If FRT is elevated, finding tickets are dragging the average. Build a saved view with a separate SLA. |
| Snoozed Conversations | Findings agents intentionally deferred. | Snoozed > Open = the team is using snooze to mask rather than action; investigate. |
| Fin AI Resolution Rate | Whether Fin is helping or hurting. | High Fin handling on Vortex IQ findings = Fin is replying to findings, which is wrong. Fix the rule. |
| Refund Rate (Shopify / BigCommerce) | Refund spikes drive most audit findings. | Refunds up + findings flat = audit blind spot; findings up + refunds dropping = programme working. |
| Ecommerce Conversion Rate | The primary outcome metric. | Open findings climbing + conversion rate dropping = direct cost evidence. |
| Customer Service Sentiment | NPS-side outcome. | Findings dropping + sentiment rising = audit programme is protecting retention. |
| Datadog Health Score | Technical findings should map to Datadog signals. | Vortex IQ “checkout error” finding open + Datadog steady = possible false positive. |
Reconciling against the vendor’s own dashboard
Where to look in Intercom’s own dashboard:
Intercom Inbox, build a saved view: tags:vortex_iq AND type:back-office AND state:open. Pin the view for the team.
Reports, Conversations for trend visibility on the same tag filter.
Tickets module on accounts with the new tickets product enabled; same filter applies.
Why our number may legitimately differ from Intercom’s view:
| Reason | Direction | Why |
|---|---|---|
| Time zone | Boundary days off | Intercom Reports use the workspace timezone; the Inbox UI uses each agent’s profile timezone. The card uses workspace timezone for alert calculations. For real-time count this rarely matters; for date-bounded comparisons it can shift one day. |
| Snoozed-ticket inclusion | Either | The card excludes state:snoozed by default; some Intercom views include them. If your saved view shows more than the card, snooze filtering is usually the cause. |
| Tag-filter exactness | Ours stricter | We require literal vortex_iq. Legacy tags from earlier Vortex IQ versions drop out. |
| Workspace scope | Either | Card aggregates across all connected workspaces; Intercom Inbox scopes to one workspace at a time. |
| Fin-handled tickets | Same in both | Fin’s auto-reply does not change ticket state; both views count Fin-replied tickets as still-open. |
| Webhook delay | Up to 60s stale | A close from the last minute may not have reached the card; Intercom’s UI updates instantly. |
| API rate-limit lag | Up to 30s stale during peak | Intercom rate-limits at 1000/min for most endpoints. |
| Legacy-conversations vs new-tickets | Either | Recent Intercom releases blur the line. The card uses the unified tickets:vortex_iq filter that works on both legacy-conversations and new-tickets accounts. |
| Card | Expected relationship | What causes the divergence |
|---|---|---|
shopify.refund_rate / bigcommerce.refund_rate | Refund spikes drive most findings (24-72h lag). | Refunds up + findings flat = audit blind spot; findings up + refunds dropping = programme working. |
shopify.ecommerce_conversion_rate | When findings stack up unaddressed, conversion typically dips within 2-4 weeks. | Open findings >25 for 3+ weeks predicts a 0.05 to 0.15 percentage-point conversion-rate dip. |
shopify.customer_service_sentiment | Inversely correlated. | Open findings >30 for 2+ weeks predicts CSAT drop of 3-5 points. |
Known limitations / merchant FAQs
My Intercom Inbox view says I have 22 open findings but Vortex IQ says 18. Which is right? Both, almost always. The four-ticket gap is the standard set: snoozed-ticket inclusion (your Inbox view may includestate:snoozed; the card excludes), workspace scope (the card aggregates across workspaces, your Inbox scopes to one), tag drift (vortex_iq vs legacy vortexiq), and webhook delay. Open the per-workspace stack panel to reconcile.
The Fin AI agent replied to one of my Vortex IQ findings. Does that count as resolved?
No. The Fin reply does not change ticket state; the ticket stays open until an agent or rule explicitly sets state: closed. So the count is still accurate. However, an Fin reply on a Vortex IQ finding is bad behaviour: stock Fin replies are designed for shopper queries (refund status, shipping ETA, working hours), not for findings like “checkout error rate spiked 18%”. Configure Fin with an exclusion: IF tag CONTAINS 'vortex_iq' THEN do_not_handle.
Snoozed tickets are excluded by default. Why?
Because the merchant intentionally deferred them, often “waiting on shopper” or “waiting on engineering”. Snoozed tickets auto-reopen when the snooze period expires, at which point they re-enter this card’s count. The card focuses on actively-open work; snoozed work is a deliberate decision.
My team uses Intercom for both ecommerce and B2B portal support. Will both Inboxes see the findings?
Yes if both Inboxes are within the same workspace. The card aggregates across all Inboxes in the workspace by default. Build a saved view per Inbox (with a custom-attribute filter on the relevant store/portal segment) for per-Inbox visibility.
A finding important enough to fix manually but we never used Intercom to track it. Do we close the ticket?
Yes. Close the ticket via the Intercom UI or set state: closed via API. Otherwise it stays in the count and the abandoned-rate timer (14 days of no movement) starts ticking. Vortex IQ does not auto-close findings just because the underlying audit signal cleared.
Open count dropped suddenly. What happened?
Three usual causes. (1) Bulk close by an agent or admin from the Inbox; Intercom does not surface bulk-close events as audit-log entries by default. (2) Tag drift: someone removed the vortex_iq tag from a batch of tickets. (3) Vortex IQ outbound paused: check the connector status in Settings, Connectors.
Why is the count higher today than the typical baseline?
On commerce-CX-led Intercom merchants, the most common cause is a promotional push driving traffic. Ad spend surfaces audit issues fast (broken checkout flows, OOS-on-ad, sale-price-drift). The mid-afternoon spike pattern is normal during promos. Pre-empt by running audits before promo windows.
Should I configure a separate Intercom SLA for Vortex IQ tickets?
Yes if your team’s volume warrants it. Intercom’s headline Avg First-Response Time includes Vortex IQ tickets by default. Two practical options. (1) Build a saved Inbox view with a separate FRT target via an SLA tag (e.g. 24h for findings, 4h for shopper queries). (2) Use Intercom’s Workflows engine to apply a different SLA to Vortex IQ tickets.
My team uses Intercom but you also have Jira connected. Will Vortex IQ duplicate findings into both?
No. Each finding routes to one tool based on the connector setup’s outbound priority. Default for ecommerce-CX-led merchants is Intercom (or Gorgias / LiveChat equivalent); for engineering-led merchants the default is Jira. Override in Settings, Connectors, Routing if your operations team owns the queue regardless of engineering involvement.
Is Intercom the right tool for managing Vortex IQ findings?
Intercom shines when audit findings have a customer-experience framing (chat-widget UX, post-purchase confusion, returns-policy drift). Intercom’s customer-context inline view (Shopify orders, plan tier, last activity) makes the cost of each finding visible alongside the work to fix it. If your team treats audit findings as engineering tickets, Linear / Jira is closer; if they treat them as ops workflows, Asana / Trello.
Today’s count looks volatile. Why?
At low volumes (<10 open) a single close or new finding moves the count by 10%+ which can register as visual noise. The 30-day average and 7-day rolling are the steadier reads for trend; the headline number is the live count.
Why is the alert threshold 20 and not 30 or 50?
20 reflects Intercom’s typical inbox-size profile. Most Intercom merchants run 100 to 300 daily total tickets/conversations, so a Vortex IQ count of 20 means roughly 7 to 20% of the inbox is findings, which is the threshold above which the team perceives the audit programme as noise. Tunable per organization in connector settings.