CX-05 · Customer Complaint & Feedback Management

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Process Flow Diagram (BPMN)

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L4 Process Steps

Step	Step Name	Role / Swim Lane	System	Input	Output	KPI	Dec?	Exc?
Phase 1 1.1	Capture complaint from all omni-channel sources	CRM Integration Platform	Salesforce Service Cloud	Customer contact via email, web form, phone, app, or social media	New case record created with source channel tag and PNR/loyalty reference	Case capture rate 100%; average intake time <2 min per case	N	N
1.2	Auto-classify complaint type and urgency tier	AI Classification Engine	Salesforce Einstein AI (within Service Cloud)	Case text, channel, booking reference, loyalty tier flag	Complaint category tag (delay, baggage, crew, billing, accessibility), urgency tier P1–P4	Auto-classification accuracy ≥85%; misclassification rate <5% (validated via monthly QA sample)	N	Y
1.3	Screen for regulatory and safety escalation triggers	Compliance Screening Agent	Salesforce Service Cloud + CAPA Tool (internal quality management)	Classified case with urgency tier	Safety flag Y/N; DOT/regulatory escalation trigger Y/N; CAPA record opened if required	100% of safety-tagged cases escalated within 15 min; DOT disability/discrimination complaints acknowledged within 24 hours (Part 259 mandate)	Y	Y
1.4	Assign case to team and set SLA clock	Case Routing Engine / Customer Care Team Lead	Salesforce Service Cloud	Complaint category, urgency tier, regulatory flag, agent availability	Case assigned to agent or specialist queue; SLA deadline set and clock started	First-assignment accuracy ≥92%; reassignment rate <8%; queue assignment time <5 min	N	N
Phase 2 2.1	Retrieve booking and full interaction history	Customer Care Agent	Amadeus Altéa PSS + Salesforce Service Cloud	PNR reference or loyalty number extracted from case	Full booking itinerary, prior complaint interactions, current loyalty tier status	History retrieval time <30 sec; data completeness ≥98% of cases with valid PNR	N	N
2.2	Validate complaint facts against operational records	Customer Care Agent	Amadeus Altéa PSS + SITA WorldTracer	Booking history, delay codes from OCC, baggage scan log	Verified complaint facts with supporting operational evidence attached to case	Validation completion within 4 hours of case creation; evidence attach rate ≥95% of cases	N	Y
2.3	Code root cause category for the complaint	Customer Care Specialist	Salesforce Service Cloud + Tableau	Verified complaint facts, operational evidence, delay reason codes	Root cause code applied (OTP failure, crew behavior, baggage mishandled, ancillary billing error, etc.)	Root cause coding accuracy ≥90% (validated via monthly QA review of 5% sample); uncoded case rate <2%	Y	N
2.4	Escalate complex cases to specialist team	Senior Customer Care Specialist / Legal / Safety Team	Salesforce Service Cloud	Complex case flag from root cause coding step	Case transferred to specialist queue with priority flag and investigation notes	Escalation acknowledgment within 2 hours; escalation rate <15% of total monthly cases	N	Y
Phase 3 3.1	Determine resolution type and compensation eligibility	Customer Care Agent	Salesforce Service Cloud + ATPCO Fare Rules Engine	Root cause code, customer loyalty tier, fare class, applicable regulatory entitlement (EU261, DOT)	Resolution recommendation: apology, miles award, travel voucher, cash refund, or re-accommodation	Resolution first-contact rate ≥65%; compensation accuracy ≥98% vs. entitlement rules	Y	N
3.2	Post miles or issue electronic voucher compensation	Customer Care Agent	Amadeus Altéa Loyalty + Salesforce Service Cloud	Approved compensation type (miles quantity or voucher value) from step 3.1	Miles credited to loyalty account or e-voucher code issued and emailed to customer	Miles posting time <24 hours; voucher delivery <4 hours; posting error rate <0.5%	N	Y
3.3	Process cash refund via PSS and finance system	Customer Care Agent / Finance Operations Team	Amadeus Altéa PSS + SAP S/4HANA Finance (FI/AR)	Approved refund amount, original payment method, fare rules confirmation	Refund transaction initiated in PSS; AR credit note posted in SAP; customer confirmation sent	Refund processing time ≤7 business days for credit card purchases (DOT mandate); refund error rate <1%	N	Y
3.4	Draft, approve, and send customer response	Customer Care Agent / QA Reviewer	Salesforce Service Cloud (email template library + approval workflow)	Case facts, resolution decision, compensation confirmation	Approved response letter sent to customer via preferred channel	First response time ≤24 hours (P1), ≤72 hours (P2); post-response CSAT ≥4.2/5.0	N	N
Phase 4 4.1	Confirm customer acceptance or re-open case	Customer Care Agent	Salesforce Service Cloud	Customer reply or no-reply after 7-day post-response wait window	Case closed (accepted) or re-opened with escalation note and priority uplift	Re-open rate <12%; closure on first resolution ≥65%; external escalation (DOT/BBB) rate <0.5% of cases	Y	Y
4.2	Log case outcome and enrich customer CRM profile	CRM System / Customer Care Agent	Salesforce Service Cloud + Amadeus Altéa PSS	Closed case with full resolution details and compensation record	Updated customer interaction history; CRM profile enriched with complaint category, root cause, and resolution	Profile update completion rate 100%; CRM data quality score ≥95% (measured via monthly data audit)	N	N
Phase 5 5.1	Aggregate complaint data for trend analysis	Customer Insights Analyst	AWS Redshift + Tableau	Closed case export with root cause codes, compensation amounts, resolution times, and SLA outcomes	Weekly complaint trend dashboard; top-10 root cause report; SLA compliance summary	Dashboard refresh ≤24 hours after week close; root cause coverage ≥95% of closed cases	N	N
5.2	Measure NPS and CSAT from post-resolution survey	Customer Insights Analyst	Medallia	Closed cases with valid customer email and consent flag	NPS score, CSAT score per complaint category, verbatim feedback themes	Survey response rate ≥15%; complaint-handling NPS ≥+30; complaint CSAT ≥4.0/5.0	N	N
5.3	Route VoC insights to operational improvement owners	Process Improvement Manager / VoC Program Lead	Salesforce Service Cloud + Jira (improvement backlog tracking)	Weekly trend report, NPS/CSAT data, top root causes with frequency and cost impact	Improvement action items created in Jira, assigned to owning departments (OCC, Crew, Baggage, IT); revised SLA targets where warranted	≥80% of top-10 root causes have assigned improvement owner within 5 business days of report publication	Y	N

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Process Attributes

Identification

Process IDCX-05

L1 DomainCustomer Experience & Loyalty

L2 ProcessCustomer Experience Operations

L3 NameCustomer Complaint & Feedback Management

L4 Steps17 across 5 phases

Decision Gates5 (all with iteration loops)

Exceptions7 documented

Swim Lanes (Roles)

CRM Integration Platform

AI Classification Engine

Compliance Screening Agent

Case Routing Engine / Customer Care Team Lead

Customer Care Agent

Customer Care Specialist

Senior Customer Care Specialist / Legal / Safety Team

Customer Care Agent / Finance Operations Team

Customer Care Agent / QA Reviewer

CRM System / Customer Care Agent

Customer Insights Analyst

Process Improvement Manager / VoC Program Lead

Systems & Tools

Salesforce Service CloudSalesforce Einstein AI (within Service Cloud)Salesforce Service Cloud + CAPA Tool (internal quality management)Amadeus Altéa PSS + Salesforce Service CloudAmadeus Altéa PSS + SITA WorldTracerSalesforce Service Cloud + TableauSalesforce Service Cloud + ATPCO Fare Rules EngineAmadeus Altéa Loyalty + Salesforce Service CloudAmadeus Altéa PSS + SAP S/4HANA Finance (FI/AR)Salesforce Service Cloud (email template library + approval workflow)Salesforce Service Cloud + Amadeus Altéa PSSAWS Redshift + TableauMedalliaSalesforce Service Cloud + Jira (improvement backlog tracking)

Key Performance Indicators

Capture complaint from all omni-channel sourcesCase capture rate 100%; average intake time <2 min per case

Auto-classify complaint type and urgency tierAuto-classification accuracy ≥85%; misclassification rate <5% (validated via monthly QA sample)

Screen for regulatory and safety escalation triggers100% of safety-tagged cases escalated within 15 min; DOT disability/discrimination complaints acknowledged within 24 hours (Part 259 mandate)

Assign case to team and set SLA clockFirst-assignment accuracy ≥92%; reassignment rate <8%; queue assignment time <5 min

Retrieve booking and full interaction historyHistory retrieval time <30 sec; data completeness ≥98% of cases with valid PNR

Validate complaint facts against operational recordsValidation completion within 4 hours of case creation; evidence attach rate ≥95% of cases

Code root cause category for the complaintRoot cause coding accuracy ≥90% (validated via monthly QA review of 5% sample); uncoded case rate <2%

Escalate complex cases to specialist teamEscalation acknowledgment within 2 hours; escalation rate <15% of total monthly cases

Airline-Specific Risks & Pain Points

Fragmented channel ingestion creates duplicate cases during IROPS spikes; Sprinklr social volume can exceed 5,000 mentions/hour post-disruption, overwhelming manual deduplication

Multi-language free-text complaints require NLP models retrained quarterly; incorrect urgency triage causes P1 DOT-reportable cases to sit in general queue breaching 24-hour SLA

DOT Part 259 requires written response to disability and discrimination complaints within 30 days — missed SLAs expose airline to civil penalties up to $27,500 per violation per passenger

Staffing gaps during IROPS cause queue backlog exceeding 10x normal volume; SLA clock runs regardless of staffing levels — unmanaged queues result in mass SLA breaches during weather events

Loyalty tier data sync between Altéa and Salesforce has a 15-min replication lag — agents may not see tier upgrades applied post-flight, causing incorrect resolution offers to premium members

Baggage scan data in SITA WorldTracer is incomplete for interline segments handled by third-party ground handlers — evidence gaps reduce resolution quality and increase re-open rate

Inputs / Outputs

Primary InputCustomer contact via email, web form, phone, app, or social media

Primary OutputImprovement action items created in Jira, assigned to owning departments (OCC, Crew, Baggage, IT); revised SLA targets where warranted

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