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Customers Expect More Using Technology to Deliver David Utrilla U.S. Translation Company May 24, 2018

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Page 1: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Customers Expect MoreUsing Technology to Deliver

David UtrillaU.S. Translation Company

May 24, 2018

Page 2: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Agenda

WHERE IT ALL BEGAN

TRANSLATION TECHNOLOGY1. Computer Assisted Translation (CAT)

2. Translation Memory (TM)

3. Machine Translation (MT)

4. Translation Proxy

5. Video Remote Interpretation (VRI)

6. Neural Machine Translation (NMT)

7. Translation Management Systems (TMS)

CUSTOMER RELATIONSHIP MANAGEMENT TOOLS1. Customer Relationship Management (CRM)

2. Marketing Automation & Email Campaigns

3. Survey & Feedback Tools

Page 3: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Where It All Beganthe demand for translation tools

1

Page 4: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Client DemandsTHE ULTIMATE DRIVER

Customers have always wanted three things

when making a purchase:

1. Low cost

2. High quality

3. Fast delivery

“You can only pick two!”

Page 5: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

USTC’s Translation JourneyTOOL ADOPTION

1995: Only used proprietary tools because it was the only option.

2000: We leveraged proprietary TMS solution. Trados recently began licensing their TM.

2005: memoQ technology became available to LSPs as well as other competitors.

2010: Implemented commercialized TMS solution.

2012: Began using several solutions, including commercialized MT and other technologies used by translators.

2018: Have since started using CRM and marketing automation. Launched offerings for proxy translation and remote interpretation.

Page 6: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

New Kids on the BlockINNOVATORS VS. LAGGARDS

LATE ADOPT/REJECTStruggled or failed to catch up with

competition that adopted new technology

(EARLY) ADOPTInvested early and established themselves as

leading innovators in LSP industry

As new translation technology has become available, LSPs have two options:

The Technology Adoption Lifecycle

Page 7: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Why Not Adopt?FEARS AND CONCERNS

Feared reduction in business for human translators

Thought it wouldn’t be worth the monetary investment long term

Many LSPs did not adopt current technology for various reasons:

Assumed MT would produce low quality results

“If it isn’t broken, don’t fix it”

Page 8: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Benefits of AdoptionTHE PERKS

Ability to complete projects faster

Increase in number of projects and size of project

LSPs that did adopt new technologies saw the following benefits:

Boost in need for human translators for quality assurance

Page 9: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Translation Technologythrough the years

2

Page 10: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

History of Machine Translation

Page 11: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Computer-Assisted Translation (CAT)

Translation Memory (TM)

Language Search Engine

Terminology Management

AlignmentMachine

Translation (MT)

Computer-Assisted Translation

A form of human translation carried out with the aid of computerized tools.

More than 90% of translation companies use TM and CAT tools (2016 survey by GALA)

Page 12: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Translation TechnologyPAST

Translation Memory (TM)

ECONOMICAL FAST QUALITY

Translation memory remembers and reuses past translations from a particular project to improve translation efficiency.

Page 13: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Translation TechnologyPRESENT

Machine Translation (MT)

SAVESMORE MONEY

SAVESMORE TIME

MOREROBUST ENGINE

Machine translation is the translation of text by a computer, with no human involvement. It uses machine-learning technologies to translate large amounts of text from and to any of their supported languages.

Page 14: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Large LSPs that adopted MT grew 3.5 times faster than others

Source: “Fast-Growing LSPs Turn to Machine Translation,” © Common Sense Advisory, Inc.

MT Adoption Benefits

Page 15: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Translation TechnologyPRESENT

Translation ProxyTranslation Proxy creates a layer on top of an original website that provides real-time translation in the language of choice. The original site remains in control of the owner and merely projects translated text via proxy.

SIMPLESETUP

SCALABLEPROJECTS

TRANSLATIONIN-CONTEXT

MOREECONOMICAL

Page 16: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Translation TechnologyPRESENT/FUTURE

Video Remote Interpretation (VRI)

ACCURACY &RELIABILITY

NO PHYSICALPRESENCE REQUIRED

IMMEDIACY &CONNECTIONS

Video remote interpretation uses web cameras, videophones or tablets over a high-speed internet connection to provide on-demand interpretation.

Page 17: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Translation TechnologyFUTURE

Neural Machine Translation (NMT)

UNDERSTANDS WORD SIMILARITIES

CONSIDERS ENTIRESENTENCES

LEARNS COMPLEX RELATIONSHIPS

NMT uses neural network models to learn a statistical model for machine translation. A single system can be trained directly on source and target text.

Page 18: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Translation TechnologyFUTURE

Where Does NMT Stand? Still in the Works.

- April 2016: Google’s US patent application “Neural Machine Translation Systems With

Rare Word Processing” was published.

- November 2016: Microsoft announced they were using neural networks to power all

speech translation, a further development after their February news that they were leveraging AI and deep learning for their Translator Hub.

- May 2017: Facebook published results on their approach for NMT using convolutional

neural networks, said to be 9x faster than sequential reading methods, beating Google’s system.

Source: “Neural Machine Translation Evolving At Breakneck Speed,” Inside Big Data

Page 19: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Translation TechnologyFUTURE

Source: “Neural MT: Sorting Fact from Fiction,” © Common Sense Advisory, Inc.

Expectations for NMT May Exceed Reality

Page 20: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Translation TechnologyFUTURE

Source: TechEmergence

According to this chart released by Google in 2016, Google Translate (NMT) performs translations in varying levels of accuracy on par with human translators.

Translation Model Versus Quality

Page 21: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Translation TechnologyFUTURE

2017Translators are at the end of the chain and cannot influence MT

2020+Humans are at the center and interact with MT, which learns from them to make them more efficient and productive

Source: “Neural MT: Sorting Fact from Fiction,” © Common Sense Advisory, Inc.

Page 22: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Translation Management Systems (TMS)WHAT IS IT?

A Translation Management System allows enterprises and translation companies to centralize and automate the management of localization workflows involving multiple vendors and large volumes of linguistic assets.

- Contact management

- Requests (quotes, issue orders)

- Quote management

- Order management

- Invoicing

- Queries and reporting

Page 23: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Translation Management Systems (TMS)PROGRAMS

Some common TMS software options:

- Plunet

- Transifex

- POEditor

- PhraseApp

- Lokalise

- Smartling

- GlobalSight

*Source: G2 Crowd

Page 24: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Translation Management Systems (TMS)EXPECTATIONS

Common Sense Advisory anticipates that TMS features will start to slim down as systems begin to focus more on the features actually used by customers and remove the ones that were just added to match those of their competition.

Page 25: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Customer Relationship Managementtools you can use

3

Page 26: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Today’s TechnologyWHY YOU SHOULD USE IT

Page 27: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Customer Relationship Management (CRM)WHAT IS IT?

“CRM is a technology for managing all your company’s relationships and interactions with customers and potential customers.

The goal is simple: Improve business relationships. A CRM system helps companies stay connected to customers, streamline processes, and improve profitability.” - Salesforce

Page 28: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Customer Relationship Management (CRM) PROGRAMS

• Microsoft Dynamics 365

• HubSpot CRM

• Salesforce

• Highrise

• Velocify

• Vtiger CRM

• iContact

• Daylite

• SalesNOW

• Less Annoying CRM

• Gold-Vision

• Commence CRM

• Hatchbuck

• Teamgate

• ONTRAPORT

• bpm’online

• Pipedrive

• Base

• Close.io

• PipelineDeals

• Nimble

• ProsperWorks

• amoCRM

• Agile CRM

Page 29: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Customer Relationship Management (CRM) COMPARING PROGRAMS

Free Trial

Free Version

(Target Customer Size/Users) (Target Customer Size/Users)

Free Trial

Free Version

Page 30: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

SALES: “Increase productivity, keep pipeline filled with solid leads, and score more wins without software, hardware, or speed limits.”

MARKETING: “Deliver personalized customer journeys powered by the intelligent marketing platform for email, mobile, social, digital advertising, and data management platform.”

Page 31: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Manage pipeline with total visibility

Log sales activity automatically

See everything about a lead in one place

Also a option!

Page 32: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Marketing Automation & Email CampaignsCOMPARING PROGRAMS

IDEAL FOR• Designers• Agencies• Companies of all

shapes and sizes

PROS• Auto-unsubscribe• Plug-and-play designer• No setup fee

CONS• Basic customer support• Campaign transfers are

complicated• Lack of image hosting

IDEAL FOR• Small businesses

PROS• Variety of templates• Ease of use• Affordable pricing

CONS• Limited customization and

flexibility for advanced users• Limited email segmentation

features

Page 33: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

BUILD & DESIGN CAMPAIGNS

TRACK & ANALYZECAMPAIGNS

IDENTIFY & SEGMENTPROSPECTS

Page 34: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

▪ Powerful automation for online sellers

▪ Call to action with landing pages

▪ Comprehensive mobile app

▪ Flexible design for brands of any size

▪ Advanced analytics

▪ Hundreds of integrations with apps

Page 35: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Also a option!

TechValidate creates marketing content using customer input

Page 36: Customers Expect More - GALA Global · leveraging AI and deep learning for their Translator Hub.-May 2017: Facebook published results on their approach for NMT using convolutional

Thank you!Any questions?