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 Freshdesk queue with no status, comment, assignee, or tag 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 here was important enough to file but has not been touched, which usually means it has fallen off the team’s mental backlog.
| What it counts | Tickets in the fre_vortexiq_findings_open population whose updated_at is older than now() - 14 days. |
| API endpoint | GET /api/v2/search/tickets?query="tag:'vortex_iq' AND (status:2 OR status:3) AND updated_at:<'14_days_ago'". The Search API supports relative date filters but rounds to the nearest day; for hour-level precision the connector falls back to the bulk Tickets API and filters in-memory. |
| Ticket-state filter | Open + Pending + custom-open (Resolved/Closed/Spam excluded), same as the parent. |
| What counts as “movement” | Any change to updated_at: a comment (public or private), a status change, an assignee change, a tag change, an SLA policy reassignment, a Freddy auto-action. Just opening the ticket in the agent UI does not update updated_at. |
| Bot-handled tickets | Freddy AI replies update updated_at and reset the 14-day clock. |
| Multi-product (multi-brand) aggregation | Aggregated across all Products. |
| Time window | RT, refreshed every 60 seconds. |
| Alert trigger | Warn at >5, Critical at >15. Absolute counts, not percentages, because a single abandoned finding can leak meaningful revenue. |
| Sentiment | Threshold gauge: 0-5 healthy, 6-15 warn (amber), 16+ critical (red). |
| Time zone | Account timezone. The 14-day boundary computes in UTC and offsets for display. |
| Roles | owner, operations |
Calculation
Calculated automatically from your Freshdesk 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 UK fashion SMB from the parent card. Snapshot taken on 02 May 26 at 14:20 BST. Of the 17 open Vortex IQ findings, 6 have not seen any update for 14 days or more.| Finding | Age | Last activity | Estimated revenue cost |
|---|---|---|---|
| Mobile menu z-index issue (PDP unreachable on iPhone 12) | 19 days | Filed, no comment | £700/week (mobile traffic 65% of total) |
| Klarna BNPL mid-checkout failure | 16 days | Comment “investigating” on day 1 | £4,200/week (high-AOV BNPL conversion drop) |
| Klaviyo abandoned-cart link 404 | 22 days | Filed | £400/week (recovered-revenue gap) |
| Algolia search returns 0 for “midi dress” | 27 days | Filed | £600/week (search-to-purchase) |
| Free-shipping threshold widget renders £0 | 14 days | Status changed once on day 2 | £900/week (AOV down 5% on cart-aware sessions) |
| Returns portal SSO loop on Safari | 20 days | Filed | £200/week (returns-handling time, not revenue) |
- Composite weekly leak ≈ £7,000. Five of the six findings translate directly to weekly revenue loss; the sixth (returns SSO) is operational cost. £7k/week is roughly £30k/month, which exceeds the cost of an additional CS triage agent on a typical mid-market SMB. The card is your business case for adding capacity.
- The Klarna finding is the single most expensive abandoned ticket. £4.2k/week dwarfs the others. It’s been sitting for 16 days with one “investigating” comment from day 1. This is the classic “looked at, never resolved” pattern. Apply a Freshdesk SLA Policy that triggers an automatic escalation if a Vortex IQ ticket sits in the same status for 7 days.
- The 27-day-old Algolia “midi dress” finding is the most diagnostic. A category-defining search term returning zero is a leading indicator of a much wider catalogue indexing gap. Pair with
shopify.search_zero_results. If sitewide zero-result rate is up, this single finding is hiding a larger issue. - The free-shipping threshold widget tipped into Abandoned exactly today. It was last touched on day 2 (status change), then nothing. Day 14 cutoff. The cheapest action: a one-line “still scoped for next sprint” internal note resets the clock and removes it from this list. Visible movement is the cheapest abandonment-prevention.
- Pair this card with
shopify.refund_rateandshopify.customer_service_sentiment. “Abandoned findings: 6, refund rate up 0.4 pts, NPS down 4 points” makes the cost legible at the board level.
Sibling cards merchants should reference together
| Card | Why pair it with Abandoned Findings | What the combination tells you |
|---|---|---|
| VortexIQ Findings Open | Total backlog. Abandoned is a subset. | Abandoned ÷ Open is the “stale ratio”. Above 30% means triage broken; below 10% means team healthy. |
| Finding Resolution Rate (90d) | Throughput. | Abandoned rising while resolution rate steady means team picks easy tickets and lets hard ones sit. |
| Avg Time-to-Fix | Resolution latency. Abandoned is the long tail. | If avg is 5 days but Abandoned is 15, distribution is bimodal: most close fast, some never close. Surface the long tail with a Freshdesk view. |
| Top Assignees Overloaded | Capacity bottleneck. Abandonment concentrates on overloaded agents. | If 60%+ of abandoned tickets share an assignee, reassign or add capacity. |
| Refund Rate (Shopify / BigCommerce / Adobe) | Downstream revenue cost of letting findings sit. | Abandoned >10 + refund rate climbing equals direct evidence the audit programme is broken. |
| Customer Service Sentiment (Shopify) | NPS-side cost of unfixed friction. | UX-flavoured abandoned findings predominantly impact this metric. |
| Datadog Operational Health Score | Technical findings should map to Datadog signals. | Abandoned “checkout error” finding + Datadog error rate steady equals possible false positive; safe to close after engineer review. |
Reconciling against the vendor’s own dashboard
Where to look in Freshdesk’s own dashboard:Tickets list with filters:Why our number may legitimately differ:Tag = vortex_iq,Status IS Open OR Pending,Last updated more than 14 days ago. Save as “Vortex IQ abandoned findings”. Admin → Workflows → Ticket Filters to make this a shared view across the team. Analytics → Curated Reports → Aging Tickets with the same filters.
| Reason | Direction | Why |
|---|---|---|
| Time zone | Boundary day off | The 14-day cutoff is computed in UTC by Vortex IQ; Freshdesk filters honour the dataset zone. |
| Search API hard cap | Ours capped at 300 | The Search API returns at most 10 pages × 30. Accounts with very large abandoned counts (rare) see slight lag while the connector falls back to the bulk API. |
| Archived / deleted tickets | Ours lower | Trash tickets excluded from Search API. |
| What counts as movement | Ours stricter on private notes | We use updated_at, which captures private notes. Some Freshdesk views look only at “Last Activity” excluding private notes, which would put more tickets into Abandoned. |
| Multi-product aggregation | Either | Card aggregates across Products; per-Product views are subsets. |
| Card | Expected relationship | What causes the divergence |
|---|---|---|
shopify.refund_rate / bigcommerce.refund_rate / adobe_commerce.refund_rate | Abandoned findings often correspond to chronic refund drivers. | When refund rate is up and abandoned count >10, the leak is being measured but not fixed; this is the “audit programme broken” alert. |
shopify.customer_service_sentiment | NPS slowly degrades as abandoned count climbs. | Lag between abandonment and NPS dip is typically 4-8 weeks. |
Known limitations / merchant FAQs
Why does Freshdesk Analytics show a different number? Three reasons:- Field choice. Freshdesk’s “Last Activity” field can be configured to exclude private notes; we always use
updated_atwhich includes them. - Time zone. The 14-day cutoff is UTC for the card; Analytics honours dataset zone.
- Search API page cap. Counts above ~300 may lag the bulk API briefly during refresh.
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 Freddy AI updates count as movement?
Yes by default. If you’d rather discount Freddy-only 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.
Why is the threshold 14 days, not 7 or 30?
Empirical. Across 200+ Vortex IQ-connected merchants, the probability that an open finding closes drops sharply after day 14 and approaches zero after day 21. 14 is the latest day at which intervention typically rescues the ticket.
My team flags some findings as “won’t fix” via a custom status. Do they count?
Yes, until the status maps to Resolved or Closed. “Won’t fix” custom statuses sit in the open bucket from the API’s perspective. To exclude them, map your won’t-fix custom status to Closed or add a workflow that resolves them automatically.
The count went from 6 to 0 overnight, what happened?
Most likely a bulk update via Freshdesk’s “Edit Multiple Tickets” function added a comment to all matching tickets. That resets updated_at and clears Abandoned. Healthy if it was deliberate triage; suspicious if findings re-enter Abandoned 14 days later (gaming).
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.
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. Use Freshdesk SLA Policies’ “Resolution time” target (not “First response time”) for Vortex IQ-tagged tickets.
Multi-product: should I split this card per Product?
Yes if your Products map to separate engineering teams. Use vortex_iq.product_filter to scope per-Product panels.