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A large array of MT technologies: companies do not know what to choose (daunting testing).

FOMO Syndrome: "If I choose Microsoft this year, perhaps Google will come up with an amazing update that strongly beneficiates my specific niche."

It might translate things in the wrong way (poor MT implementation): this is the commonest fear and it is well developed in some scientific papers.

Quality expectations of machine translation

Translation problems and MT

Compatibility issues with current systems.

Lack of trained internal teams on the MT subject.

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How The Funnel Will Look Like (Basic Idea)

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How The Funnel Will Look Like (Basic Idea)

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Top of the funnel:

Inbound and outbound marketing strategy using a case study.

The inbound strategy will be around super valuable content, podcasts appearances, campaigns using videos and landing pages for downloading eBooks and informative materials for companies.

Possibilities on these regards are virtually limitless. However, social media and advertising should be the main pillars.

Middle of the funnel:

The outbound strategy will be cold emailing pitching a case study. Koalingo SHOULD NOT contact startups as these do not have enough budget nor resources to acquire these custom MT-based services.

Book meetings and presentations to those warm leads interested in the service.

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1- Education platform for businesses with a paid subscription format (a demo would be available).

Lessons that will teach CTOs, CEOs, Localization Managers and everyone involved in the process, to properly understand the MT universe and make better and informed decisions.

These will have 24/7 support in many languages and private 1-on-1s in case they need more details and examples according to their own situation.

Possible names: DIFEMTI! (Don't Fear Machine Translation!)
KMT Academy

2- In-house or over-the-air training for specific projects or for the general implementation of the right MT technology.

The principle is very similar to the educational platform but in this case, there is a deep customized approach. The name and logo could even be the same to my current business.

3- Deliver translations services fully powered by MT algorithms with a comprehensive MTPE and QA process.

The user will go through a screening process to determine the right type of technology for their niche and objective, it will never be a generic translation workflow.

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1- Alibaba Cloud (MT)
For e-Commerce and very general texts. It works really bad with most Roman languages as it uses BLEU scores. It needs a full MTPE and QA process after populating.
2- DeepL
It's a revolutionary API based on an independent MT patent that has a high-quality output for politics and society, finance, energy compliance policies, and even some technical topics.
3- Microsoft
4- SAP
5- Systran
It is focused on full website and simple and rich text translation.
6- Youdao
7- Amazon
8- Google Cloud (Google Translate; Neural)
9- SDL Language Cloud
10- Baidu
11- Yandex

Top reference:

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State of the Machine Translation by Intento (July 2018)

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Evaluation of 19 major Cloud Machine Translation Engines (Alibaba, Amazon, Baidu, DeepL, Google, GRCom, IBM SMT and NMT, Microsoft SMT and NMT, ModernMT, PROMT...