#113 Translation and Localization Industry Grows 11.8% in 2021 to USD 26.6bn

#113 Translation and Localization Industry Grows 11.8% in 2021 to USD 26.6bn

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Addressable market is 26.6 billion US dollars in 2021. At a conservative scenario of 2.5% growth, we'd end up at 30 billion dollars in 2026. 2021, obviously saw a really strong rebound in growth for media localization.

And welcome everyone to SlatorPod 113. Hello, Esther. Hello, Anna. Hey, Florian. Hey, Anna.

We are firmly in the triple digits and today we brought on somebody from our very own team, Anna Wyndham. You're joining us today to talk about our 2022 Language Industry Market Report, our flagship annual report that's out now. It's a 100-page beauty and it's been out now for a few days, so first, congratulations Anna on the report.

Thanks. Yeah. It's got a lot of very interesting content and as you said, 100 pages. 100 pages, so one big report there, and then we're going to go through some of the highlights of the report, just for people to understand what it's about.

We're going to give you some high-level data points of market size and like which vertical performed, how, and then we're going to round off, Esther you and I, we're going to talk about Lilt and Jeenie in our abbreviated news segment because while we're publishing reports, the industry continues to produce pieces of news. So, Anna first tell us a bit more about what does the report cover in terms of like industry analysis, first? The report covers industry market size and growth in 2021. It analyzes the language industry through the lens of 10 primary buyer verticals. We list the top growing verticals by percentage and US dollar growth. We have a geographic analysis there that lists market share and percentage growth per region and identifies the fastest-growing markets in North America, Europe, and Asia.

We also have that buyer intentions framework that we introduced last year, so this identifies nine primary drivers or reasons that buyers need localization services, so the kind of underlying rationales, and we have an infographic as well that shows the more than 200 core and adjacent services provided by leading language service providers. We look at the competitive landscape, so analyzing data from the Sleeter 2022 language service provider index, which came out a couple of weeks ago, so it's a segment by segment analysis of the growth and market share in 2020. We, of course, look at core translation technologies, machine translation, TMS, analyzing the ecosystem there, the key players and the main business models and a quick closeup as well on that M&A activity in the TMS space, which was really prominent in 2021 and, of course, we've got a market outlook there, growth for 2022 and projections to 2026.

What happened in 2021? So tell us, what's our headline figure for market size, and what's the growth figure there? Addressable market is 26.6 billion US dollars in 2021 according to our calculations, so it was a full recovery from the slowdown in 2020. Market size increased by 11.75% compared to 2020, so yeah, we see that the market remains very resilient and we've identified the reasons before, the diversity of bisectors, adaptability to remote work, and early adoption of AI in the supply chain is another factor coming into play there. Yeah, so this figure is very much relied upon by anybody looking to invest in the language industry, so we tend to be, we've spoken about this many times, Esther, you and I, right.

We tend to be on the conservative side here. Now, why are we more on the conservative side compared to some of our competitors, like Nimdzi, like CSA? I mean, it's difficult for us to say, I think in terms of what the methodology is used by others, but I think we probably take a slightly narrower view of what constitutes the services and the technologies involved in the core language industry. So, I mean, Anna mentioned earlier, just the services map of services provided as core services, translation, localization. You can rattle off a lot of them and then adjacent services, which a lot of LSPs do, like technical writing, content authoring. I could list, again, rattle off a whole load but so I think we're probably taking a slightly narrower view of defining those, the kind of core of the language industry.

Got it, so Anna let's look at the geographic split here on our headline figure, so we also divided this out for, I think North America and Europe, for example, like what are these two blocks? How much do they generate? Yeah. I mean, the report has a full segmentation but for North America, market size is at 10.38 billion US dollars in 2021 and we see this has been driven by their main sectors, technology, healthcare sector is really important there, as well as manufacturing and engineering and then Europe market size 9.6 billion US dollars in 2021 and public sector tends to dominate there as well.

Very good and, Anna, you mentioned earlier just about the sort of vertical split that we make when we're dissecting the industry. Are there any insights that you can share on a vertical basis? Yeah. Some interesting insights. The smallest vertical in those 10 by verticals is gaming, but this also happened to be the fastest-growing in 2021, so it increased by 26% from 2020 and the drivers behind that widespread adoption of smartphones. Yeah.

Keywords probably accounted for a significant portion of that, didn't they? Their localization, I think grew like 20% in 2021. A big player in the market. Yep. Definitely seeing those double-digit growth figures for those LSPs specialized there. Other key verticals or highlight verticals, manufacturing and engineering was below industry average.

It was at 6% and one of the contributing factors is, of course, the disruptions to supply chains in 2021 and then stronger growing verticals, technology always, but especially life sciences increasing by 19% from 2020 and media localization, which increased by 18% from 2020. And that was probably, just on media localization, I mean, they had a really rough ride in 2020, so I think I can't remember the exact stats from 2020 but I think we've discussed the reasons why media, in particular, was impacted in 2020 with closures of dubbing studios and things like that but I think in 2021, obviously saw a really strong rebound in growth for media localization. Yeah, definitely the case, so they're back to producing new materials, continuing to localize back catalogs. We see those streaming platforms expanding internationally and this new strategy as well of local for global content.

For example, Squid Game is the most talked about, but this is a real strategy that's impacting the industry, so streaming platforms are creating content for local markets, but with a view for global consumption, so it's creating all of this volume demand, but also demand for these new language combinations and we do a bit of a deep dive in the report into this because it's such an interesting area and kind of compare the different expansion strategies that these different platforms have taken in terms of where they're expanding to, where they're going next and how that's impacting on the demand. Yeah, so I was going to say, I think the report takes an expanded look at media localization, also video localization. Are there other areas that we're pulling out and highlighting in the report? Yeah. We also do a bit of a deep dive on interpreting services and tech, so we have 11 pages analyzing this sub-sector and we look at demand drivers in the US, Europe, and Asia-Pacific. Especially the rise of telehealth and we kind of dived into that into the most recent SlatorCon so some really interesting insights there about how this is changing interpreting and then we look at how, of course, remote technology is transforming the sector. This is probably one of the biggest changes the sector's ever experienced, so we look at what implications that has for growth funding and competition and how different players in this sector are kind of positioning themselves.

What they're prioritizing in terms of developing their product. Then we also look at frontier tech or at least what we call frontier tech, for lack of a better word, frontier language tech, so what are the two most, for you, the two most interesting quote-unquote language frontier tech areas? Give us the highlights. So, frontier tech is a super interesting area. In the report, we look at speech synthesis and speech-to-speech translation. My favorite, my favorite. And the other are these large language models and the potential to impact on text generation and what we try and do in the report is to understand how these frontier technologies are being productized at the moment, who the early movers are in these areas, and what type of language services and products they're offering and how that can impact on the language industry at the moment so, for example, we see synthetically dubbed media.

It's a new means of accessing new markets for media localizers, sorry, for media production companies. We have companies like Paper and Deepdub, so they're using this speech synthesis and speech-to-speech translation technology to offer synthetic dubbing of video content and we can see it mainly used for content like news, documentaries, user-generated content. Not so much the high-end Hollywood stuff yet but we do see that it's kind of expanding the market because it's making it so much more accessible to dub this type of content and I think last week or the week before, you covered Google's move into this area as well.

Yeah, the Aloud project, right. Google Aloud where it's basically building, I think it's, I mean, it's an internal Google project, so... For YouTube.

For YouTube. Okay and then yeah, you said the other one was like these language models that people are building on top of these GPT-3's and what have you. I mean, now I read that there's GPT-Y's and there's this big Google thing that we're trying to parse for our readers and we're not done yet. I think it's still like in our pipeline to cover this, what was it called? I forgot. We tried to unpack it last week.

Anyway, so these big language models that people are building on top of and I think we call it like synthetically generated content marketing, right, and so you can work with those. Just tell us the top two highlights there. Top two, three highlights. What we're seeing? What kind of players are in that space? Yeah, so I mean, as you mentioned all of these large language models are being released.

We saw Google releasing a model with 1.3 trillion parameters in December 2021. Very recent, so that's the largest at the moment but Microsoft also released one in October 2021 and GPT-3 earlier in the year and I mean, the key point is that they have language capabilities. They can comprehend and produce language, they can analyze sentiment, they can answer questions, and so on, so they have really a huge number of potential applications. One potential application that we see is taking off already is generating content marketing, as you said, so content marketing is quite well suited to this technology because it's kind of it's needed in large volumes. It has a short shelf life.

It doesn't need to be as polished as say high-end advertising copy, so we see startups such as Copy AI or OtherwiseAI creating these products that allow you to automatically generate emails, blogs, e-commerce copy. All different types of texts just by inputting a small amount of data, for example, a summary or a couple of keywords, and these, of course, are available in multiple languages so, at the moment, content marketing is either produced in the original language and localized, or it's produced in a multilingual content origination workflow based on a brief. But we can see that this synthetic content marketing is kind of moving into that space, maybe not necessarily disrupting it or taking away from that market, maybe expanding it but definitely, it's in the same space. They're providing the same service.

So Google will have to figure out eventually, if everybody's using these models to produce original content marketing, Google probably has to then figure out and prioritize content that was written by a human and where there is some effort that went into it for SEO. Again, now we're getting really like into the weeds of it, but if everybody at the click, yeah, if everybody at the click of a button can generate thousands and thousands of words of like original content, then at some point, like it's just another SEO game. Alright, so we're fascinated by that and I also tend to fall down that rabbit hole and I'm glad I recently read a really interesting post by a founder. I forgot the company name but it was on like Andreessen Horowitz's Future sites. It's like, it's kind of a, well, for lack of a better word, a content blog platform by the venture capital firm, Andreessen Horowitz and anyway, so that founder also kind of laid out the history of all these large language models and did say, basically concluded that a lot of stuff is happening super fast and that guy basically founded this company based on these technologies, right, so it's not like just us struggling to comprehend the speed of it all, but it's like even founders in that space are struggling to understand the progress.

So, I think we also had on our list here that we wanted to talk about Meta's roadmap for speech-to-speech translation but I think people can just read up on it. I think if we keep talking about it then people are like, Hey, you guys wanted to talk about your language industry market report and here you are falling into these kind of AI rabbit holes again, so let's talk about the outlook. So, again we were at that 26.6 billion dollars in total market size and for the outlook, we had a couple of different scenarios here, so tell us what are the figures here? What is the conservative and the optimistic and our base case? Yeah, so the reason we have these different scenarios is that there are a number of different macro factors that are creating a lot of uncertainty, inflation, supply chain disruptions, the war in Ukraine, and so on, so conservative scenario growth of 2.5% year-on-year to the most optimistic scenario which is 7.5% growth. So if we're looking at the, it's interesting how different the outcome would be right, so at a conservative scenario of 2.5% growth, which is

quite conservative, we'd end up at, what, 30 billion dollars in 2026. If you take the 7.5% year-on-year scenario, we'd end up at 38 billion dollars in 2026, so you see the magic of compound, whatever, compound interest at work here.

No, it's true, right, and so our base case takes us to just below 36 billion dollars, so right now we're at 26, so there's like, even our base case means that in the next few years there's like another 10 billion dollars up for grabs, right, and so that is a very, very attractive scenario here that we, yeah. We're looking forward to capturing that, maybe we should start an LSP. Let's do it, with the language models. With the language, exactly, with the language models, so now let's talk about the macro. I made a few notes.

I mean, it's just, we're at an extremely uncertain point right now because we had this somewhat unexpected kind of bumper year last year despite all the kind of restrictions because of Covid. There was just so much money flooding the market and inflation really hadn't taken hold yet, so everybody like provided funding and et cetera, and generally businesses rebounded from Covid. But now this kind of inflation that people said it was going, people, like some government said it was going to be transitory.

Now it's, well, it's not and all that money printing means it's not really transitory, so you're seeing interest rates rising sharply, like some of the benchmark, like the 10-year treasury note that the US treasuries are going up quite strongly. Now, this is actually relevant to the language industry because as these kind of benchmarks go up, stocks tend to get hit quite hard because of some, let's not get into the details there, I'm not the right person to explain that. But basically, eventually, what it's going to do, it's going to filter into the funding environment, so you'll see probably somewhat a more conservative funding environment for language industry startups as well. Not that those are first in line to get hit by a slowdown and then also there is the M&A side's probably going to slow down a little bit as opposed to 2021 and then generally, of course, as the entire economy slows down, of course, you see probably some of the just outright demand for language services is going to slow down a little bit.

I'm not expecting, again, our base case is for 2.5% growth, sorry, our conservative case is for 2.5% growth, so we're still expecting growth but it's probably, I would expect it a bit more towards the conservative side this year, given what's happened over the past like four to six weeks just generally globally, so yeah. But again, to end on a more positive note, I mean, typically the language industry is very resilient and tends to ride out these cycles quite well. I mean, it's correlated with them with the broader economy, but it's not overly correlated, so it wouldn't go down more than the broader economy so, and yes, so I just said that we're going to see maybe a bit of a pullback on the funding, but there is... However.

However, well, those deals were probably lined up before, probably towards the end of last year, right, so Esther, tell us more about two fundings that were just announced last week. Yeah. Well, the biggest of the two, Lilt raised 55 million in their series C funding. That was announced in early April.

That brings the total funds raised by Lilt to 92.5 million US dollars, so a considerable amount of money there and the series C is roughly two years after Lilt raised 25 million dollars in their series B. This latest round is led by Four Rivers VC. They've got also new investors Sorenson Capital, Clear Ventures, Wipro Ventures, and the existing investors, including Sequoia, Intel, and Redpoint. Which, well, you will remember Florian, but others might not that we had Tomasz Tunguz from Redpoint Ventures back in SlatorCon San Francisco in 2019, so yeah. They also participated in this latest round.

The valuation undisclosed unsurprisingly but in terms of, well, one kind of metric. Tell us why is it undisclosed? Give us the metric, Spence. Come on, tell us. Okay.

We can invite him on again. Give him a grill against to why he doesn't disclose. Need data points. I mean, it's his prerogative, let's put it that way. He's not required to disclose. Doesn't want to, so...

Unless they go IPO. Okay. Let me just pause you there for a second. Did you see what they put on LinkedIn? On LinkedIn, they put a picture. Yes, the Nasdaq! The Nasdaq, so Nasdaq the stock exchange in New York, right, put a giant kind of congratulatory note on their monster-like screen in, yeah, like in New York outside of the stock exchange, so I tweeted below like, well, IPO soon? Nobody replied. Only Kris from Summa liked my tweet but nobody else replied.

You should have done it on LinkedIn. Yeah right, it was on Twitter. I saw it on Twitter. Because I saw the same thing. Yeah, I saw the same thing on LinkedIn.

So what's the point here? Is that, well, now they're not disclosing, but they're raising, what is it? A series C now. Well, after series C, yeah, you can do another series D or you go public, right, and Nasdaq. I mean, that's basically kind of lead generation by Nasdaq, so they're congratulating, hoping that there going to go public on Nasdaq and then we know all the details and the financials. They could do a series D, a series E, and then go public.

Yeah, yeah, yeah. Yeah, series E, no. Series D, maybe, but well... We did have one.

We had like, wasn't it Verbit or somebody did a series E? I can't remember. One of the companies that we're tracking did a series E but yeah, it seems to be less, somewhat less typical. At some point, you just have to jump. So anyway, back to Lilt. They have 150 employees.

That was one metric that he did, Spence did to us and he also said just talking about growth in the company, they're seeing growth across the board across multiple sectors, but they have noticed unique applications in education, crypto technology, and defense and intelligence, supposedly for their services and Spence also spoke to us a little bit about the roadmap. So, which seemed very much focused on developing MT, developing connectors also, so for example, Spence said that Lilt's working on significant updates to its MT system to support high volume use cases and that they've developed more than 100 neural MT models in the past two years, so it sounds like a lot. They've been busy and the idea being here to support customers who are looking to transition to fully automatic workflows, so congratulations to Lilt on large amount of money, and let's see what they do with it. Fully automatic, so cutting out the expert-in-the-loop here, are we? No, I'm just, yeah, but I mean, that's what he said.

They said fully automatic workflows, meaning it's fully automatic, so steering a little bit more towards the pure tech angle. Alright, let's go to Jeenie, J E E N I E, Jeenie. Jeenie.

Yeah, so different kind of ballgame here in terms of type of company. This is an on-demand health care interpreting platform called Jeenie which raised 9.3 US dollars in a series A and they did tell us about the valuation. Hey, thank you. But the valuation is around 34 million dollars for Jeenie and that was the series A round led by Transformation Capital. Wait, wait. I was going to say, that is better late than never.

For the listeners, we found like our platform launched a few new features. Among them, Canned Cheers and Canned Clapping and stuff like that. It would be great if we could have it on cue rather than sort of 10 seconds after the thing that warrants applause. Yeah, we'll get better. But yeah, just a bit about Jeenie because I think maybe they've been flying under the radar for some people in the industry. I mean, they launched, they did a seed round back in 2018, so 3, 4 years ago now, launched the product back then.

They were actually initially focused on international tourists, so that kind of market in the US. Yeah, that was tough in 2020. Well, exactly, so when Covid hit, they pivoted the business to healthcare, which I mean, fairly smart decision given what we were saying about healthcare market, healthcare interpreting, et cetera. So now they have about 90% of their customers within that sector, so healthcare enterprises, doctor's offices, clinics, hospitals, those kind of profile of user, and the monthly recurring revenue, MRR, is currently growing at around 25%, so got some good traction there. Yeah, in terms of what they're going to do with the funds, they plan to grow the team.

Engineers, product experts, hiring people in those areas of specialty, and plans to develop UX, UI for clients and for interpreters that use the platform. They obviously are, like I said, currently focused on healthcare. There's potential for expansion into immigration and refugee support they said, as well as other critical services but the idea here is to remain focused on interpreting like pure play interpreting and not so much kind of branching out into translation to become a full-blown LSP or anything along those lines but it's a marketplace model at the moment, so kind of gig economy marketplace with like specific minimum requirements and qualifications for interpreters, so that is Jeenie. That is Jeenie, ladies and gentlemen. Jeenie in a bottle, in a nutshell. Jeenie in a phone and so Jeenie will also contribute to the 26.62 billion dollar

language industry market that grew by 11.75% compared to 2020, as you can read up in our flagship 2022 Market Report. Congratulations, Anna for putting this together and we're very excited to also host a briefing in late April. Go check out the, I forgot the date, but check out the date for anybody who bought the report or is a Slator Strategy Package subscriber, so looking forward to seeing you there.

See you there. Alright, that's a wrap for today. Thank you very much.

2022-04-17 03:27

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