SystemLoyalty & Customer Experience

Airline NPS Verbatim Analysis

NPS verbatim analysis that names the aircraft, the seat and the team that fixes it

Every lost NPS point tied to its cause, the flights behind it and the team that fixes it.

See one case, screen by screen ↓
demo61,284commentsread in September in 11 languages: every comment, not a sample
demo41sfor the agents to answer why business NPS fell 11 points on ORD–LHR, in 7 steps
demo−5.6NPS pointstraced to business seats that will not go flat on two aircraft, proved by 17 technical-log write-ups
target100%of NPS drops of 4+ points tied to a cause with an owner within 5 business days
In short

What is Airline NPS Verbatim Analysis?

NPS verbatim analysis, also called NPS comment analysis, reads the open comments behind Net Promoter Score survey answers to explain why the score moved. Airline NPS Verbatim Analysis does it for airlines: eight agents read every post-flight survey comment the night it arrives, match it to the flight, aircraft, seat and loyalty tier, rank the causes by the NPS points each one cost, and prove each in the airline's records. The insight analyst decides what goes to which owner.

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Updated

The problem

Why NPS verbatim analysis stops at topics, not causes

Most NPS verbatim analysis at an airline, like most open-ended survey analysis, is still a sample and a topic tree. A post-flight survey goes out 24–48 hours after arrival, tens of thousands of comments come back each month in many languages, and senior managers read a handful a day. The rest go through survey text analytics that tags them “seat” or “food” against a topic list analysts keep by hand, so a new problem goes uncounted until someone adds a rule. Joining a response to the operating tail, the seat or the catering load is a warehouse project most programs never finish.

So the monthly deck explains the score with a word cloud and a few quotes, and NPS driver analysis, where it is done at all, runs on touchpoint ratings rather than on the comments. It cannot say which aircraft, which seat, or that the technical log already has the write-up. A route-cabin score swings by ±8 to ±11 points on a few hundred responses, so teams chase noise or miss a real drop. Nobody puts the premium revenue at risk next to the cause, the owner hears about it by email, if at all, and nobody measures whether the fix moved the score.

typical10commentsor videos, randomly selected, that a large carrier's senior managers review each day
typical$8.2Ba yearone US network carrier received from its co-brand card partner in 2025 — the members behind the score
Where a month's NPS insight days goestimated
By hand15 days
With the solution1.6 days
  • Joining responses to flights, aircraft, seats and tiers3 → 0.1 d
  • Tagging comments and keeping the topic list up to date4 → 0.3 d
  • Reading samples and pulling quotes2 → 0.3 d
  • Checking which changes are real, not noise1 → 0.1 d
  • Proving a cause in operations records2 → 0.3 d
  • Building the report and briefing owners3 → 0.5 d

Estimated split for one month's insight report at a network carrier's CX insight team, by hand and with the solution.

How it works

How a question becomes a fix

Eight agents read every comment, find and prove the causes, check each other and brief the owner; the analyst decides.

What comes in
Comments in61,284 a month · surveys in 11 languages, matched to flights
Agents at work
Comment readerevery comment
Flight matcherflight, aircraft, seat, tier
Then
Cause finderthe cause ladder
Then
Operations linkerproves it in the records
Survey-quality agentreal or noise
Then
Revenue-at-risk agentpremium members
Hand-off writercited brief, measured fix
A person decides
Customer Insight Analystasks back, accepts, rejects, sends
What comes out
Cause proved
Owner briefed
Fix measured
One case, step by step

NPS verbatim analysis on one route, screen by screen

Corvane Airways read 61,284 post-flight survey comments in September. Overnight, the agents flag that business-cabin NPS on Chicago O'Hare–London Heathrow fell from +42 to +31. Here is how Talia Brennan, the insight analyst for long-haul, works it through with the agents, from the question to a cited brief in Maintenance's hands.

  1. 01Friday morning

    One new change that needs her

    Talia Brennan · Customer Insight Analyst, long-haul

    The agents read 2,148 new comments overnight. Talia's Today screen shows network NPS at +34, −2 against August on 186,412 surveys, 61,284 comments read in September, and 5 things waiting for her. At the top of what the agents found: business, ORD–LHR fell 11 points, n = 412, beside five older findings: three already sent to owners, one piece of good news and one to watch.

    “Business, ORD–LHR fell 11 points · Seats that will not go flat on 2 aircraft · Found today 05:52, as late September surveys arrived.”

  2. 02Overnight

    Only real changes, with their range

    Change watcher

    The change watcher tested 1,128 route, cabin and tier cells. A change is shown only when it is at least 4 points, outside the 95% range and on at least 50 responses. Five changes qualify; Economy on MIA–GRU, down 5, does not, and is labeled “watch, not a change”.

    “A fall of 5 inside a range of ±14.5 at n = 233. The agents will look again when October closes.”

  3. 0309:02

    “Why did business-cabin NPS fall on ORD–LHR in September?”

    Talia Brennan asks why

    She asks in plain words, and five agents go to work in view. They read 412 responses and 371 comments in 4 languages with names masked, match every response to its flight and tail and 409 to a seat, group 87 detractor comments into causes with no fixed list, check each cause against the technical log, inventory, catering load plan, facilities and on-time data, and price the risk from Platinum and Gold members.

    “Matched each response to flight, tail, seat and tier — all 412 to flight and tail; seat 409 (3 had no record locator).”

  4. 0441 seconds later

    A ladder of causes, ranked by NPS points

    Cause finder

    Four causes explain most of the fall. The largest: business seats that will not recline or go flat, 38% of detractor comments (33), −5.6 points, 94% confidence, proved by records. Then the first meal choice gone before the last rows (−2.3), a crowded temporary lounge at ORD (−1.5, possible) and late arrivals on CV 971 (−1.1). Each rung opens to the passengers' own words, with score, tier, flight, date, tail and seat — a Spanish comment beside its translation.

    “Seat 3A would not go flat. Crew moved me twice and the second seat stuck halfway too.” — Platinum, score 2, CV 972, Sep 14, N812CV

  5. 05See the proof

    From one comment to the technical log

    Operations linker

    The proof follows a comment to its reservation, flight, aircraft and technical-log entry. Business NPS by aircraft splits the route: N812CV −1 and N814CV +13, with 5 and 6 seats placarded INOP, against +45 to +49 on the other four 787-9s. Together the two tails score +6 against +47. The recline actuator, CS-ACT-2210, is back-ordered to Oct 28, and the placarded seats were sold and flown 23 times in September.

    “Read-only. The agents never change a technical-log entry or a deferral.”

  6. 06Second reader

    Real, but only just — and one cause marked possible

    Survey-quality agent

    A second agent checks every answer before Talia relies on it. The fall of 11 is outside its ±10.9 range, z = 1.98, and the seat cause does not depend on it. Platinum members answer at 11.8% against 3.1% for non-members; 38 of 412 responses came from two disrupted CV 971 flights, and without them the fall is −9. The lounge rung has only 12 comments and a closure that ends Oct 30, so it is marked possible.

    “Operations linker → cause finder: 4 of the 33 seat comments came from other aircraft with no technical-log entry. Kept as comments, not as proof.”

  7. 07Ask back

    “Only Platinum and Gold” — the ladder re-runs

    Talia Brennan · Customer Insight Analyst

    Talia narrows the question with one click. The cause finder re-runs it for Platinum and Gold only: +40 → +22, −18 on 187 responses, and seats are an even bigger share of their detractor comments at 44%. The survey-quality agent confirms the fall is outside its ±16.2 range on the smaller sample, and the revenue at risk stays $2.5M a year.

    Ask back: “Is it only those two aircraft?” · “Exclude the two disrupted flights” · “When will the seats be fixed?” · “What is at risk if we don't fix it?”

  8. 08Revenue at risk

    What the cause costs, with the inputs shown

    Revenue-at-risk agent

    Four hundred seventeen Platinum and Gold members flew business on N812CV and N814CV in September, spending $15,600 each a year with Corvane. Corvane's own history says members who score 0–6 cut next-year spend by 38%, so $2.5M a year is at risk, estimated. The five largest open causes come to $6.1M a year. Members are never contacted by the agents; a recovery list goes to Loyalty only if someone approves it.

    417 members × $15,600 × 38% = $2.5M a year at risk (estimated).

  9. 09Approve and send

    A cited brief to Maintenance, sent only when she approves

    Hand-off writer

    The hand-off writer drafts the brief to Dale Hutchins in Cabin Interiors Engineering, cc Renee Castillo, Product Manager, Cabin: 21 detractor comments from Platinum and Gold members (44%), 17 write-ups, 11 seats placarded INOP, and the ask — replace recline actuators on 11 seats. The measure: business NPS on the two tails back to the other tails within 6 weeks of the fix. Reply due Fri, Oct 23, five business days. Talia reads it and clicks Approve and send.

    “Attached: evidence pack (21 masked comments, 17 technical-log write-ups, inventory extract). Passenger names never leave this solution.”

  10. 10Tracked to the fix

    Every cause on a reply clock, then measured

    Hand-off writer

    Owners shows every hand-off: the seat brief sent, reply due Oct 23; the meal brief ready for Gwen Talbot in Inflight Catering; Loyalty Operations two days late on the Meridale miles, with a Nudge; DEN station's reply due today; and Digital's agreed fix for the upgrade list in release 7.14 on Oct 22. After a fix, the agents measure NPS on exactly the affected flights and propose closing or reopening the cause.

    “The hand-off writer sends nothing until you approve the brief, and never closes a cause on its own.”

Who it’s for

Built for everyone who answers for the score.

The same NPS drop, seen by the four people who carry the voice of the customer at the airline — what their month looked like, and what it looks like now.

TB
Talia BrennanCustomer Insight Analyst · lead for long-haul
Customer Insight Analyst
Before
“Don't give me a word cloud. Tell me which aircraft.” Answers every why question from cabin, airports, digital and loyalty with samples, a topic tree and a monthly deck.
Now
Asks why in plain words, gets a ladder of causes proved by records and checked by a second agent, asks back, and sends a cited brief she has approved.
ME
Marcus ElleryHead of Customer Experience · signs the monthly report
Head of Customer Experience
Before
“If we know the cause, I want a name and a date next to it.” Reports NPS to the CCO and the board, and chases owners by email.
Now
Reads a monthly report the agents draft with every number cited, sees each cause's owner, reply clock and measured effect, and is the only one who can sign.
RC
Renee CastilloProduct Manager, Cabin · business seat, menus, amenity kit
Product Manager, Cabin
Before
“Show me whether it's the product or the aircraft before you send it to me.” Gets seat complaints with no tail, no seat and no write-up.
Now
Is copied on the Maintenance brief that shows the seat problem sits on two tails, not the seat product — and gets good news explained too.
DH
Dale HutchinsManager, Cabin Interiors Engineering · TechOps
Cabin Interiors Engineering
Before
“Give me the tails and seat numbers, and I'll give you a date.” Hears about seat complaints without the tails, the seat numbers or the write-ups.
Now
Receives the tails, the 11 seats, the 17 write-ups and the passengers' words in one brief, with a measure and a reply date.
Built on the engine

8 agents. Each with one job, and hard limits.

Eight agents read every comment, find and prove the causes, check each other and brief the owner; the analyst decides.

Comment reader

Reads every survey comment the night it arrives in 11 languages, keeps the original beside the translation, splits it into statements, masks names and contact details, and routes complaint-like comments.

  • Never answers a passenger
  • Complaints under 14 CFR 259.7 and disability complaints under 382.155 go to Customer Relations untouched
Flight matcher

Joins each response to its flight, date, operating aircraft, seat after any reseat, cabin, fare and loyalty tier.

  • Read-only
  • Marks a response unmatched rather than guess
Cause finder

Groups statements into causes in plain words, attributes the NPS change to each, writes the cause ladder with the remainder kept as mixed or unexplained, and re-cuts it on request by tier, aircraft or flights.

  • New causes need an analyst's approval
  • Never sends anything
Operations linker

Confirms or rejects each cause against the airline's records: technical log and deferrals, seat inventory, catering load plans and run-out reports, on-time data, facilities notices, app releases and loyalty suspense.

  • Read-only; never edits a record
  • Says “no record found” when there is none
Survey-quality agent

Second reader on every answer: the change against its 95% range, response-rate skew by tier, disrupted flights and language coverage, working from the ISO 20252:2019 disclosures.

  • Can mark a cause possible or a change “watch”, never delete one
  • Disagreements go to a person, with both views
Change watcher

Tests every route, cabin and tier cell each night against the thresholds and raises only real changes.

  • Alerts only outside the range
  • Changes inside it are labeled “watch, not a change”
Revenue-at-risk agent

Prices each cause by the Platinum and Gold members it touched, their 12-month spend and the airline's own spend change after a 0–6 score, and shows the multiplication.

  • Estimates only, inputs shown
  • Never contacts a member; recovery lists go to Loyalty to decide
Hand-off writer

Drafts the cited brief to the owning team, tracks the reply clock, proposes a nudge when an owner is late, and measures NPS on the affected flights after the fix.

  • Sends only after an analyst approves
  • Never closes a cause on its own
Analyst and Head of CX

Decide, send and sign. The agents propose; a named person decides.

Ask in plain words

Ask about any route, cabin, tier or aircraft

Ask from any screen, in plain words. Every answer cites its source, and anything it proposes waits for your approval.

Why did business-cabin NPS fall on ORD–LHR?

From +42 to +31 in September (n = 412; range ±10.9). The biggest cause: business seats that will not go flat on N812CV and N814CV, 38% of detractor comments and −5.6 points. The technical log has 17 seat write-ups and 11 seats placarded INOP on those two aircraft. Then the meal choice running out (−2.3) and the ORD temporary lounge (possible).

Which causes put the most premium revenue at risk?

Estimated, from Platinum and Gold members: seats on N812CV and N814CV $2.5M a year, Meridale miles $1.8M, upgrade list $1.1M, meal choice $0.4M, DEN boarding $0.3M. $6.1M in all.

Send the meal cause to Inflight Catering

I drafted the brief for Gwen Talbot: 18 detractor comments (21%), −2.3 points; load plan LP-ORD-J-0901 cut entrées from 34 to 30 per flight. Asked: restore 34 or open pre-order. Please review and approve; nothing is sent before you do.

Is the Platinum drop real or survey noise?

Real. Platinum NPS fell from +46 to +42 on 9,214 responses; the 95% range is ±2.3, so 4 points is outside it. 29% of Platinum detractor comments name the upgrade and standby list that app release 7.12 moved on Sep 3. Digital agreed a fix for Oct 22.

Every screen

The working solution, as it ships.

13 screens from the working solution, on its sample data. Pick one to see it large.

TodayThe insight analyst's morning: network NPS, every post-flight survey comment read, the significant NPS changes the agents found overnight and what is waiting for a decision.
ChangesOnly real NPS changes by route, cabin and tier, each with its range, sample and top cause — and the one inside the noise labeled watch.
The agents at workAsk why in plain words and watch the agents read the comments, match them to flight, tail and seat, group causes and check the records.
The cause ladderNPS driver analysis from the comments themselves: a ladder of causes ranked by NPS points, each proved by records and opened to the passengers' own words.
The proofFrom one comment to the technical log: NPS by aircraft, the seats placarded INOP and the part on back-order.
Survey qualityThe NPS margin of error, response rate by tier, disrupted flights, languages and where the agents checked each other.
Ask backOne click re-runs the analysis for Platinum and Gold members only, with the second reader's note on the smaller sample.
Revenue at riskPremium revenue at risk on each cause, with the members touched, their spend and the inputs of the estimate.
The brief to the ownerThe cited brief to Maintenance: the evidence, the ask, the measure and the reply date, sent only when the analyst approves.
OwnersClosed-loop feedback: every cause sent to its owning team, the reply clock, the agreed fix and the effect measured after it.
CommentsAirline customer feedback analysis at the source: every post-flight survey comment in the passenger's own words, matched to flight, aircraft, seat and tier, with names masked.
The monthly reportThe monthly NPS insight report the agents draft with every number cited, reviewed by the analyst and signed by the Head of CX.
Your thresholdsMinimum responses, confidence for a real change, the smallest change to alert on and when a cause counts as possible.
Governance

Built for trust in every number: cited, checked, decided by a person.

Every number cited to its comment or recordEvery number and every agent statement carries a source — a comment, a reservation, the technical log, a load plan or the survey frame — and one click opens the passage with the system and the time.
A second agent checks every answerThe survey-quality agent tests each change against its 95% range, response-rate skew and disrupted flights, marks weak causes possible, and shows any disagreement to a person with both views.
A person decides every causeThe analyst accepts, rewords or rejects each cause. A rejection needs one of five reason codes — known and time-limited, outside our control, coincidence, survey artifact, already fixed — and new causes count only once an analyst approves them.
Nothing reaches an owner unapprovedThe hand-off writer sends a brief only after the analyst approves it and never closes a cause. Only the Head of Customer Experience can sign the monthly report; analysts can edit until it is signed.
Passengers protectedNames and contact details are masked in quotes, a privacy setting the solution ties to CCPA/CPRA and GDPR; member lists show tier, not member number, and comments and evidence are kept 25 months. Complaints in comments go to Customer Relations untouched under 14 CFR 259.7 and 382.155; the agents never answer a passenger.
Every step on the audit trailEvery agent step and every person's decision — question, re-cut, cause proved, brief sent, feed failure — is on an audit trail that cannot be edited, with filters, search and CSV export.
Configuration

Your thresholds, your owners, your privacy rules

What counts as a real change, who owns each cause and how long they have to reply are settings, applied tonight and on the audit trail.

SettingDefaultChoose from
Minimum responses to show a score50Step up or down by 10; cells below show “too few responses”
Confidence for a real change95%Step up or down one point; the change must fall outside this range
Smallest change to alert on4 NPS pointsStep up or down one point; a preview names the changes that would drop out
Below this confidence a cause is “possible”75%Step up or down by 5, for the survey-quality agent
Reply clock5 business daysStep up or down a day; the Head of CX is told after 2 more days
Owner routingCause family → owning teamAircraft and cabin · Food and drink · Airport · Digital · Loyalty · Punctuality · Complaint — change each one
Mask passenger names and contact details in quotesOnOn · Off; for CCPA/CPRA and GDPR, quotes show tier, flight and seat, never a name
Keep comments and evidence25 monthsThen deleted, with the audit trail kept
Connections

Works with the systems the survey and the flight already run on

Survey platformpost-flight surveys, scores and comments in 11 languages
Reservations and departure controlthe flight, the seat after any reseat, cabin, fare and tier
Technical log and seat inventorywrite-ups, deferrals and seats placarded INOP
Flight operationson-time data and the operating aircraft
Catering, facilities and app releasesload plans and run-out reports, lounge notices, release notes
Loyalty and the owner directorytiers and member spend; 38 owning teams and their people
What it changes

The difference, in numbers.

Every figure is labelled: a target the solution is built to, an estimate, a typical published result, or a proven one.

target
100%
of NPS drops of 4+ points tied to a cause with an owner in 5 days
every drop
cause, owner, date
estimated
2.5$M
a year of premium revenue at risk found on one route's seat cause
Members' spend$6.5M
At risk$2.5M
target
100%
of comments read the night they arrive, not a sample of ten a day
Sampled today≈ 10 a day
With agents61,284 a month

“demo” = seen in the working solution, on its sample survey data · “target” = the design goal, measured in the live solution · “estimated” = our estimate · “typical” = published figures (a 2024 vendor case study of a large Latin American carrier's survey program — senior managers review 10 randomly selected comments or videos a day; Reuters, 2025 — about $8.2B from a co-brand card partner at a US network carrier). 14 CFR 259.7, 14 CFR 382.155, CCPA/CPRA, GDPR and ISO 20252:2019 are named as context only. NPS is a registered trademark of Bain & Company, Satmetrix and Fred Reichheld, used here descriptively. Corvane Airways, Meridale Air and the people named on this page are fictional — characters and sample data in the working solution.

Questions

What CX teams ask about NPS verbatim analysis.

What is NPS verbatim analysis?

NPS verbatim analysis, also called NPS comment analysis, reads the open comments behind Net Promoter Score survey answers to explain why the score moved. Airline NPS Verbatim Analysis does it for airlines: eight agents read every post-flight survey comment the night it arrives, match it to the flight, aircraft, seat and loyalty tier, rank the causes by the NPS points each one cost, and prove each in the airline's records. The insight analyst decides what goes to which owner.

How is NPS root cause analysis different from NPS text analytics?

NPS text analytics tags topics: “seat” or “food”. Here a cause is proved by a record: on the sample route, 33 seat comments lead to 17 technical-log write-ups and 11 seats placarded INOP on two aircraft. Nobody keeps a fixed topic tree; the agents suggest new causes in plain words and an analyst approves, renames or rejects them.

How do you know if an NPS change is statistically significant?

Every change is shown with its 95% range. The change watcher raises a change only when it is at least 4 points, outside the range and on at least 50 responses, and the survey-quality agent checks every answer for response-rate skew by tier and disrupted flights. A fall inside the range is labeled “watch, not a change”.

Can post-flight survey analysis tie a comment to the flight, aircraft and seat?

Yes. The flight matcher joins each response to its flight, date, operating aircraft, seat after any reseat, cabin, fare and tier from reservations, departure control and flight operations. A response with no matching record is marked unmatched, never guessed.

Is a survey comment ever a complaint under 14 CFR 259.7?

It can be. A comment that describes a specific problem is routed to Customer Relations untouched, and disability complaints under 14 CFR 382.155 too. The agents never answer a passenger.

How does it put a dollar figure on an NPS drop?

The revenue-at-risk agent counts the Platinum and Gold members a cause touched, their 12-month spend and the airline's own spend change after a 0–6 score, and shows the multiplication. On the sample route: 417 members × $15,600 × 38% = $2.5M a year at risk, labeled estimated.

Do people stay in control?

Yes. The analyst accepts, rewords or rejects every cause, with a reason code for a rejection, and approves every brief before it is sent. The Head of Customer Experience signs the monthly report. The agents never contact a passenger or member, never change an operational record and never close a cause.

How long does it take to go live?

The Agentic Solution Engine builds and deploys it from your requirements and documents — your survey program, owner directory and a month of past comments — and it goes live once every quality gate has passed. A first-time setup connects the sources and ends with a test question the agents answer end to end on last month's data.

See it on
your survey comments.

We'll run Airline NPS Verbatim Analysis on a month of your own post-flight survey comments and the flights behind them.