lenati point of view - the google–ita software deal (oct 10)

8/7/2019 Lenati Point of View - The GoogleITA Software deal (Oct 10)

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2825 Eastlake Ave E #210, Seattle, WA 98102 | (800) 848-1449 | www.lenati.com

Point of View

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The Google ITA Software deal

How Android voice integration with ITAs airfare

query structure can drive travel innovation andcreate a more effective consumer experience

October 2010


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Point of View

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Introduction

Googles $700 M acquisition of ITA has driven both good debate and sometimes illogical lobbying on risksto airfare search integrity, competitor web traffic, advertising costs, and service to air industry customers.

There are positive opportunities, of course, and here we focus on a specific, less-publicized one thatcould have a meaningful impact in the near future:

Based on our tests, Googles Android voice recognition outperforms Bing, Vlingo and possibly otherspeech solutions in travel-focused natural language search and is almost ready for mainstream adoption

Integrating with ITAs airfare query structure (and potentially hotels) is a key opportunity for Google-ITAto drive industry innovation and create a better consumer travel search experience


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Point of View How it could work the basic process

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Google-ITA could convert spoken natural language terms to voice objects similar to drop down selections in booking engines,which would then integrate with the fare search query data structure. Hotel search is a potential opportunity as well.

VXML 3.0

Analyzes voice inputusing Speech RecognitionGrammar Specifications

(SRGS) to translate to text

SISR

Semantic Interpretation forSpeech Recognitionextractskey travel terms to convert to

voice objects

QPX fare search

Voice objects matched todata structure for fare searchquery and result processing

Google ITA Software

Fly 1st-class Seattle to LA August 25 coming back August 28 on Virgin America


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Point of View

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Cutting multiple inefficient and redundant steps out of todays mobile search and travel intermediary experience

Enabling consumers to bypass OTA and Metasearch competitors, who could not easily replicate it without

considerable capital investment

Encouraging competitors to innovate and find other ways to improve and bring their mobile products to consumers

Prompting Microsoft and Apple to leverage their mobile platforms and alter the intermediary landscape further

Potential high-level impact

In a sense, this is a component of a larger potential Google PC and mobile metasearch play, but it also impacts a keyarea of consumer experience needing improvement, and implications of leveraging the Android platform could include:


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Point of View Potential vs current mobile search experience

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Speak or Typeto search

Compared to todays mobile search experience, voice search with fare integration would be much faster than inconsistent

text links due to SEM/SEO manipulation, redundant steps, and multiple drop-down or typing fields

Speak or Touch toselect airline

Speak or Touch toselect flight

Airline / OTABooking

path

Potential Voicesearch to

booking path


path

Speak or typeto search

Re-selectFlight

Inefficienttext links

Re-enterterms in multiple fields Flight resultmatrix or list

Current mobilesearch to OTA

mobile path

Note: Expedia used for demonstration of general steps, not to imply variance in quality relative to other OTA paths


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Point of View Potential vs mobile app download experience

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Open app Flight resultmatrix or list

Flight detail Choose OTAor supplier

Comparing to downloaded mobile apps, current metasearch or OTA apps also require several additional steps, including

multiple drop-down or typing fields and additional site selections

Multiple text, calendar,or drop-down fields

Note: Kayak used for demonstration of general steps, not to imply variance in quality relative to other metasearch apps

Currentmetasearch

mobile app path

Potential Voicesearch to

booking path

Speak or Typeto search

Speak or Touch toselect airline

Speak or Touch toselect flight


path


path


7/182825 Eastlake Ave E #210, Seattle, WA 98102 | (800) 848-1449 | www.lenati.com

Point of View Why timing is right for Googles opportunity

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Travel is a strongcandidate for mobile voice

search and multimodalengagement

Google-ITA will have the

tools to execute it

Speech recognition has seemed promising for years, but has mainly been limited to electronic voice menusso whattechnology and consumer forces are aligning with Google capabilities to enable this now?

Travel lends well to speechrecognition demonstrated inDefense Dept tests 1991-1995

Smartphone penetration,processing power, and dualmicrophones growing rapidly

Cloud enables network-basedspeech to process larger

vocabularies than embedded apps

Travel planning requires relativelysmall grammar sets

Android currently outperformsMicrosoft and Vlingo for natural

language voice search of travel terms

In a short period of time, 25% ofAndroid searches are already Voice

Google has invested heavily to trainspeech algorithms

Mobile and Tablet search should be

15% of searches by 2013-2014

Consumers rapidly adopting voice inlocal search, car navigation, andplatforms like Microsoft Kinect

Technology elementsConsumer adoption and

Google advantages



Point of View

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Competitive implications

Only Google-ITA could achieve proprietary voice and fare technology integration, but Microsoft and Apple (a threat to enter)

own their mobile and speech platforms and have a key advantage in interfacing voice search directly with consumers.OTA and Metasearch players are at risk if Google, Microsoft or Apple leverage ownership of mobile platforms and would also need topartner with Vlingo, Loquendo, Nuance or others to embed speech.

Travelport ePricing

Amadeus Meta-pricer

Sabre

Vayant

Everbread

Expedia BFS

(if productized)

Fare query platformSpeech platformMobile platform

SiriiPhone

MSFT Speech /Tellme

Windows Phone 7

Android Android ITA Software

Vlingo

Nuance

Loquendo

Promptu

MSFT API

Android SDK

None

Must distribute appsor gain search traffic

through Android,WP7 and iPhone

platforms



Point of View Sample testing shows Android advantage

and challenges

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Sample - Fly 1st-class Seattle to LA August 25 coming back August 28 on Virgin America

To evaluate the readiness of voice search platforms to handle travel-specific natural language input strings, we tested 140searches on Android, Bing (Windows Phone 7), and Vlingo speech platforms (see Appendix for specific samples).Our tests indicate Android is currently more advanced for travel, while Bing performed fairly well and Vlingo was poor.

Platform Noise level

Key term

success rate WER Queries

mean search

time (sec)

mean

words

mean error

words

Android loud - Starbucks 30% 29% 20 7.4 12.4 3.6

Android quiet - office 85% 4% 20 3.7 13.2 0.6

Windows Phone 7 quiet - office 70% 7% 20 4.9 13.2 0.9

Vlingo quiet - office 10% 15% 20 3.5 13.2 2.0

Improved accuracy and search time is needed for practical use, especially in noisier environments, which we expect willoccur as dual microphone devices proliferate and cloud technology and speech training sets across all platforms improve.



Point of View Appendices

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Appendices

Defense Advanced Research Project (DARPA) Travel Planning testingTravel vocabulary size and relative speech complexity indicator

Lenati voice test sample data by phone platformProjected mobile and tablet search query growth 2010-2014Voice technology provider segments

Voice technology overview



Point of View Appendix

Travel planning ideal for speech recognition

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Travel lends well to speech recognition, demonstrated by testing during the Defense Advanced Research Project(DARPA) from 1991-1995

http://www.itl.nist.go

v/iad/mig//publications/ASRhistory/index.html

DARPAs Airtravel planning test: Used multiple microphones

Word Error Rate (WER) dropped from20% to less than 3% in 5 years

Measured to be as effective as human

interpretation




Travel planning ideal for speech recognition

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Travel vocabulary consists mainly of finite sets of origins, destinations, dates, travel brands, and other key categories ratherthan continuous or conversational speech that becomes incredibly complex in vocabulary, meaning, nuance, and dialect.

Therefore travel likely fits in the leastcomplex speech recognition type

And reduces the complexity ofcreating voice objects to match faresearch data structures

ABIResearch

Data set vocabulary size and relative complexity by speech type




Sample testing results

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Vlingo was worse than expected at this point

Android error rate was low, and in most cases, errors did not affect relevant terms needed to create Voice Objects

Spoken search string Text result WER

Search Virgin America flights from Seattle to San Francisco August 25 returning August 28 Search Virgin America flight from Seattle to San Francisco August 25 returning August 28 0%

I want to fly to Seattle from Washington DC on October 15, returning October 20 I want to fly to seattle from washington d c on october 15th returning october 20th 0%

I want to fly to Philadelphia from New Orleans on October 15, returning October 21 I want fly to philadelphia from new orleans on october 15th returning october 21st 7%

Fly from Seattle to Anchorage August 25 returning August 28 Alaska Airlines fly from seattle to anchorage august 25th returning august 28th alaska airlines 0%

Find flight Boston to Ft. Lauderdale August 25 returning August 28 JetBlue find flights boston to fort lauderdale august 25th returning august 28th jetblue 0%

Search round-t rip flight St. Louis to Phoenix January 5 to 9 search round t rip flights saint louis to phoenix january fifth 29 17%


Search Virgin America flights from Seattle to San Francisco August 25 returning August 28 virgin america flights from Seattle to San Francisco Aug 25th returning August 28th 0%

I want to fly to Seattle from Washington DC on October 15, returning October 20 12 flight to Seattle from Washington DC on October 15th, returning October 20th 27%

I want to fly to Philadelphia from New Orleans on October 15, returning October 21 Iwon to Fly to Philadelphia from New Orleans on October 15th raton October 20th 13%

Fly from Seattle to Anchorage August 25 returning August 28 Alaska Airlines flights from Seattle to Anchorage Aug 25th returning August 28 Alaska Airlines 0%

Find flight Boston to Ft. Lauderdale August 25 returning August 28 JetBlue flight Boston to Fort Lauderdale August 25th returning on 20 Eights Jet Blue 17%

Search round-trip flight St. Louis to Phoenix January 5 to 9 round trip flight St. Louis to Phoenix January 5th 29 17%


Search Virgin America flights from Seattle to San Francisco August 25 returning August 28 search virgin america flights from seattle to san francisco otis 25th return in august 28 14%

I want to fly to Seattle from Washington DC on October 15, returning October 20 I want to fly to seattle from washington dc on october 15th return in october 20th 7%

I want to fly to Philadelphia from New Orleans on October 15, returning October 21 I want to fly the philadelphia from new orleans on the kerber 15 return in october 21st 20%

Fly from Seattle to Anchorage August 25 returning August 28 Alaska Airlines fly from seattle to anchorage august 25th attorney in august 28 alaska airlines 8%

Find flight Boston to Ft. Lauderdale August 25 returning August 28 JetBlue flight boston the fort lauderdale august 25th return in august 28 jet blue 25%

Search round-t rip flight St. Louis to Phoenix January 5 to 9 search round t rip lake saint louis to phoenix january fi fth 29 17%

Windows Phone 7 error rate was higher, but in many cases did not affect relevant terms




Voice will help drive mobile search growth

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PC search should continue to dominate, but Mobile andTablet are also high-growth

Google owns estimated 90% of mobile query share

25% of Android searches are already Voice

Mobile, Tablet and PC search queries 2010 - 2014

Both Google and Microsoft have invested heavily in Android and Windows-based Voice recognition in anticipation of Mobileand Tablet search growth

Sources: Morgan Stanley; Microsoft





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VXML manages dialogue between person and device, and version 3.0 focuses on improved mediacontrol and synchronization, identification and verification capability, improved extensibility, andbetter multimodal input architectures via use of XHTML+Voice

VoiceXML

Speech RecognitionGrammar Specifications

Semantic Interpretationfor Speech Recognition

SRGS identifies the sentence structure expected in the human voice responses

SISR extracts key information from voice inputs to create voice objects for applications, andexamples include airfsearch integration with ITA data structures or converting phone-basedrestaurant delivery order data into a format for order processing applications

Speech recognition is based on the Hidden Markov Model (HMM), with a statistical approach enabling the technology to be trained,

decision weighting adjusted to improve accuracy, and huge data sets ideally of examples of all variations of a spoken string.Since it is unlikely any two spoken terms by different people will match, the model statistically determines what was most likely said,and the process below takes place to enable spoken terms to convert to use for applications.





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Often preferred since response times can be faster than network-based speech and performance is notsubject to network connectivity.Though phone technology will improve and many applications are suitable for embedded speech, largevocabularies and spontaneous speech require processing and memory not yet available.

Virtually unlimited processing power enables more robust capabilities in handling large vocabularyrequirements, complex continuous speech processing, and natural language inputs.Key challenges revolve around latency in data transfer, and a quick and accurate experience on mobiledevices. However, both should continue to improve consistently as technology improves.

Hybrid systems combine embedded and network-based processing, offering an advantage over a straightnetwork approach as the extraction performed on the device reduces complexity that can increase errors.

Network-basedSpeech

EmbeddedSpeech

Hybrid orDistributed

Speech

Speech recognition systems can be network (cloud)-based, embedded directly into phone operating systems, or a combination of both,

each of which carries advantages and disadvantages.


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Voice technology provider segments

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Microsoft Windows Phone 7Google AndroidApple iPhone / iPad (iOS)

VlingoNuanceLoquendo

Promptu

IBMAT&T Watson

Mobile platforms with proprietary speech

Speech providers with mobile apps

Speech technology infrastructure

By owning the phone platforms and default search applications, theycould essentially control the voice search experience and market

But by owning ITA Software, only Google could create seamless voicesearch integration with airfare and potentially hotel data structures

Travel intermediaries or suppliers could partner with them, or theycould develop their own travel-specific applications

Must market to travelers to bypass default mobile search applications

Promptu owns ProntoTreno, a voice-interactive train services and

booking application in Italy, and Flights2Go, an airline services app

AT&T Watson technology is a key component of Vlingo

Travel intermediaries or suppliers could partner with them


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2825 Eastlake Ave E #210 Seattle WA 98102 | (800) 848-1449 | www lenati com

Point of View

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About Lenati

We are an award-winning boutique consulting firm that designs, implements, and optimizesmarketing and sales solutions for companies that want to build stronger customer connection.

Based in Seattle, Lenati was recently named one of the Seven Small Gems of the ConsultingProfession by Consulting Magazine.

About the Author

Jonathan Alford brings over 14 years of experience in consumer travel and lifestyle business,technology and finance. His specialties include business strategy, online and mobile marketingstrategy, and global finance.He is a graduate of The Johnson School at Cornell University and the University of Virginia.

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