The individual conversations rated negatively (1-2★) in the last 30 days, listed with customer, handling agent, topic tag, and the rating remark — the qualitative detail behind the CSAT number.
At a glance
Negative-Rated Conversations is a customer-satisfaction metric tracked from your Intercom workspace. Where CSAT and CSAT Trend give you the number, this card gives you the evidence: a table of the real conversations a customer scored 1 or 2 stars, with the remark they left. For the Blitz support lead this is the most actionable card in the satisfaction set — every row is a named customer, a recoverable relationship, and a clue about what is going wrong. Worked weekly, it turns CSAT from a scoreboard into a queue of follow-ups.
| What it counts | Each conversation with a negative conversation_rating (1 or 2 stars) in the last 30 days, one row per conversation. Columns typically include the customer/contact, the handling admin, the topic tag(s), the rating, the free-text remark, and a deep link back into Intercom. The card also surfaces concentration — how many negatives cluster on a single tag or topic. |
| Sample type | API-derived from the Intercom conversations endpoint. Vortex IQ filters on conversation_rating.rating ≤ 2 and enriches each row with the contact, assigned admin, and conversation tags. |
| Why it matters | A percentage cannot be coached or recovered — a specific conversation can. Reading the remarks tells you whether bad scores stem from shipping, sizing, refunds, tone, or slow replies, and which customers are worth a personal save. Five negatives on one tag is a process problem, not five unlucky days. |
| Reading the value | Scan for clustering first: if the alert has fired, several negatives share a tag or topic — start there. Then triage by customer value and recency. Each row is a to-do: reopen, apologise, fix, and where relevant route to the team that owns the underlying issue. |
| Currency | mixed (table: counts, ratings, and text remarks) |
| Time window | 30D |
| Alert trigger | >5 on one tag/topic |
| Sentiment key | — |
| Roles | owner, operations |
Calculation
Vortex IQ selects conversations whoseconversation_rating.rating is 1 or 2 within the last 30 days and builds one row per conversation, joining the contact, the handling/assigned admin, and the conversation’s tags. It then groups negatives by tag/topic; when more than five negatives share a single tag, the alert fires, flagging a systemic issue rather than scattered one-offs. There is no positive-share percentage here — this card is the raw, named list, deliberately qualitative so you can read intent and recover customers.
Worked example
A representative reading of Negative-Rated Conversations for Blitz. Over 30 days the table holds 14 negative-rated conversations. Triaged by tag, seven of them carrysizing and remarks like “boots ran a full size small, no help offered” and “had to ask three times for an exchange label.” That clears the >5-on-one-tag threshold and trips the alert. The pattern is not an agent problem — replies were prompt — it is a product-information and returns-policy problem. You do three things: reopen the seven sizing threads and offer free exchanges, brief the team on a standard sizing-and-exchange response, and flag the size-guide gap to the merchandising side of the business. The remaining seven negatives are scattered across tags and read as genuine one-offs, handled individually. To trace whether sizing complaints correlate with specific SKUs, open Vortex Mind; to ask “list this month’s 1-2★ conversations grouped by tag” in plain English, use Ask Viq.
Sibling cards merchants should reference together
| Card | Why merchants reach for it |
|---|---|
ic_csat_score | The headline number these rows explain — read the score, then read the words behind it. |
ic_csat_trend | When the trend bends down, this table is where you find out why. |
ic_csat_by_agent | Cross-check whether negatives cluster on one agent or are spread across the team. |
ic_top_tags | See whether a topic driving negatives is also a high-volume topic overall. |
ic_reopen_rate | Negatives plus reopens point to conversations closed before the customer was satisfied. |
Reconciling against the vendor’s own dashboard
Where to look in Intercom’s own dashboard: In Intercom, open the Inbox and apply a filter on conversation rating set to the negative scores (1-2★), date range last 30 days. That gives you the same list of conversations. The Reports → Customer satisfaction view shows the negative share and lets you click through to the underlying threads and read each remark. Why the Vortex IQ value may legitimately differ:| Reason | Direction | What to do |
|---|---|---|
| Negative threshold. Vortex IQ treats 1-2★ as negative; if your workspace uses a 3-point scale (good/ok/bad) or counts 3★ as negative, row counts will differ. | Variable | Confirm which ratings your workspace classifies as negative. |
| Tag attribution. A conversation may carry several tags or none; how negatives group depends on tagging discipline, which differs from Intercom’s own grouping. | Variable | Audit tagging consistency before reading the clustering. |
| Rating-date vs conversation-date. Vortex IQ lists by rating submission date; an Inbox filter may key off conversation created/updated date, shifting a row in or out at the window edge. | Marginal | Align the date basis. |
| Time zone. Workspace time zone vs merchant reporting time zone can move a borderline row across the 30-day boundary. | Marginal | Confirm time-zone match. |
delivery, refund, or stock, pivot to the cross-channel cards — Complaints on Out-of-Stock SKUs and Support Spike on Failed Payments — to see whether a commerce or payment problem is generating the bad scores. For divergence investigations, use Vortex Mind.