new generation shopping & pricing€¦ · pricing optimization algorithms act on rules at the...

New Generation Shopping & Pricing

PRIMER

AUTHORSManish NagpalVP Software DevelopmentFarelogix

Amanda CampbellDirector of Product MarketingFarelogix

[email protected]

farelogix.com

ContentsIntroduction

Background

Search - The Trend Rocking the Status Quo

High Performance Shopping

The Dynamic Pricing Opportunity

Dynamic Pricing - How it works

What to Look for in a Shopping & Pricing Engine

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4

6

8

9

10

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Copyright 2018 farelogix

Introduction

3

The airline industry has witnessed the steady growth of airline ancillary revenue for more than a decade, with $82 billion projected for 2017. How will the industry keep that party going?

Enter dynamic pricing, which is increasingly regarded as the next big – perhaps the biggest ever – revenue transformation opportunity for air commerce.

For many airlines, taking advantage of such an opportunity can seem daunting, especially with the exponential rise in search already pushing the boundaries of performance and budgets.

New generation shopping and pricing engines provide the answer.

This primer introduces air commerce executives to the world of new generation shopping and pricing. It begins by discussing the complexity and challenges presented by traditional air shopping and pricing, before diving into how new generation technology can reduce strain while boosting revenue.

For those with an interest in shopping and pricing technology, there’s even some useful advice regarding what to look out for.

We hope you’ll find it an interesting read.

All the best,

Manish Nagpal

VP Software DevelopmentFarelogix

Background

4 Copyright Farelogix 2018

NEW GENERATION SHOPPING & PRICING PRIMER

The level of complexity associated with air shopping and pricing is often the source of surprise and consternation for industry newcomers. How could it be this complicated?

Part of the answer lies in the very nature of air travel. There are a vast number of available connections to get from origin to destination and return. For example, getting from Fargo, North Dakota (USA) to New Delhi (India) can involve hundreds of flights. Even if you limit these to the top 50 possible in-bound flights and 50 possible out-bound flights, you get2,500 possible route combinations.

Another part of the answer lies in the annals of history and the airline processes which were defined in the 1960s and the post de-regulation era of the late 1970s.

Since the 1960s, airlines have filed their fares with ATPCO. Although these fares contain a limited amount of information (the base fare, government charges, and airline fees), each fare also comes with hundreds, if not thousands, of associated rules such as minimum stay required, blackout dates, and cancellation penalties.

Getting from Fargo to New Delhi

can involve hundreds of flights. Even if you limit

these to the top 50 possible in-bound flights and 50

possible out-bound flights, you get 2,500 possible route combinations.

For an airline to find the lowest fares to match a customer’s preferred travel time and class, they engage in a process called ‘air pricing’. To do this, a system must go to ATPCO and search through hundreds of thousands of different flight combinations and fares. For example, if a person flying from Fargo, to New Delhi has picked a specific flight, a pricing engine would have to search approximately 600,000 fares to price the itinerary. This whole process would require the system to handle 1.5 billion fares for a single shopping request.

This whole process would require the

system to handle 1.5 billion fares for a single

shopping request.

1974 ATP reorganizes Airline Tariff Publishing Company (ATPCO), with expanded capabilities and responsibilities, and moves headquarters to Dulles International Airport.

1969 ATP buys its first IBM mainframe computer to process fare data.

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PRIMER NEW GENERATION SHOPPING & PRICING

In terms of calculation, this increases exponentially as each fare has hundreds, if not thousands, of associated fare rules. In real terms, the calculation would be in the trillions. And because airline inventory and availability can change every second, all this has to be accomplished in real time.

Typically, this mind-boggling complexity is handled by technology that was originally built in the 1950s to provide travel agents with flight availability information. Plus, decades of ‘fixes’ and ‘work-arounds’.

Until recently, traditional shopping and pricing engines have just about coped with the cost and complexity of air shopping and pricing. But the delicately balanced status quo is quaking under pressure, from the onslaught of a powerful trend that shows no sign of waning. This makes for fertile ground for disruption.

The whole process would

require the system to handle 1.5 billion fares for a single shopping

request

However, the cheapest fare is not always the best fare, as routing, journey time, and other factors can make some fares more attractive than others. If an airline wants to enable its customers to browse and select the best fares, the airline would engage in a process called ‘air shopping’.

FAR - DEL1.5 billion faresFAR – ORD, ORD – LHR, LHR- DEL

DEL – LHR, LHR- ORD, ORD- FAR


Search - The Trend Rocking the Status Quo


Inaccuracyacrosschannels

Lotsof cache

Heavyhardware

Commoditizedfare structure

High costlook-to-book

Rise ofsearch

Traditional processes and technology are being rocked by exploding search volumes which are placing technology and profitability under pressure. In our experience, a 10,000:1 look-to-book ratio is the new norm. This rise is a result of many factors including increases in:

Important note: High search volumes are not only a challenge but also present opportunity. Once search is controlled by the airline, it can become a rich source of data for Artificial Intelligence (AI) and Machine Learning (ML) initiatives. Resulting insights can be used to continuously optimize offer creation.

Searching for air products on multiple devices and methods including voice search (e.g. Amazon Alexa) and chatbots.

Affinity/attribute shopping which inspires travelers by presenting them wide search results based on a range of criteria including interest, destination attributes (e.g. sun/ski), and budget.

Large date-range calendar shopping that shows potential customers their flight options across days, weeks, months, and very soon, an entire year.

Meta-Search Engines (MSEs) which can trawl the internet for thousands of flights in a single search.

New Distribution Capabilities (NDC) will enable more airlines to directly serve their customers. We predict that the maturing of the NDC program will result in a 5 – 10 fold increase in shopping transactions for the airline systems.

10,000 look-to-book

is thenew norm


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From a technical perspective, the outcome can be slow response times at best, and system outages at worst. From a financial perspective, it means eye-watering search costs. And from a customer’s perspective, it can lead to inaccuracy across channels. It’s not unusual for airline customers to experience price differences in excess of $10.00 for no commercial reason.

To cope with this precarious situation, many airlines have employed a variety of solutions including:

Employing a cache solution that stores search results to serve them to another customer when they conduct the same search. The upside is improvements in search response times; the downside is the return of inaccurate, out-of-date results. From an external perspective, price discrepancies lead to customer dissatisfaction, and from a revenue management perspective lead to intolerable forecasting errors.

Using more hardware which compounds the high cost of technology ownership since many systems use proprietary hardware that’s expensive to run and maintain.

Putting up with high cost by retaining financial models that made sense 20 years ago, when airlines saw look-to-book ratios of 10:1.

When it comes to air shopping and pricing, the industry has finally reached a tipping point.

From an external perspective, price

discrepancies lead to customer dissatisfaction,

and from a revenue management perspective

it leads to intolerable forecasting errors.



High-Performance ShoppingIn the previous section, we discussed the difficult balancing act that is traditional shopping and pricing. But how can these challenges be overcome? The answer lies in new generation offer engines that effortlessly handle the exponential rise in search while reducing costs.

New generation technology vendors have built shopping and pricing engines from the ground up without the legacy overhead. By using the best-fit technology, these new engines scale linearly to accurately respond to requests in milliseconds. They are designed to perform on commodity hardware, thereby reducing IT footprint and hardware expense.

By integrating shopping and pricing engines with schedule and availability data from sources that operate outside of the traditional ecosystem, such as the FLX Availability Calculator and FLX Schedule Builder from Farelogix, it’s also possible to eliminate look-to-book fees by removing expensive reliance on the PSS/GDS and other third-parties.

Now airlines can deal with the 'pain' of shopping and pricing. They can also engage in revenue boosting opportunity.


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The Dynamic Pricing Opportunity

Research has shown that modern revenue management and pricing methods have the potential to boost fare revenues by 6%. For a Tier 2 airline generating $800 million in passenger revenue per year, that’s an additional $48 million annually. In addition, a market research report published by Deutsche Bank on February 6, 2018 on the European Airline Industry predicts that flexible pricing and a greater ability to sell ancillaries has the potential to increase network airline EBIT by 20%.

New generation shopping and pricing engines put modern strategies, like dynamic pricing, into the hands of revenue and pricing specialists.

These flexible innovations re-imagine

how airlines shop and price, and elegantly handle

shopping, offer creation, faring, and pricing

requirements.

New retailing methodologies, like dynamic pricing, have captured the interest of executives across the airline organization. This is not surprising, given the potential for dynamic pricing to turbo charge airline revenue generation efforts for a minimal investment.

Dynamic Pricing:Increases revenue

by 6%+

6%+

*for a Tier 2 airline generating $800 million in passenger revenue

$48m

Per Year *



Dynamic Pricing - How it works

TheRIGHT OFFER

at theRIGHT PRICE

Dynam

ic Pricing Business R

ules

Bid Price/ Base

Fare

DataScience

AirlineData

$

ExternalData

The starting price is optimized through the application of data insights on airline-controlled pricing rules configured to reflect the airline’s revenue management strategy.

Common data inputs include:

Load factor

Season, market, or channel

Equipment/product attributes

Known customer data (e.g. Frequent Flier Program membership)

Historical trends

Classic revenue management models

Data science initiatives

Starting price data can come from any number of sources – ranging from revenue management (RM) systems and filed fares to those autonomously generated by ML and AI initiatives. The choice of where to start depends on the airline’s own requirements.

The starting price is optimized through the application of data insights on airline-controlled pricing rules configured to reflect the airline’s revenue management strategy.

Common data inputs include:

Load factor

Season, market, or channel

Equipment/product attributes

Known customer data (e.g. Frequent Flier Program membership)

Historical trends

Classic revenue management models

Data science initiatives

Starting price data can come from any number of sources – ranging from revenue management (RM) systems and filed fares to those autonomously generated by ML and AI initiatives. The choice of where to start depends on the airline’s own requirements.

How do these new generation shopping and pricing engines work?

In a nutshell, dynamic pricing is the automatic adjustment of a starting price based on data insights for the purposes of optimizing both revenue and customer uptake.


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Option One – Traditional

Many airlines are crafting first-round dynamic pricing initiatives based on a filed fare. In this case, the pricing engine will calculate a starting price from:

Fare tariffs and rules from ATPCO, SITA, or direct from the airline reservation system/PSS

Taxes from IATA or ATPCO

Flight schedules and availability from OAG, the PSS, etc.

Pricing optimization algorithms act on rules at the heart of a new generation pricing engine to manipulate the starting ATPCO-based fare with “dynamic” results, leading to the creation of better competing price combinations.

As filed-fares and 26 booking class buckets are at the core of today’s revenue management science, this option enables airline revenue management to immediately start experimenting with dynamic pricing initiatives. For some, such experiments include innovating with filed fares and even increasing the number of fares filed. The downside to this approach is the overhead associated with fare filing, plus the retention of the 26 booking class buckets can restrict game-changing innovation.



Option Two – New Generation

For airlines that are looking to experiment with dynamic pricing outside of filed fares and 26 booking class restriction, it is possible for revenue management to begin its dynamic pricing initiatives with the bid price or market fare, which is generated in the revenue management system. A new generation shopping and pricing engine then applies pricing logic to the bid price or market fare to eliminate the 26-bucket problem. As a result, the revenue management specialist has infinitely more opportunity to fine-tune a customized offer, which can be further discounted, bundled, or promoted.

Regardless of the approach, by reducing or eliminating the reliance on booking classes, airlines can engage in a pricing strategy that's more akin to a curve rather than incremental jumps in price, per the illustration below.

Price curve (illustrative)

Currently untapped revenue potential

(Dynamic revenue management with unlimitedpricing points)

Price point (26 letters of the alphabet)

Upward shift of the price curve(Increasing sales of ancillary and personalized fares)

Booking classes

Source: Lufthansa Group Conference & Roadshow Presentation, February 8, 2018.

Price

As you can see in the example above, fully elastic dynamic pricing takes advantage of untapped revenue potential from both flights and ancillaries.

Airlines looking to invest in new generation shopping and pricing will be pleased to discover that there are only a handful of such engines on the market today. Even though narrowing the search for potential vendors should be straightforward, making the right choice can be a challenge.


What to look for in a

Shopping & Pricing Engine When shopping for a shopping and pricing engine, keep the following points in mind:

Built for Airlines – Used by Airlines

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Ask your vendor who their first, second, and

third customers were. Walk away if the answers aren’t

airlines.

Building successful technology to service the airline industry is neither for the faint hearted nor the inexperienced.

If an airline is going to trust its business-critical technology to an external party, the airline needs to ensure it’s in safe hands. One way to do this is to ensure the technology selected is designed to meet the unique demands of the airline industry and is production proven.

If it’s commercially attractive to acquire the most advanced technology that has limited market exposure, an airline should place its ‘leap of faith’ directly into the hands of experienced industry innovators that can navigate new terrain.

Flexible Dynamic Pricing

Ask the vendor to see dynamic pricing

in action. Don’t settle for PowerPoint!

Dynamic pricing is a strategy that sees the price of the offer increase or decrease based on data insights. Shopping and pricing engines should be able to mark up or discount a starting price – whether that’s an ATPCO-filed fare, market fare, or bid price from an RM system – to reflect the airline’s offer management strategy.

TIP

TIP



Performance

Ask the vendor if they rely on

cache to deliver millisecond

response time.

Despite spiraling search volumes, a shopping and pricing engine needs to deliver accurate results in millisecond response times. Airline customers—whether guests on an airline’s website/mobile app/kiosk; an OTA or MSE; travel agent or TMC—demand nothing less.

It’s important to note that lightning-fast speed shouldn’t come at the expense of accuracy. That’s why an airline’s next shopping and pricing engine shouldn’t rely on inaccurate cached results; instead it should handle shopping, offer creation, faring, and pricing requirements in real-time.

TIP

Open & Interoperable

Ask the vendor if their technology can be used to customize

a best-of-breed offer management

platform.

Rarely is the airline business a ‘green-field site’ and it may not be feasible to replace existing implementations with a new technology stack. In addition, it may not be desirable if pursuing a ‘best-of-breed’ approach. Airlines can avoid technology lock-in by ensuring the components of their next shopping and pricing engine can easily de-couple and work with other systems (e.g. RM, loyalty, CRM, core PSS, merchandising etc.) as required.

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User-FriendlyAsk

the vendor how long it takes

to train business staff to use their shopping

engine. Ask to see the user interface for defining and managing rules

and offers.

As conventional wisdom would have it, a technology purchase that no one uses isn’t an investment - it’s a sunk cost. Selecting a shopping and pricing engine that is easy to use is just one of the ways to ensure it’s a valuable asset. The more comfortable revenue management and pricing professionals are using a tool, the quicker they will be able to counter competitive threats, take advantage of market opportunities, and experiment with new science.

TIP


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Low Cost of Ownership

Ask the vendor how

their technology lowers shopping and pricing costs.

Consider a solution that includes off-PSS availability and connection building to reduce costs. Airlines should also look for a shopping and pricing engine that scales using commodity hardware rather than pricey compute power. Linear scalability is key.

TIP

Are you in the market for a new shopping and pricing

engine?Learn more about

FLX Shop & Price by scheduling a consultation with

a member of theFarelogix team.

Please email:

[email protected]

FARELOGIXMiami (Headquarters)

760 NW 107 Ave. Suite 300Miami, FL 33172

Direct 305-552-6094farelogix.com

Download your copy

www.farelogix.com/shop-primer

new generation shopping & pricing€¦ · pricing optimization algorithms act on rules at the...

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