Delivered at the GALA Global Conference March 22nd 2016 Brooklyn, NY. Clients are increasingly asking LSP sales teams about Machine Translation (MT) solutions. Consequently, sales teams and project managers must skilfully field MT inquiries in order to win new business and to build and maintain trust with current clients. With numerous types of MT solutions in the marketplace, how can sales managers equip themselves with the right MT knowledge to provide effective translation solutions for clients spanning different industries, and with different translation quality and technical needs? This session will provide insights from both technical and sales perspectives to help sales teams position MT information for various stakeholders, and enable them to reliably sell different types of MT solutions. Participants will also learn the key factors relevant in determining a project's suitability for MT.

1. What your sales team really needs to know
about MT (but is afraid to ask?)
John Tinsley
CEO and Co-founder
GALA New York. Brooklyn. 22nd March 2016

2. This is a piece
of string
Asking how MT works is like asking…how long is
a piece of string?

3. Machine Translation is a complex sell

4. But it doesn’t have to be that hard!

5. Speaking from a position of knowledge
Machine Translation with Subject Matter Expertise

6. Understand the client’s project in detail
Assess your capability to deliver the project
Work closely with your MT partner
3 take home messages

7. Why MT?
• Speed
• Cost savings
• Time to market
• Your competitors are
doing it!
“Why would I need MT?”
Why Now?
• volume of content is
growing
• demand, more words less
time
• growth facilitator
• #FOMO – you’re missing
out on business
What’s the MT value proposition?

8. “What type of MT is it?”
statistical
rule based
hybrid
syntactic
custom
hierarchical
composite
cloud
DIY
intelligent
enterprise

9. • The goal of the MT here is to be good enough so that - on
the whole – with TMs, translators are faster post-editing some
segments
• Challenges
– development has to focus on reducing needs for edits, not
necessarily anything else
– translator acceptance always a big barrier
– evaluation can take time and has many factors
– pricing models
How will your clients use MT?
What are the use cases for MT?
Translator productivity through post-editing

10. • The goal is to produce MT that’s fit for a particular purpose as is
• Arguably easier from an MT development perspective
• Often high-volumes = more achievable
How will your clients use MT?
What are the use cases for MT?
MT for information

12. COST
FEASIBILITY
The MT Butterfly Effect
Language
Volumes
Content type
Training data
Integration requirements
Quality requirements
TM leverage
MT experience

13. Language
Not all languages are created equal
French
German
Turkish
Finnish
Spanish
Chinese
Korean
Hungarian
Portuguese
Japanese
Thai
Basque

14. Volume
Not all languages are created equal
The more words…the better…the worse?

15. MT experience
Little experience A lot of experience
Hard
“Easy”
LSP/vendor
experience with MT
Ease of
adoption
The more experience the LSP has
with onboarding/training vendors,
and the more experience the vendor
has with MT, the more feasible the
adoption of MT will be

16. Quality requirements
• Fully automatic human quality
• 300% post-editing productivity
• French to Spanish == English to Korean
• Best performance out of the box

17. TM Leverage
High TM
Leverage
Low MT
Effectiveness
Matches
# words
Context 403,803
100% 585,459
95-99% 50,366
85-94% 41,604
75-84% 32,319
50-74% 18,972
No Match 81,119
Total 1,213,643
Only 8% of
all words go
to MT

18. Integration requirements
Standard vs Custom Integration
“instant” solution costs rise
proportionality with the number of
languages and the throughput
needs

19. Training Data
Corpora. Dictionaries. Terminology.

20. Content Type
The bed was two twin beds put together and
me and my girlfriend kept fallin in the middle
(since we like to cuddle) and that was iritating
Late nite room service was awesome
Social Media
User Generated Content
Highly Technical
Marketing, Nuanced

21. The Conundrum
Confront the elephant in the room!

22. • “What volume of words do you estimate for the project?”
• “Do we have translation memories, glossaries that are
relevant? Can we create them?”
• “If so, what leverage are we getting?”
• “To we have post-editors? Access to a supply chain?”
– “what experience do they have?”
• “Where will MT fit in the workflow (depending on the use
case)?”
• “What variety is there in the content that the MT will be
processing?”
• “Why aren’t you using Google Translate?”
• “Is there sufficient budget for this project?”
What questions should YOU be asking?

23. Understand the client’s project in detail
Assess your capability to deliver the project
Work closely with your MT partner
3 take home messages

24. “How much
training data do I
need?”
“How frequently
can I retrain the
engine?”
“What
happens to my
data?”
“Do you do
language X?”
“How good is
the quality?”
“How do you
measure
performance
over time?”