MT as a Platform Service
Last August when I delivered the opening keynote at the MT Summit on “responsive MT,” one trend that I identified was the emergence of MT as a platform-level service provided by creators of enterprise ecosystems.
What do we mean by MT as a platform service? Take the case of an ERP like NetSuite or SAP, or a CRM such as SalesForce or Zendesk. In a simple case an implementation results in flows of localized information among at least four parties – the organization that relies on the platform for business functions, its customers, the developer of the platform, and anyone building third-party applications within that ecosystem.
Business Systems Combine International Users, Data, and Code, Often Badly
The complex ways in which these streams of content interact can make traditional localization difficult, particularly for any multiparty interactions. For example, what happens when a Bulgarian customer interacts with a company in Germany that is using a US-based CRM with plug-ins from a French developer? Because the interaction may involve content from all of these sources, no single party can create a fully localized experience. Gaps in any one of them can contribute to a sub-par customer experience, so it is in the interest of all parties to solve the problem. However, because lines of responsibility are often unclear, improvements are frequently slow in coming.
This macaronic mixture is particularly challenging when business-critical third-party applications are involved. When CSA Research examined major CRM developers in 2021, we discovered that most developers do not list the languages they support – only the SalesForce marketplace systematically identified which apps are localized – and most probably appear in just one language. In such cases the organizations that implement these apps and their customers have little recourse unless someone is willing to pay developers to localize their apps.
In the face of this complexity, it is almost natural that the ERP and CRM developers would either build their own MT or work with third parties to extend it as a basic functionality in their ecosystem. Although machine translation is far from perfect, our research has consistently shown that if the choice is between bad MT and no translation, customers overwhelmingly prefer MT. When MT is baked into the systems at a low level, then all parties can take advantage of ubiquitous, on-demand language functionality to address the gaps that derail the customer journey.
Although platform-level MT has not yet become ubiquitous, various MT providers have stepped in to partner with ERP and CRM providers to deliver these services, at least in part. Unbabel and Language.io, for example, help to localize the customer interaction portion. In other cases, individual developers within enterprise ecosystems have provided their own MT to support their users. But the greatest efficiency will come about when the ecosystem providers make MT on demand pervasive, something we know that several of them are working on now. Already Amazon, Google, and Microsoft have made it simple to add their respective translation systems into their cloud-based platforms, but few developers have fully incorporated those offerings.
Inclusion of on-demand MT in enterprise ecosystems, tuned to their particular needs, will have a knock-on effect as it increases the expectation of language as a fundamental feature of everything rather than something customers have to beg for or pay extra to have. This shift in expectation will in turn drive greater adoption of both machine translation and traditional human services. Platform developers benefit from language support that keeps users on the job inside their ecosystem rather than requiring them to bail out to third-party translation hubs.
In other words, what we see today is just the start of something far bigger than the disconnected and disjointed technological infrastructure that currently leaves far too many gaps. As enterprise ecosystems normalize the expectation of localization, they will help drive localization forward in other areas as well.
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