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Card class: HeroCategory: Customer support
Minutes to first admin reply (conversation.statistics.time_to_admin_reply), median over the window.

At a glance

Median First-Response Time answers the question customers care about most: “how long until a human replies?” For every conversation in the window, Intercom records the minutes from the customer’s first message to the first agent reply (conversation.statistics.time_to_admin_reply). This card reports the median of those — the typical experience, not the average that one stray all-nighter can distort. Blitz’s support lead uses it as the headline speed metric; the founder reads the week-over-week arrow to know whether the desk is getting faster or slower.
What it countsThe median of conversation.statistics.time_to_admin_reply (minutes from conversation open to first admin reply) across all conversations that received a first reply in the window.
Sample typeAPI-derived. Computed by Vortex IQ from the per-conversation statistics Intercom exposes on the Conversations API.
Why it mattersResponse speed is the strongest single lever on CSAT and the first thing a customer judges. The median is the honest “typical wait”; tracking it week-over-week tells you whether staffing, routing or volume changes are helping or hurting before customers complain.
Reading the valueLower is better, shown in minutes with a comparison against the prior week. A rising median means customers are waiting longer for that first human reply. The alert fires above 240 minutes (4 hours).
Currencynumber
Time window7D vsP
Alert trigger>240 min
Sentiment keyfirst_response_time
Rolesowner, operations

Calculation

Vortex IQ reads conversation.statistics.time_to_admin_reply for every conversation that received its first admin reply during the last 7 days, then takes the median (50th percentile) of those values in minutes. The median is used deliberately: one conversation opened on a Friday night and answered Monday morning would skew an average wildly, but barely moves the median. The card displays the current 7-day median alongside the previous 7-day period (vsP) so direction is visible at a glance. Office hours configured in Intercom are honoured, so overnight gaps do not unfairly inflate the figure.

Worked example

A representative reading of Median First-Response Time for Blitz. This week the median reads 3h 40m (220 minutes), up from 1h 5m last week, with the arrow pointing the wrong way — and it is creeping toward the 240-minute alert line. CSAT has dipped two points in parallel. The support lead pulls First-Response Time by Team and finds the returns team’s median has ballooned to over six hours while live chat is unchanged. The cause: a teammate left and returns are now triaged by one person who batches them twice a day. The fix is to re-route returns or add cover, not to push the whole team. The lead rebalances the queue and the median drops back under 90 minutes next week. To see which conversations dragged the median, open Resolution Time by Agent and CSAT by Agent; to ask in plain English, try Ask Viq “why did our first-response time slow down this week?”

Sibling cards merchants should reference together

CardWhy merchants reach for it
ic_first_response_by_teamBreaks the median down by team so you can see which queue is slow.
ic_sla_attainmentTurns the speed into a pass/fail share against your SLA target.
ic_unanswered_nowThe live conversations already past target — the worst tail of this distribution.
ic_resolution_time_medianFirst reply is only half the journey; this tracks time to close.
ic_health_scoreThe composite this speed metric feeds as its first-response input.

Reconciling against the vendor’s own dashboard

Where to look in Intercom’s own dashboard: Open Reports → Conversations → First response time. Intercom shows median and average first-response time there, with filters for team, channel and office hours. Match the report’s median (not mean) and its date range to compare against this card. Why the Vortex IQ value may legitimately differ:
ReasonDirectionWhat to do
Median vs mean. This card reports the median; if you read Intercom’s average instead, it will look higher.Intercom mean higherCompare median to median.
Office-hours setting. Both honour office hours, but if the Intercom report toggles “calendar time” or your office hours differ from the profile, the numbers move.VariableMatch office-hours / calendar-time settings.
Window edges. “7D vsP” uses rolling 7-day windows; an Intercom report on calendar weeks covers different conversations.VariableAlign the date range.
Reply definition. Only a genuine admin reply stops the clock; auto-messages and bot replies are excluded here.Vortex IQ higherCheck whether the Intercom report counts bot replies.
Cross-connector reconciliation: a sudden slowdown often coincides with a volume spike driven by a commerce or payment event — check Volume Spike and Support Spike on Failed Payments. For divergence investigations, use Vortex Mind.

Known limitations / merchant FAQs

Q: How often does Median First-Response Time update? It refreshes on the standard data refresh (typically every 30-60 minutes) as conversations accrue first replies through the day. Q: Why does my Intercom report show a different number? The two most common reasons are median versus average (this card uses the median) and office-hours / calendar-time settings. Align both before assuming a real divergence. Q: Does a bot or auto-reply count as the first response? No. Only a genuine admin reply stops the clock, so an auto-greeting does not artificially shorten the median. Q: Can I customise the alert threshold? Yes. The default fires above 240 minutes, but set it per profile in the Sensitivity tab to match the first-response SLA you promise customers.

Tracked live in Vortex IQ Nerve Centre

Median First-Response Time 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 or book a demo to see this metric running on your own data.