Tickets we created from audit findings that haven’t been resolved yet.
At a glance
Live count of Zendesk tickets that Vortex IQ filed on your behalf from audit findings (broken checkout flows, refund spikes, performance regressions, ad-on-OOS, missing SEO fields) and which still sit in an unresolved state in your support queue. The merchant question this answers is: “how many revenue-protecting fixes have I asked Zendesk to triage that haven’t been picked up yet?” Treat this card as your unactioned-revenue-leak counter, not as a generic ticket count.
| What it counts | Zendesk tickets created by the Vortex IQ integration (tagged vortex_iq or vortex_finding in Zendesk) whose status is one of: New, Open, Pending, On-hold. Solved and Closed tickets drop out. |
| API endpoint | GET /api/v2/search.json?query=type:ticket tags:vortex_iq status<solved. We page until exhaustion, capped at 1,000 results per refresh (Zendesk Search API page-size hard cap). |
| Ticket-state filter | New + Open + Pending + On-hold. Solved/Closed/Deleted excluded. Pending counts because in Zendesk that state means “waiting for the requester”, which on a Vortex IQ ticket usually means waiting on the agency or on the merchant’s developer, so it still represents an open finding. |
| Bot-handled tickets | Included. If your Answer Bot or a custom Sunshine Conversations bot replies to one of these tickets and leaves it in a non-solved state, it still counts as open. The ticket is only “closed” when a human or workflow sets status to Solved. |
| Multi-brand aggregation | Aggregated across every Zendesk brand under the same subdomain when the connector has access. Set vortex_iq.brand_filter in the connector config to scope to a single brand. |
| Multi-channel scope | All channels (Email, Web Form, API, Help Centre, Chat, Talk, Social Messaging) because Vortex IQ-created tickets always come in via API. The card does not filter by via.channel. |
| Time window | RT, refreshed every 60 seconds via the Zendesk Search API. |
| Alert trigger | > 20 open. The 20-ticket threshold is the typical point at which the merchant has lost track of which findings have been triaged. |
| Anomaly detection | If the count grows by >5 in 60 minutes, Vortex IQ raises an “Audit findings backing up” alert. |
| Time zone | Account timezone in Zendesk Admin Centre → Account → Localisation. Used for the rolling-window alert calculation. |
| Roles | owner, operations |
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
A US mid-market home-and-kitchen brand on Adobe Commerce running Zendesk Suite Professional with three brands (US, Canada, Wholesale). Snapshot taken on 02 May 26 at 09:40 PT.| Brand | Open Vortex IQ findings | Channel mix | Oldest ticket age |
|---|---|---|---|
| US retail | 14 | API only | 9 days (broken size-chart on 4 PDPs) |
| Canada retail | 6 | API only | 4 days (CAD currency mis-rounding on cart totals) |
| Wholesale | 3 | API only | 12 days (B2B pricing tier missing on 22 SKUs) |
| Total | 23 |
- The number itself is the leak count, not a workload metric. 23 unactioned findings means 23 places where Vortex IQ has already evidenced a revenue or customer-experience problem and the team has not yet decided what to do. Anchor the standup on these tickets first, before triaging anything else in the queue.
- The Canada CAD rounding finding (4 days old) is the highest-impact one even though it is the newest. Cross-reference
adobe_commerce.refund_ratefor Canada. If refund rate has crept up by more than a percentage point since the bug landed, the cost is roughly (refund delta) × (CAD GMV in window). That number usually justifies same-day resolution. - The Wholesale finding is the oldest at 12 days but lowest urgency. B2B pricing tier missing on 22 SKUs only matters when those SKUs are quoted; if the wholesale rep has been quoting manually, the impact is zero. Confirm with the rep before bumping priority. Old does not mean urgent in the support queue.
- 23 open is a leading indicator of customer-service capacity strain. Pair this card with
zen_open_tickets. If the whole Zendesk backlog is also elevated and the team are drowning, Vortex IQ findings get buried under live customer queries, which is how silent revenue leaks form. Throwing a temp agent at the queue for two days clears the air. - The 9-day-old size-chart finding is the most likely to read as “stale” to a non-engineering CXO. Make sure it has a status update from engineering attached as an internal note in Zendesk, even if the fix is not done. Visible movement is the cheapest way to keep findings from being abandoned (and tipping into the Abandoned Findings card).
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 “this one is silently leaking money” subset of this card. | Open count steady but Abandoned rising equals you are filing findings faster than you are triaging them. The team needs a SLA on Vortex IQ tickets, not just on customer tickets. |
| Open Tickets (all) | Total Zendesk backlog. Vortex IQ findings compete with live customer tickets for agent attention. | If both are elevated together, your CS team is overloaded and findings will get buried. Add capacity or carve out a dedicated triage hour. |
| Avg Cycle Time | How long the team takes to move a Vortex IQ ticket from Open to Solved. | Cycle time creeping up while open count grows means triage is breaking down. Inspect Top Assignees Overloaded next. |
| Finding Resolution Rate (90d) | The throughput-side counterpart. | Open count high + resolution rate low equals findings get filed but never closed, the worst possible state for an audit programme. |
| Refund Rate (Adobe Commerce / Shopify / BigCommerce) | Refund spikes are a leading indicator that should generate Vortex IQ findings; this card shows whether you are acting on them. | Refund rate up + Vortex IQ findings flat equals audit gap. Findings up + refund rate trending down equals the programme is working. |
| Avg First-Response Time | Vortex IQ tickets count toward your CS-team SLAs unless excluded. | If FRT is elevated, the agency or merchant is letting findings sit unassigned, which both fails the merchant SLA and drags average team metrics. |
| Customer Service Sentiment (Shopify) | The downstream NPS-style outcome that justifies running this audit programme at all. | Open findings dropping + CS sentiment rising equals proof the audit programme protects retention. The CXO-readable story. |
Reconciling against the vendor’s own dashboard
Where to look in Zendesk’s own dashboard:Agent Workspace → Views → Unsolved tickets in your groups with a tag filter onFor multi-brand accounts, run the search inside each brand’s subdomain or filter bytags:vortex_iq. Admin Centre → Reporting → Explore → Tickets dataset for a queryable view of all Vortex IQ tickets and their state. Search bar with the literal querytags:vortex_iq status<solvedreturns the same population this card counts.
brand_id in Explore.
Why our number may legitimately differ from Zendesk’s view:
| Reason | Direction | Why |
|---|---|---|
| Time zone | Boundary days off | Zendesk Agent Workspace honours each agent’s personal timezone; Vortex IQ uses the account-level timezone for the alert threshold and cross-connector arithmetic. |
| Ticket-channel scope | Ours equals theirs | Both Zendesk and the card include all channels by default. If you have set up a brand-level channel filter in Zendesk, apply the equivalent filter in Vortex IQ’s connector config. |
| Archived / deleted tickets | Ours lower | Tickets in Zendesk’s Recycle Bin still appear in some Explore queries for up to 30 days; Vortex IQ’s Search API call excludes them entirely. |
| Pending status semantics | Ours higher in some readings | We count Pending tickets as open because on a Vortex IQ finding “pending” usually means “waiting on a developer”, not “waiting on a customer”. Some Zendesk views (the default agent inbox) hide Pending. |
| Multi-brand aggregation | Either | We aggregate across all brands the connector can read; if you only look at one brand subdomain in Zendesk, that view is a subset of ours. |
| Search index lag | Ours lower for “just now” | Zendesk’s Search API uses a separate index that lags real-time ticket creation by 30-90 seconds. A finding filed seconds ago may not yet be in the count. |
| Card | Expected relationship | What causes the divergence |
|---|---|---|
adobe_commerce.refund_rate / shopify.refund_rate / bigcommerce.refund_rate | Refund rate spikes should generate Vortex IQ findings, so the two should co-move with a 24-72h lag. | If refund rate is up but findings count is flat, the audit programme is missing the signal; if findings are up but refund rate is steady, you are catching issues before they cause refunds (the goal). |
shopify.customer_service_sentiment | Inversely correlated. Findings closing fast equals sentiment protected. | When findings open count climbs above 30 for more than two weeks, expect CSAT to dip 3-5 points; this is the merchant cost of letting the queue build. |
Known limitations / merchant FAQs
Why does Vortex IQ’s number disagree with Zendesk Explore? Three usual culprits, in order of likelihood:- Time zone. Explore reports honour the dataset’s configured timezone (often UTC); Agent Workspace honours the agent’s personal timezone. Our card uses the account-level timezone. A 30-minute disagreement at midnight is normal.
- Pending tickets. Most default agent views hide Pending. We count it because for a Vortex IQ finding, “pending” usually means waiting on a developer, not a customer.
- Search index lag. The Zendesk Search API lags real-time creation by 30-90 seconds. If you just filed a finding, give it a minute before counting.
vortex_iq.brand_filter: <brand_id> in the connector config. Multi-brand merchants typically prefer per-brand cards on separate dashboards.
Open count just jumped, what should I check first?
A 5-step playbook:
- Check your commerce platform first. Open the relevant Refund Rate, Cancellation Rate, and Order Volume cards for Shopify / BigCommerce / Adobe Commerce. A spike in refunds is the most common driver of audit findings.
- Then check site reliability. Open Datadog Operational Health Score and Sentry error rate. A bad deploy generates a tail of customer-facing errors that turn into support tickets.
- Then check the product catalogue. Catalogue Drift, Ads on OOS, and Top Products cards on the commerce platform. A pricing or stock change that shipped without QA can flood Zendesk with refund and “where is my order” tickets.
- Finally, check Vortex IQ findings categories. Filter by Vortex IQ tag (
vortex_iq:checkout,vortex_iq:catalogue,vortex_iq:performance) to see which audit area is firing. The category is the strongest signal of which engineering team to assign. - If none of the above explain it, suspect a viral negative review or social mention. Check Brand Mentions or social listening; one bad TikTok can drive 30+ tickets in an hour.
POST /api/v2/tickets). If a merchant or agency forwards a finding into Zendesk by email, that creates a separate ticket which will not carry the vortex_iq tag and so is excluded from this count. Add the tag manually if you want it counted.