NP-RM-07 · Ancillary Revenue Optimization

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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	Benchmark ancillary revenue vs. peer carriers	Ancillary Revenue Manager	OAG Schedule Analyser	IATA annual ancillary revenue survey, peer carrier 10-K filings	Ancillary benchmark report with gap analysis by product category	Ancillary revenue per passenger ≥ $35 (IATA LCC benchmark); report produced annually	N	N
1.2	Analyse ancillary product mix by revenue category	Ancillary Revenue Analyst	AWS Redshift	Amadeus Altéa PSS booking records, ancillary sales transaction log	Ancillary revenue decomposition: baggage, seat selection, F&B, insurance, partner referrals	Top-3 categories contribute ≥70% of total ancillary revenue; data refresh ≤24 hours	N	Y
1.3	Identify new ancillary product opportunities	Ancillary Revenue Manager	Amadeus SkyCAST	Benchmark gap analysis, passenger demand segmentation, route O&D traffic data	Ancillary product roadmap with prioritised opportunities and revenue potential estimates	Minimum 3 new ancillary product candidates identified per annual review cycle	Y	N
Phase 2 2.1	Configure ancillary service catalog in PSS	Revenue Management Systems Analyst	Amadeus Altéa PSS	Approved ancillary product roadmap, IATA EMD (Electronic Miscellaneous Document) standards	Active ancillary service catalog with SSR/OSI codes and EMD settlement rules configured	100% of approved ancillaries configured and testable in Altéa within 5 business days of sign-off	N	Y
2.2	Set dynamic pricing rules for seats and baggage	Ancillary Pricing Analyst	PROS RM	Historical ancillary demand elasticity data, booking curve by flight, load factor thresholds	Dynamic ancillary price ladders by product, route, and days-to-departure bucket	Elasticity model coverage ≥80% of O&D pairs; yield uplift ≥8% vs. static pricing baseline	N	N
2.3	Design fare family bundles with ancillary inclusions	Pricing Strategy Manager	ATPCO	Fare family structure, ancillary cost-to-serve data, competitive bundle benchmarks	Defined fare family tiers (e.g. Basic / Standard / Flex) with ancillary inclusion matrix filed in ATPCO	Bundle attach rate ≥40% of total bookings; bundle margin ≥ à la carte revenue equivalent	Y	Y
2.4	Validate ancillary offers in NDC API test environment	Distribution Systems Analyst	NDC API Gateway	Configured ancillary catalog, fare family bundle definitions from ATPCO	Validated NDC offer schema with ancillaries returned in AirShopping and OrderCreate responses	100% of ancillary products surfaced in NDC AirShopping response; NDC API error rate < 0.5%	Y	Y
Phase 3 3.1	Segment passengers for targeted ancillary offers	Customer Analytics Manager	AWS Redshift	Loyalty programme profiles, booking history, route type (leisure/business), fare class	Passenger micro-segments with propensity scores for each ancillary product category	Propensity model AUC ≥0.72 for top-3 ancillary categories; segments refreshed ≤24 hours before departure	N	Y
3.2	Configure real-time ancillary offer engine	Revenue Management Systems Analyst	Amadeus Revenue Management (NRM / AltéaRM)	Passenger propensity scores, dynamic price ladders from PROS RM, inventory availability	Personalised ancillary offer sets ranked by revenue contribution per passenger segment	Offer generation latency < 200ms per PNR; personalised offer conversion rate ≥15%	Y	Y
3.3	Deploy personalised offers via direct and GDS channels	Distribution Channel Manager	NDC API Gateway	Ranked personalised offer sets, channel capability matrix (NDC Level 3, GDS, direct web)	Live ancillary offers served to all booking channels with channel-specific display logic	NDC channel ancillary attach rate ≥ direct channel within 6 months of launch; GDS ancillary display compliance ≥90% of enabled PCCs	Y	Y
Phase 4 4.1	Monitor ancillary attach rates by channel and product	Ancillary Revenue Analyst	Tableau	Real-time ancillary sales feed from Altéa PSS, channel booking logs, budget targets	Live ancillary performance dashboard: attach rate, revenue per pax, channel mix, trend	Ancillary revenue as % of total revenue ≥15%; dashboard data latency < 4 hours	Y	Y
4.2	Conduct ancillary price elasticity A/B testing	Ancillary Pricing Analyst	PROS RM	Current ancillary price points, candidate test prices, booking volume thresholds for statistical significance	A/B test results with elasticity coefficient and recommended price adjustment per product	A/B test significance ≥95% confidence interval; minimum 500 transactions per test cell	Y	N
4.3	Optimise ancillary offer placement and sequencing	Ancillary Revenue Manager	Amadeus Altéa PSS	A/B test results, channel conversion data, passenger journey stage (search / select / pre-check-in)	Updated offer sequencing rules: optimal placement by journey stage and channel	Incremental ancillary revenue uplift ≥5% per optimisation cycle; cycle cadence monthly	N	Y
Phase 5 5.1	Generate ancillary revenue performance report	Revenue Management Analyst	Power BI	Monthly ancillary sales data from Redshift, budget targets, prior-period actuals	Monthly ancillary revenue report: actuals vs. budget, trend analysis, category and channel breakdown	Report delivered within 3 business days of month-end; forecast accuracy ≤5% variance vs. actuals	N	Y
5.2	Review portfolio and retire underperforming products	Ancillary Revenue Manager	AWS Redshift	Monthly performance report, ancillary product P&L, customer NPS scores by ancillary category	Portfolio rationalisation decision per product: retain / reprice / discontinue with timeline	Products with <0.5% attach rate and negative NPS reviewed quarterly; discontinuation decision within 30 days of review	Y	N

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Process Attributes

Identification

Process IDNP-RM-07

L1 DomainNetwork Planning & Scheduling

L2 ProcessRevenue Management

L3 NameAncillary Revenue Optimization

L4 Steps15 across 5 phases

Decision Gates8 (all with iteration loops)

Exceptions10 documented

Swim Lanes (Roles)

Ancillary Revenue Manager

Ancillary Revenue Analyst

Revenue Management Systems Analyst

Ancillary Pricing Analyst

Pricing Strategy Manager

Distribution Systems Analyst

Customer Analytics Manager

Distribution Channel Manager

Revenue Management Analyst

Systems & Tools

OAG Schedule AnalyserAWS RedshiftAmadeus SkyCASTAmadeus Altéa PSSPROS RMATPCONDC API GatewayAmadeus Revenue Management (NRM / AltéaRM)TableauPower BI

Key Performance Indicators

Benchmark ancillary revenue vs. peer carriersAncillary revenue per passenger ≥ $35 (IATA LCC benchmark); report produced annually

Analyse ancillary product mix by revenue categoryTop-3 categories contribute ≥70% of total ancillary revenue; data refresh ≤24 hours

Identify new ancillary product opportunitiesMinimum 3 new ancillary product candidates identified per annual review cycle

Configure ancillary service catalog in PSS100% of approved ancillaries configured and testable in Altéa within 5 business days of sign-off

Set dynamic pricing rules for seats and baggageElasticity model coverage ≥80% of O&D pairs; yield uplift ≥8% vs. static pricing baseline

Design fare family bundles with ancillary inclusionsBundle attach rate ≥40% of total bookings; bundle margin ≥ à la carte revenue equivalent

Validate ancillary offers in NDC API test environment100% of ancillary products surfaced in NDC AirShopping response; NDC API error rate < 0.5%

Segment passengers for targeted ancillary offersPropensity model AUC ≥0.72 for top-3 ancillary categories; segments refreshed ≤24 hours before departure

Airline-Specific Risks & Pain Points

IATA benchmark data lags 12–18 months; ultra-LCC peers (Spirit, Frontier) distort averages, masking true FSC comparison group and overstating apparent gap

Altéa PSS ancillary sales codes are inconsistently applied by airport agents, causing product misclassification in Redshift that distorts category-level P&L

SkyCAST O&D segmentation is designed for seat demand forecasting, not ancillary willingness-to-pay; proxy metrics must substitute for direct demand estimation, reducing confidence

EMD issuance rules require coordination with Finance for BSP settlement alignment; misconfigured EMD types generate revenue accounting errors and trigger BSP dispute processes

PROS RM dynamic ancillary pricing requires separate model training from core RM; data sparsity on thin routes produces unreliable elasticity estimates, defaulting to static fallback pricing

ATPCO Category 15 (Sales Restrictions) and Category 31 (Voluntary Changes) rules must be manually aligned with each bundle tier — a mismatch causes GDS display failures and customer refund claims

Inputs / Outputs

Primary InputIATA annual ancillary revenue survey, peer carrier 10-K filings

Primary OutputPortfolio rationalisation decision per product: retain / reprice / discontinue with timeline

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