> ## Documentation Index > Fetch the complete documentation index at: https://docs.vortexiq.ai/llms.txt > Use this file to discover all available pages before exploring further. # Support Contacts per 100 Orders, Intercom > Cross-channel ratio of Intercom conversations created to commerce orders, normalised per 100 orders, compared to the prior period. How to read it, why it matters, and how to act on it. **Card class:** [Non-Hero](/nerve-centre/overview#card-classes-explained) • **Category:** [Cross-Channel: Revenue at Risk](/nerve-centre/connectors#connectors-by-type) > How many support conversations each 100 orders generates — the single best gauge of whether your operation is getting easier or harder to run. ## At a glance > **Support Contacts per 100 Orders** is a cross-channel revenue-at-risk metric that divides the Intercom conversations you created by the orders your commerce sibling processed, scaled to a per-100-orders rate. It is the contact-rate health check: a single number that strips out seasonality and growth so you can see whether each sale is costing you more or less support effort than before. A low, stable rate means the buying experience is self-explanatory; a rising rate means something — fulfilment, product pages, payments — is generating questions and complaints. The card only renders when an ecommerce-platform or marketplace sibling is connected, because the order count comes from there. | | | | --------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **What it counts** | Intercom conversations created in the window divided by (commerce sibling order count ÷ 100). The result is the number of support conversations generated per 100 orders, shown against the prior comparable period. | | **Sample type** | Derived. Intercom `conversations` created, divided by commerce sibling order count, normalised per 100 orders. Refreshed on the standard data refresh. | | **Why it matters** | Raw conversation volume always rises with sales, so it cannot tell you whether support is getting more or less efficient. Normalising per 100 orders removes growth and seasonality, exposing the real trend. A climbing rate is an early, leading indicator of an operational problem — and of rising support cost per sale — well before it shows up in CSAT or churn. | | **Reading the value** | Read the rate together with its direction versus the prior period. A flat rate as orders grow means support is scaling cleanly. A rise above the +25% trigger means each 100 orders now generates a quarter more contacts than before — investigate what changed. Lower is generally better, but a very low rate can also mean shoppers cannot find help. | | **Currency** | decimal | | **Time window** | `30D vsP` (30 days versus prior period) | | **Alert trigger** | `rise >25% vsP` | | **Sentiment key** | — | | **Roles** | owner, operations | ## Calculation The card counts Intercom conversations created in the trailing 30 days, divides by the commerce sibling's order count for the same window, and multiplies by 100 to express the result as conversations per 100 orders. It then compares that rate to the prior comparable 30-day period (`vsP`) and flags a rise above 25%. Because both numerator and denominator are pulled per period, growth and seasonal swings cancel out, leaving a clean efficiency trend. The `only_when` gate keeps the card hidden unless an ecommerce-platform or marketplace sibling supplies the order count for the denominator. ## Worked example *A representative reading of **Support Contacts per 100 Orders** for Blitz, the sports retailer.* Last period Blitz processed 4,000 orders and opened 320 conversations — a rate of 8.0 contacts per 100 orders, a number the support lead considers healthy for a sports retailer with sizing questions. This period orders rose to 5,200 (a strong month) and conversations rose to 572. Raw volume is up 79%, which on its own looks alarming. But the rate is 11.0 per 100 orders — a 37.5% rise versus prior, well past the +25% trigger. So the extra tickets are *not* just more sales: each 100 orders is now generating meaningfully more contacts. The support lead cross-references the topic mix and the out-of-stock-complaints card and finds a sizing-guide change drove a spike in "wrong size" returns. The founder reads the same card as a margin warning: support cost per order is climbing. Without normalisation, the raw 79% volume jump would have been written off as "we grew". To trace the cause, drill into the topic and stockout siblings; for natural-language exploration, ask Ask Viq "why did contacts per 100 orders rise this month". ## Sibling cards merchants should reference together | Card | Why merchants reach for it | | ---------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------- | | [`ic_volume_trend`](/nerve-centre/kpi-cards/intercom/conversation-volume-trend) | Conversation Intelligence sibling: see the raw volume this rate normalises. | | [`ic_top_tags`](/nerve-centre/kpi-cards/intercom/top-topics-tags) | Conversation Intelligence sibling: when the rate rises, the topic mix tells you which driver grew. | | [`ic_xc_complaints_on_oos`](/nerve-centre/kpi-cards/intercom/complaints-on-out-of-stock-skus) | Cross-channel sibling: stockout complaints are a common reason the rate climbs. | | [`ic_xc_support_spike_failed_payments`](/nerve-centre/kpi-cards/intercom/support-spike-on-failed-payments) | Cross-channel sibling: a payment fault inflates contacts per order. | | [`ic_csat`](/nerve-centre/kpi-cards/intercom/csat) | Executive sibling: a rising contact rate with falling CSAT confirms a real experience problem. | ## Reconciling against the vendor's own dashboard **Where to look in Intercom's own dashboard:** Intercom can give you the numerator but never the full ratio. In Reports → Conversations you can read new conversations created over a period, which is the count this card divides. Intercom has no view of your order count, so it cannot produce a per-100-orders rate — that normalisation depends on the commerce sibling supplying the denominator. If you want to sanity-check the numerator, match the Vortex IQ window to the same date range in Intercom's conversation report. **Why the Vortex IQ value may legitimately differ:** | Reason | Direction | What to do | | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- | --------------------------------------------------------------------------- | | **What counts as a "conversation".** Vortex IQ counts conversations created; Intercom reports may count by first-reply or include bot-only threads differently. | Variable | Confirm the conversation definition matches before comparing the numerator. | | **Order count basis.** The denominator depends on whether the commerce sibling counts gross, net of cancellations, or test orders. | Variable | Align the order-count definition with the commerce sibling card. | | **Window and time zone.** Vortex IQ uses a rolling 30-day window in the merchant reporting time zone; vendor dashboards may use calendar months or account time zone. | Variable | Match the period and time zone on both sides. | **Cross-connector reconciliation:** reconcile the denominator against the commerce sibling's order-count / total-orders card and the numerator against the Intercom conversation-volume card. A rate that moves while both inputs look stable points at a window-boundary mismatch. For divergence investigations, use Vortex Mind. ## Known limitations / merchant FAQs **Q: How often does Support Contacts per 100 Orders update?** The card refreshes on the standard data refresh (typically every 30-60 minutes for live integrations). Both the conversation count and the order count are re-pulled on that cycle. **Q: Why is the card hidden?** It is gated by `only_when`: without an ecommerce-platform or marketplace sibling there is no order count for the denominator, so the rate cannot be computed and the card stays hidden. **Q: Is a lower rate always better?** Usually — fewer contacts per order means a smoother buying experience and lower support cost per sale. But an unusually low rate can also mean shoppers cannot find your support entry points, so read it alongside CSAT and resolution metrics rather than in isolation. **Q: Can I customise the alert threshold?** Yes. The default alert fires on a rise greater than 25% versus the prior period; the threshold and the comparison period are configurable per profile in the Sensitivity tab to match Blitz's normal seasonal swing. *** ### Tracked live in Vortex IQ Nerve Centre *Support Contacts per 100 Orders* is one of hundreds of KPI pulses Vortex IQ tracks across Intercom and 70+ other ecommerce connectors. Nerve Centre runs the detection layer; Vortex Mind investigates the cause when something moves; Ask Viq lets you interrogate any number in plain English. [Start for free](https://app.vortexiq.ai/login) or [book a demo](https://www.vortexiq.ai/contact-us) to see this metric running on your own data.