Ladies and gentlemen, thank you for standing by, and welcome to the Appen Limited FY 2021 full year results conference call. All participants are in a listen only mode. There will be a presentation followed by a question and answer session. If you wish to ask a question, you will need to press the star key followed by number one on your telephone keypad. I would now like to hand the conference over to Mr. Mark Brayan, Chief Executive Officer. Thank you, and over to you, sir.
Thank you very much. Hello, everybody. Welcome to the call for our full year results for 2021. I hope you're all doing well and possibly back in your offices as we get used to living with COVID. I'm traveling regularly once again and am pleased to be able to spend time with our customers, partners and staff in our offices all around the world. Life's returning to some normal. My name's Mark Brayan, I'm the Chief Executive. I'm joined today by our Chief Financial Officer, Kevin Levine, and our Head of IR, Rosalie Duff. The presentation was loaded to the ASX website this morning. I'll be referring to that throughout. The presentation will take 30-40 minutes, and then we'll open it for questions. We aim to finish at 12:00 P.M. Sydney time.
As a reminder, before we get going, all the financials are in US dollars. This year's presentation is a little richer than prior years. It includes an update on our market, an overview of our business, and importantly, the outcomes of our growth strategy review that we undertook last year, and of course, the financial results. To page five to start. Our vision is to make AI work in the real world, and AI relies on training data, and it needs high quality data to perform well. We aim to be the number one provider of data for the AI life cycle, and by doing so, we'll help our customers build high quality and responsible AI. We're a full service provider. Our products cover the data-heavy steps of the AI life cycle, data sourcing, data preparation, and model evaluation.
We deliver our products with a combination of our tech platform, our expertise, and our crowd. We're pleased to announce record revenue of $447 million this year, and EBITDA of $78.9 million, and that's before the impact of foreign exchange. We've grown revenue at 40% per annum over the last five years, which is an extraordinary achievement, a credit to our talented team. We delivered into the second half skew that we forecast at the first half. This was underpinned by a 32% half-on-half increase in global services revenue. This is revenue we derived from providing crowd services to our large tech customers. The sharp uptick in this revenue returns it to its year-on-year growth trajectory and shows the health of our customers.
We're also doing very well in China, with revenue up 422% on last year on the back of strong sales to the tech giants, autonomous vehicle and mobile sectors. We count the world's most advanced companies amongst our customers. Google, Amazon, Microsoft and others have relied on the many modalities of high quality data that we provide them for many years. Some of the world's best known products are powered by our training data. This is a tremendous achievement for an Australian company and one that we're very proud of. To page six now, our non-financial impact. Our global crowd of over 1 million contributors is essential for our business and the data that we provide for our customers. It's also a responsibility. We are a member of the Global Impact Sourcing Coalition that creates opportunities for people in developing countries.
Our recent crowd survey told us that 17% of respondents were long-term unemployed before they found work with us, and 16% lived under the poverty line prior to working with us. 63%, almost two-thirds, use the money they earn from us to support their households or their education. We're supported by our talented global and diverse team of linguists, engineers, data scientists, project managers and other professionals. This talent and diversity helps us deliver unbiased data for our customers. We've also increased female representation at senior management and board levels this year to 38% and 50% respectively. Our business has a low environmental footprint, but we're committed to reducing it nonetheless. We've completed an inventory of our Scope 1 and 2 emissions and will be net zero by 2030. Page seven brings the impact of our work to life.
We worked with one of our customers to ensure that their language generator was inclusive, unbiased, and that it worked for everyone. We did this by using a diverse team of contributors from our global crowd. They were from different cultures, ethnicities, genders, ages, and they tested the product and they provided the test data for our customer to tune the product so they would ensure that it worked in the real world for everyone. We've all heard horror stories of AI that behaves badly, so we're very pleased to be working with our customers to ensure that their AI works well for all of their users. To page nine and the AI market.
A recent survey by PwC showed that not only was the use of AI becoming more pervasive and mainstream, but half of the companies they surveyed had accelerated their AI plans because of COVID. This is due to many reasons, including the need to alleviate staff shortages. Some of our customers are building chatbots for customer service as their customers and the need to look after them runs ahead of their ability to attract and train staff. The growth in AI is driving the need for training data, as you can see from the chart on page 10. This chart from research firm Cognilytica is very important. It's some of the first comprehensive research on training data. We're often asked if techniques such as self-supervised learning will make training data redundant.
Our view has always been that the need for training data will continue to grow alongside the emergence of new technologies, and this research confirms that. The chart shows the growth of different training data delivery models. Full service, where the vendor provides the technology, crowd labor, and project manager management to deliver the required training data. Labor only, where a vendor uses a third-party platform or customer technology and provides the crowd or BPO labor. BPO business process outsourcing. Non-managed crowd, where the vendor provides the technology and access to a crowd but doesn't manage the process for its customers. Labeling tools, where the vendor just sells the tech platform and supports the customer on that platform, but doesn't provide the crowd or project management.
Finally, synthetic data, which is an emerging but important area to watch, where data is fully synthesized and comes complete with labels. Now we are a full service vendor, and we participate in the majority of these delivery models to varying degrees. We provide fully managed service as well as labor only using our customer platforms. We also have customers that use our platform and access our crowd without our management or support. Now, on the right-hand side of the page, you can see that customer needs are evolving, but we hear many of the same themes, year on year. Firstly, that scale and quality are important. The latter quality is particularly important. Poor training data leads to poor AI.
Now, synthetic data will play a role, but the nuance and the specificity and the quality requirements for training data see a continued reliance on humans, as you can see from the chart on the left. Plus, not every stage of the data lifecycle can be automated or synthesized, as we'll see in a few slides. An area that's been with us for a while, but it is emerging in its importance is trust and privacy. Data privacy, ownership, governance, provenance are all emerging as must-haves for anybody dealing with data. Another thing we learned this year is that because AI is experimental in its nature, you don't know the outcome until you build it. Our full service customers need to be agile, and they're reluctant to commit to data volumes or annual spend.
We're putting our customer needs ahead of us, ahead of ours, and hence, committed revenue is not a focus for us and we won't report on it henceforth. We support all these customer needs and requirements very well, and we are the market leader as the chart on page 11 shows. We are close to double the revenue of our nearest competitor and many times larger than the others. We've achieved this position through a close alignment with our customers and their needs. We're trusted to deliver and to look after our customers' data. We maintain our reputation for high quality data and our platform, people, and crowd combine to support our customers' needs for usability, scale, and speed. Our 25 years of experience give us depth and unparalleled expertise. We maintain a strong position against our competitors. We have capacity and scale that betters the biggest players.
Sorry, over the page. Pardon me. To the competitor grid. We maintain our position against our competitors. We have the capacity and scale that betters the biggest players and the breadth of technology that keeps us ahead of the tech-forward competitors. Both of these elements, capacity and technology, are necessary in our market, and the depth of our capabilities is an effective moat vis-à-vis our competitors. To page 14 in our business on a page. We are and will continue to be the number one provider of data for the AI life cycle. We provide what our customers need trust, quality, usability, scale, and speed. Our products support the data-heavy stages of the AI life cycle. We collect and originate training data for our customers in many ways and in many data modalities. We've done this for years, and we continue to enhance our capabilities.
For example, with the recent acquisition of Quadrant and our ability now to collect point of interest data. We're also working on some synthetic data. It's early, but this will play a role. We prepare data for ingestion and models by labeling and/or organizing it subject to the requirements of the use case. We do this with our crowd and using machine learning to automate these processes to improve our scale, quality, speed, and the value we provide to our customers. We leave the model training, that is the development of the model and deployment to others. Building models is compute heavy, and that's not our core competence. There are others that are far more expert than us, so we're building partnerships with them to be part of their ecosystem and to help them support their customers. Finally, we provide essential evaluation and testing service.
Much of the relevance work we do falls into this category. We provide specific crowd cohorts that respond to the demographic needs of our customers in order to test their search and social media applications at scale. We deliver our products with a combination of our technology platform, our crowd, and our expertise. All are essential, and the extent of each varies depending upon the project and the use case. We cater for all data modalities from text, image, audio, video, three-dimensional lidar, multimodal data, and point of interest. Our ability to cover all of the data-heavy stages of the AI life cycle, all customer requirements, all delivery modes, and all data type make us a truly unique and powerful full-service partner for our customers.
We invested in a refresh of our growth strategy last year, and I'd like to take you through that now. If you could turn to page 16. Our growth strategy has four core pillars. We'll continue to grow our revenue and diversify our customer base. We have five customer-facing business units to ensure a focus on our customers, as well as growth outside of our large global customers. Our BUs global, supporting the five tech giants enterprise, who support commercial customers in the U.S., Europe, and Asia-Pacific. China government and Quadrant are all highly focused on their customers and have the resources they need to win and deliver in their markets. The next pillar is automation, and we're seeing early success in our efforts to automate crowd and labeling processes.
We'll continue to rely heavily on the crowd, of which more later, but our automation will reduce the cost of the crowd and enhance the speed, scale, quality, and value of the data that we provide for our customers. Our data science team is an important enabler of our automation strategy. We're expanding our product offerings. We wanna be a one-stop-shop for training data needs, so the more use cases we cover, the less reasons our customers have to go to our competitors. We have point-of-interest data, and we're exploring synthetic data. We'll continue to invest in product and engineering to enable this expansion. We're also working to evolve and transform our internal processes. We're investing or we have invested in a transformation office to enable this change.
We have many complex and manual processes such as recruiting our many crowd workers, and we're working to streamline these to improve the service that we offer to our customers and crowd and enable our teams to focus on higher order work. Implementing this strategy is a journey. We've set ourselves three long-term five-year goals. The first is to grow and at least double last year's revenue by 2026. Secondly, to diversify. We wanna have more than 1/3 of our revenue from our non-global customers, that is customers outside of the five U.S. tech giants. Of course, we're a profitable business, and we'll maintain that and set ourselves an EBITDA target, a margin target of 20% by 2026. It is a journey, but we're on our way and you can see some progress on page 17.
To support the growth pillar, we expanded operations in China in 2021, hired a new leadership team for enterprise headed by Jen Cole, and hired Sujatha Sagiraju as our Head of Product. Jen and Sujatha are highly skilled and impressive executives and have made an immediate impact. Their bios are on our website. For our automate pillar, we've pulled together a world-class data science team, and they've developed models to automate speech data preparation. We're active on customer projects with these models. We'll deliver these projects, improve the models, and move on to the next project and the next use case. We've added new products this year. Point-of-interest data via the Quadrant acquisition, we've had great success with our autonomous vehicle products in China, of which more later. Finally, we've built our transformation team, headed by Eric DeCaux, who's an experienced change executive.
He and his team are deep into the process analysis improvement stage of our transformation project. We lay out some of the 2022 steps and investments on the page as well, all of which contribute to the goals on the right. We'll update this slide as we progress along the journey. We now dive a little deeper into some elements of the strategy, starting with automation on page 18. As a full service provider, we need our crowd, our expertise, and our technology in different measures across the AI life cycle. This chart shows the relative human involvement and automation potential of the different stages. Data collection, for example, is highly manual. You need humans to speak into their phones if you're collecting speech data, or to take photos of buildings if you're collecting point of interest data in the field.
Now, steps can be automated for efficiency, but humans are essential, as they are for model evaluation and relevance, which is on the right-hand side of the chart. Contrast this, for example, with synthetic data. This is compute intensive and highly automatable. Humans play a limited role. Automation is important, and we're investing to deliver its benefits for our customers. Not all elements of the AI life cycle can be automated to the same extent. Our crowd and those related capabilities give us an effective moat against competitors in these areas. Relevance, the bulk of our revenue is crowd dependent, and hence the risk of disruption by automation is very low to non-existent. Page 19 highlights one of our new products. We're having great success in China in the autonomous vehicle market.
Autonomous vehicles require vast amounts of training data, and we're working with 11 auto companies in China, as well as over 20 other tech companies, such as drone providers, who are investing in autonomous mobility. Slide 20 highlights point of interest data. Point of interest or POI is important to keep maps up to date, especially now given COVID. For example, small businesses that have closed may still appear open on the maps, and it's important that that's all updated. The Quadrant product enables very efficient collection of point of interest data, and the data supports mapping, e-commerce and marketing applications. There's also an interesting intersection between point of interest or geolocational data and augmented reality. I'm sure there'll be apps in the future that detect where you are and automatically provide directions or translations and other information via wearable devices like glasses.
It's a pretty interesting area of technology and one that we're glad to be part of. Let's turn now to the financial performance starting on page 22 and an outline of our reporting segments. We have two reporting segments and five customer-facing business units. The reporting segments reflect our product-led strategy. For example, we have global services, which are the services that we provide the leading U.S. tech companies on their platforms. We have new markets, which is all the customers that we support, including some of our global services projects on our platform, on our technology. Our five customer-facing units include Global, which are the five largest U.S. tech companies. Enterprise, which cover other companies in North America, EMEA and Asia Pacific. Government, federal agencies. China, which now encompasses China, Japan and Korea and q uadrant, the provider of location data.
Over to page 23 and the financial highlights. We had another record full year revenue performance. Revenue was up to $447.3 million, and that was up 8% on last year. Key drivers were a sharp uptick in global services revenue in the second half that grew 32% on the first half of FY 2021. New markets revenue was also up sharply, 21% to $102.5 million, and that was driven by a very high increase in revenue in China. Underlying EBITDA before foreign exchange grew 12% to $78.9 million, and that was driven by the revenue growth and some gross margin expansion in the second half.
We maintained a strong balance sheet, $48 million in cash and no debt as of December 31, 2021. We're pleased to provide a final dividend of $0.055 per share, and the total dividend is flat on 2021. Digging into the segments now to page 24 in global services. The chart on the right shows the uptick in global services revenue from the first half to the second half. That came on the back of a number of expansions of existing projects and a number of new projects in the second half. This was consistent with the skew that we called out at our first half results. Overall, revenue was up 5% to $344.7 million and EBITDA up 3% to $91.2 million.
To our next segment of new markets, and you can see sharp year-on-year growth of 21% to $102.5 million and a pleasing half-on-half trend. China played a big role in this growth, as we'll see in later slides. Over the page to page 26 and the global customers. Global revenue overall was up 3.4% to $386.3 million. You can see again that return to growth in the second half on the right-hand side. Importantly, you can also see the percentage of projects that we're working on with our customers that are not related to ad products continues to climb. This is very important and shows that our customers are investing in AI products outside of advertising.
To page 27 and just a little bit on the digital advertising market, which is important. First of all, the advertising market, which underpins a lot of the revenue of our biggest customers, continues to grow. Very healthy upward trend for digital ad spending worldwide. It is a dynamic market. As you're all aware, there are many changes in the market, including, for example, the recent change to the iOS operating system that impacts the data that search and social media companies can collect from Apple phones. What this means, the combination of those dynamics and the chart on the left mean that spend is still happening, but it's shifting between vendors. What it also means is that the major search and social media customers, companies of which many are our customers, are working hard to solve this problem to return to those highly personalized ads.
The impact of these trends on us is threefold. First of all, we're working with our customers to build products that are not related to ads, which is to our advantage. We also work across many of these companies, both in the U.S. and China. As ad spend, which is growing, shifts from one to the other, then that can be advantageous to us as well. Finally, as our customers look to solve this problem, it may provide opportunities for us as they seek new sources of data to create highly personal ads. Over the page now to page 28 and our other BUs, Enterprise, China, Government, Quadrant. Strong growth, 2021 revenue of $60.8 million, up 55% on FY 2020. This was a lot to do with success in China, but the other business units played their part.
You can see on the right-hand side, tremendous growth in those business units, and very important for us to improve the amount of diversity that we have in our customer base. The revenue that we derive from these customers is now 14% of our total revenue, which is up from 9% last year. Over the page to page 29, and the chart, as you can see on the left-hand side, quarter-on-quarter revenue in China is growing extremely healthy. Our customers include the tech giants, social media companies, mobile providers, and autonomous vehicle companies. As I mentioned earlier, we have 11 of the leading AV companies or autonomous vehicle companies as our customers. We have more than 20 other tech companies, such as drones and robotics, that are using our data for autonomous mobility.
Now, the China operation is highly focused on growth. That includes growing projects with existing customers as well as new customer acquisition. We are on track to be the market leader in China. We're very pleased with progress there, and we see further growth, further high growth in China. Turn to page 30, an update on our other business units. The enterprise team had a solid year, but yet to fully reach their potential. They're winning a lot of projects and winning a lot of customers. Of course, we have a new leadership team there, highly focused on accelerating growth. Our government team was successful recently in being selected in the partnership for the Joint Artificial Intelligence Center blanket purchase agreement to support AI, the development of AI capabilities.
That positions us to win projects with a number of agencies. Quadrant is integrating with the business and winning work with the Appen customer base, including many projects or a number of live projects with some of our largest customers. I'll now hand it over to Kevin for page 31 to take you through the rest of the financials.
Yeah. Thank you, Mark. So on slide 31, our revenue and other income increased 8% to $447.3 million. This reflects a strong half-on-half performance with the second half up 28% on the first half. Reversing the first half decline of 2%, and that's comparing to the prior corresponding period. There were two major drivers for the record second-half performance. Firstly, global services, which delivered a significant turnaround from the first half revenue reduction of 9%, with second half revenue up 19% versus the prior corresponding period, and up 32% on the first half of FY 2021. This record second-half revenue performance was driven by continued increase in non-ads and with ad-related projects returning to growth as forecast.
This highlights the value that our global customers place in our ability to deliver high quality data at scale across all data modalities. The second driver was China, with 422% growth coming from both increases in market share, i.e., from new customers, as well as in customer share, i.e., expansion from existing customers in new and existing projects. Underlying EBITDA, excluding an FX loss of $1.2 million, increased 12% to $78.9 million. This result and the associated margin was positively impacted by strong second half drivers, namely revenue growth, gross margin expansion, and moderate expense increase to support the growth. Underlying NPAT reduced 10%, impacted by increased amortization of product development investments. The effective tax rate of 20.5% is in line with the prior year.
The effective tax rate is subject to fluctuations from the tax effect of movements from expensing, investing of employee performance shares, and differences in overseas tax rates. Excluding these fluctuations, we have reduced the normalized tax rate to 25%. Over the page on to the balance sheet on slide 32. Balance sheet remains strong and resilient with no debt. Trade receivables increased by $38.6 million to $89.2 million.
Increase in trading volumes approaching year-end. Invoices were raised on 30 December for work completed in December as the milestones were satisfied. This resulted resulted in a corresponding decrease in contract assets. Non-current assets comprise mainly goodwill and identifiable intangible assets, mostly arising through acquisition. Following a detailed impairment review, we report adequate headroom in the carrying value of these intangibles. Non-current assets increased mainly due to $45.4 million being recognized as goodwill relating to the Quadrant acquisition. Total liabilities increased by $19.1 million to $107 million, mainly due to the earn-out liability of $18.4 million associated with the Quadrant acquisition. A final dividend of 5.5 Australian cents per share has been declared. This is in line with last year and is 50% franked.
This takes the full-year dividend to 10 Australian cents per share in line with FY20. Over to page 33. In 2021, we invested $30.2 million in product development. representing 6.8% of revenue. This focus is important to drive customer growth and repeatability, as well as quality improvements and margin expansion. In FY19, we are strategically investing in engineering resources to develop new products. 68% of our product spend was capitalized in FY21, up from 64% in the prior year, reflecting our commitment to development of new products and tools. We will continue to invest in product development of up to 10% of annual revenue. Moving on to slide 34 and the cash flow. The cash on hand at year end decreased by $12.6 million.
However, this was due to the upfront payment for Quadrant of $25.3 million. Cash balance and cash conversion were impacted by timing issues, primarily due to the working capital cycle impact from the higher volumes in November and December.
Cash flow from operations reduced by $17.9 million due to the aforementioned working capital cycle impact. However, this was somewhat offset by lower tax payments. Cash has been effectively deployed for product development. Dividends, uptakes, and growth investments. Notwithstanding the cash flow cycle impact, the cash flow conversion from EBITDA was still solid at 67%. Thank you, and I'll hand you back to Mark..
Thank you very much, Kevin. To conclude, and to move now to page 35, we're very pleased with our performance in 2021. We also refreshed our growth strategy to transform the business with a focus on revenue growth, customer diversification, automation, and product expansion. Implementing this strategy is a journey, so we're taking a long-term view and we've set ourselves five-year targets as our North Stars. Those targets are to at least double our FY 2021 revenue by 2026. This demonstrates our focus on long-term revenue growth. We're off to a good start. Our revenue order book for this year, which includes year-to-date revenue plus orders in hand, stands at $190 million.
We also expect the FY 2022 half-on-half revenue skew to be similar to prior years, excluding FY 2020. The second target is to improve the mix of customers with 1/3 of revenue from our non-global customers. That is 1/3 of revenue from customers other than the five U.S. tech giants. We'll achieve this with investments for growth in new products, sales and marketing partnerships. We'll explore M&A opportunities, and we're targeting higher than 35% compound annual growth revenue from non-global customers. This is in line with the market growth rate of the chart earlier in the deck. Finally, we are a profitable business, and we'll maintain that. We set ourselves a long-term goal of 20% EBITDA margins. Our focus on revenue may impact near-term EBITDA margins and future dividend payout ratios.
This long-term focus also means that we will no longer provide short-term EBITDA guidance. A few things, higher costs in the first half of 2022, including the transformation office, investment in product and technology, and share-based payment expenses, will impact first half earnings this year. There'll be an earnings skew to the second half, which could be larger when compared to FY 2021. In closing, I'd like to thank our customers for their support and especially to thank all of our talented and hardworking teammates around the world. We appreciate everything they do for us. This result is theirs, and I'd like to thank them. Now I'll hand it back to the moderator to take time for questions. Thanks very much.
Thank you. If you wish to ask a question, please press star one on your telephone and wait for your name to be announced. If you wish to cancel your request, please press star two. If you are on a speakerphone, please pick up the handset to ask your question. Your first question comes from Josh Kannourakis with Barrenjoey. Please go ahead.
Hi, Mark and Kevin. Can you hear me okay?
Yeah. Hey, Josh, how you doing?
Yeah, good. Thank you. Good. Just first question, just with regard to, you know, some of your core customers. You mentioned that the non-ad related projects obviously saw some good growth in the period, and that was on a project basis. Would you be able to give a bit more context on how that's come through on a revenue basis and just how, I guess, you know, your comfort , I guess, in the future outlook of some of those non-ad related projects?
Sorry, the line on page 26 that gets to 77%, that's revenue.
Okay.
The non-ads revenue is 77%. Sorry if I misspoke.
Yep. No, that's fine. I guess in terms of those projects, though, 'cause obviously they're still at early stages, is it too early also for you to say in terms of the potential materiality, you know, long term from those projects?
Yeah, it's hard on a project by project basis. You know, some of them are to do with augmented and virtual reality, for example, which we know is a growth focus for some of our customers. It's hard to know how any individual project will play out, but they're in areas that are growth focus for the customers. Another one is e-commerce, another growth area. Another area is mapping. These are all in forward-looking areas, but hard to tell how an individual project may play out at this point.
Got it. I guess some of our industry feedback has suggested data collection works have, you know, been quite a significant part of the market or a growing part of the market. Would you be able to comment on, you know, I guess, how you've seen those trends there and, you know, Appen's ability to capture share of that market on a go-forward basis?
We have seen an uptick in data collection, and it is a competence of the business with our crowd-based model because, as I explained earlier in the presentation, you know, a lot of the data collection needs humans. Hence also the acquisition of Quadrant, which also goes to data collection. Yeah, I agree with the industry feedback you're getting. It's very important and we're very much in the thick of that. The reason why. Sorry, just add one more thing. The reason why data collection is important is because the best performing AI is typically narrow AI, something that does a very specific task. Correspondingly, you need data that's representative of that use case. Now, not all the data may be available from current sources or by the customer.
If they need a specific piece of AI that needs specific data, they have to go find that data and collect it, and that's what we're doing. Yeah, lot of different data collection projects currently.
Got it. Just final question, I'm sure there'll be a few around margins, so I won't spend too much time on it. In terms of, I guess, your longer term commitment versus the shorter term investment, should we be thinking about some of these shorter term investments as transitory in nature or more in terms of a step change in terms of how the business needs to operate and the costs it needs to put in to, you know, fulfill those growth objectives?
I think what we foresee immediately is more incremental, but we just need the flexibility to make those investments as and when they come up. It could be, for example, lighting up a team of people to, you know, build a particular model to automate part of the business. You know, we don't foresee any step change type investment in the near term, but it's not to say they may not come along, but it's more likely to be incremental at this point.
Got it. Is there any way or any comments you can make in terms of how you're thinking about, I guess, you know, obviously you talked it's gonna be below 20%, but is there any numbers you're comfortable talking about it being above in the period or on a go-forward basis to give people a bit of comfort?
Yeah. We wouldn't want the percentages to go backwards. You know, the objective is to keep going forward with a long-term view of getting to that 20% target.
Okay. That's great context. Thanks, Mark.
Yeah. Sorry, Josh, if I can just add to that as well. That is
Yeah. Thanks, Kevin.
Yeah. Obviously we're gonna manage the cost base and prioritize the spend, you know, to align with those long-term growth objectives. You know, around product development and expenses to support the growth. And then obviously, calling out in the short term, as we call out, just some impacts from some of the investments that we make in the transformation office and things like that. Yeah, very much aligning to the future growth and prioritizing the spend in order to achieve that.
Thanks, Kevin.
Thank you. Your next question comes from Siraj Ahmed with Citi. Please go ahead.
Thanks. Hi, Mark and Kevin. A few questions. Just first one, on the work in hand and conversion to revenue. Any change in how we should think about it? Last year, obviously it was second half skewed because of the major customers. How are the discussions tracking this year? It's up 15% year-over-year. That's pretty good. Just keen to understand how we should think about conversion.
Yeah, I think, hey, Siraj, I would on a full year basis, I wouldn't think any different to prior years. You know, there's always, you know, subtle differences year on year. In general, I'd think about it in a similar way.
Okay. Second thing, you're giving five-year target of more than doubling revenue. Just trying to understand, when you think about the growth trajectory over that five years, are you expecting growth to be faster in the first few years, slower later, or is it just consistent revenue growth?
We've obviously got a bunch of models that get us to those figures. There's different trajectories. I think the shape of the curve will depend upon the non-global customers more so than the globals. As you can see with the China chart that had a slower start and then got some momentum. I'd expect a little bit of a build, but probably more so from the non-global customers than the globals. Globals will be a little steadier.
Sure. Actually, just on the globals, again, the target implies that in global is growing at 7% year-on-year. It grew 3% this year. Just keen to understand how you're thinking about that and what gives you confidence that growth will be at around those high single digits%.
Yeah. We, you know, there are five customers in that cohort, and they all have their own characteristics and challenges. If we look at, you know, some of the things they faced, last year versus this year, we're pretty optimistic given the book of projects we've got with them, compared to where we were at this point last year.
Got it. That's helpful. Last one, just maybe for Kevin. Just regarding the margin comment, just confirming that we shouldn't be expecting margins to go backwards next year. That's the thing. Would you be able to quantify the level of investment? I mean, given the project office, but you also need to take costs out. Just keen to understand, you know, the level of investment that you're thinking about.
Yeah. We give the guidance of up to 10% of any one year. In terms of for this next year, you know, probably a range of 8%-9% is how we're thinking about our investment. As to Mark's point, the key thing for us is to build a foundation and a pathway, you know, for that future growth, and which means we may accelerate or decelerate at any point in time in order to do that. Within that overall framework of the 10%, probably around 8%-9% for 2022 in terms of how we're seeing it this year. In terms of the margins, obviously we have some which we've called out. We've obviously got some things going on, particularly just in 2022.
When you compare to 2021, obviously we've got cost of the transformation office. This will give us positive benefit only from 2023. We've also, when you look at the share-based payment cost, 2022 versus 2021 had an adjustment in their downward adjustment. Obviously expect you know normalized share-based payment costs coming through in 2022 and note the comparison you know with 2021, which is gonna impact things as well. Once again, these aren't anything that is really impacting us or bothering us from our long-term positioning, but just letting the market know in terms of how we're thinking or seeing things just in the immediate short term.
Okay. The earnings skew is more about those costs coming in the first half rather than the second half compared to last year. That's why the earnings skew is more skewed to the second half.
Yes. There's a couple of, you know, comparative pressures, you know, that impact that I've called out and obviously that impacts that skew as we've called out.
Okay. Super helpful. Thanks, Mark. Thanks, Kevin.
Thank you. Your next question comes from Michael Aspinall with Jefferies. Please go ahead.
Thanks. Good day, Mark and Kevin. I'd like to start on the order book. I mean, Siraj touched on this, but it's +15% year-on-year so far. Would you expect the first half or the full year to reflect that at the top line based on what you're seeing so far?
Hey, Michael. We do expect a half-on-half revenue skew, as we call it there, if you look at years prior to 2020, as a guide.
Yeah. Just thinking about the 15%, though, growth you're seeing in the first two months, call it, of the year. Would you expect at least the first half to, say, reflect that, given, you know, it's revenue already received for the first two months of the year?
This only includes revenue for January, to be clear.
Mm-hmm.
I'm not sure I understand the question given we're calling out that half-on-half skew. I think that's your answer there.
Yeah.
Okay.
I think there are two data points there, Michael, just to take away. Basically, the methodology here is that these orders are for the whole year, so you can't really draw any necessary comparisons as to a certain period, it is most representative over a full year period, [that] is the first data point, and then take the other one where we talk about the skew. Both those data points will help you with that.
Okay. The full year could be a 15% growth, but the first half might not be.
Yeah, you've got the data points that help you with that skew.
It sounds like you saw a return to growth in the large legacy projects in the second half. Just confirming that that's right. What drove the customers to return to investing in that area?
I don't know if legacy program is the right way to put it. There are a number of large programs that we support with our customers. There's built-in seasonality in some of those programs. For example, those that deal with advertising tend to pick up in the second half because of the retail season. I think that was as the season would have it. Really what we saw was, you know, newer projects picking up in the second half that were consistent with customer strategy to, you know, build non-ad related projects, for example. It was a blend of both. I think on the large core programs that we support, there's always a degree of seasonality there.
Okay. You showed us some numbers at the half. I think it was projects started prior to calendar year 2021 and projects started in calendar year 2021. I mean, if we just have that in the back of our minds, it sounds like we should expect those projects that started this calendar year have contributed more than what they had in the first half on a proportional basis.
Yeah. We get new project starts all the time. Sometimes they take a little while to ramp up, sometimes they ramp up very quickly. Yes, we had some projects start the first half that ramped up into the second, and then some that started fresh in the second half that delivered material revenue as well.
Okay. Yep, that's interesting. Last one from me is kinda follow up on Siraj's question. You mentioned that the target in 2026 is for 1/3 of revenue to be from non-global customers, which implies that 2/3 will be from global customers or revenue going from $340 million odd last year to $600 million in 2026. I'm just interested in how much consultation you've had with your global customers on that medium term perspective.
We obviously work very closely with our customers on, you know, their needs. That gives us a view of the demand for data. It's a combination of existing projects and some assumptions for some new projects. Yes, there's some customer input there, but there's also, you know, we're backing our ability to find new projects and continue to deliver into existing ones.
Okay. There is some input there from customers in terms of that 3, 4, 5-year outlook?
Yeah. The customers wanna make sure that we have, you know, in addition to the, you know, the quality of data that we provide for them. The customers are always keen to know that we've got new ideas to bring to them. We do have, you know, forward-looking conversations that inevitably go to, you know, some discussion around, you know, capacity and volume. Having said that, they don't lay out specifically what their requirements are, because their businesses are very dynamic, and they rely on us to be dynamic and agile to support them as they need us to.
No, that's helpful. Thanks very much, guys.
Thank you. Your next question comes from Xavier Waterstone with QuayStreet Asset Management. Please go ahead.
Morning, Mark and Kevin. Just a couple from me. First one, positive to note that there's a clear disclosure of the development capitalization and amortization on slides 33 and 38. I'm just curious, though, given the enduring nature of a lot of these costs, especially the development spend, whether EBIT margin should be the focus rather than EBITDA as a better reflection of economic profitability?
Yes. I'll take this one, Mark. Yeah. We certainly consider this. What we do as well is we look at ourselves compared to our peers as well, and we look at those levels of development as percentage of revenue. Essentially what we've derived from that research and comparison is that a lot of companies, similar type peer companies and other companies, all disclose on an EBITDA basis, even though they have higher levels of development as a percentage of revenue. At this point in time, we would consider ourselves an outlier just going to the EBIT relative to everyone else that's on the EBITDA. It is something that we consider. Given our levels of spend lower than a lot of others, we've...
We're reflecting and we're looking to report at this level for the time being.
All right. Cool. The second one was, I guess I understand, you know, the comment about no longer providing short-term guidance. It's understandable given the volatility of some of these revenue and contracts. Second question, I guess is it looks like, you know, given a surprise magnitude of today's share price reaction, probably partly reflects a bit of a lack of confidence and timeliness in continuous disclosure. Can the market expect anything in terms of more frequent or substantial, you know, just business operational updates to help address this trust and information gap?
I'm sorry, I was offline talking to the moderator. Could you repeat the question?
The question was, I guess, you know, understanding your comment about no longer providing short-term guidance, you know, given the surprise magnitude of today's share price movement and, you know, some of that being a lack of confidence and timeliness in continuous disclosure, whether the market can expect anything in terms of a more frequent or substantial business updates, to help address this information gap.
We've always provided information as we've been required to do so. We'll continue with that policy. If there's anything that we feel is in the interest of the shareholders, then we'll provide that.
Okay. Thanks for that.
Thank you. Ladies and gentlemen, we have five minutes remaining with us. Your next question comes from Garry Sherriff with RBC. Please go ahead.
Hi, Mark and Kevin. A couple of questions. First, the FY 2026 goals, they're looking ambitious. Does that include any acquisitions for those goals? If you could clarify for us.
No, not material acquisitions, Garry.
Understood. Thank you for that graph on the competitive landscape. It's very helpful. You flag after Lionbridge and Scale, the next largest competitor. Who is that? The follow-up question is, do you find any of the assets that you've flagged or companies you've flagged, do they have anything attractive that you think could be beneficial under the Appen umbrella?
The fourth one is a blend of information that we've picked up in the market. There are some competitors in the tens of millions of revenue in the $30 million-$50 million range. It's just a blend of people. The point of the chart is to show that, you know, Scale has put out a figure about their revenue. The others, we pick up things from time to time, but they're gonna be around that size. It's not a specific company. It's just representative of where the fourth place competitor is.
You know, in terms of other companies on the slide and do they have things that would be beneficial, look, we look all the time, Gary, at you know, companies in the space and whether or not we could you know, combine with them, bring them under the Appen umbrella as you say. Oftentimes, though, they're fairly early and you know, loftily valued to be candid. You know, we just have to be very careful and strategic about some of the things that we look at. I'd also say that most of the companies on the chart have you know, are tech forward.
When we look at the technology and the capabilities we've got, you know, there's a fair chance we can build it ourselves at a better return to shareholders than combining.
Understood. Just going back to the ad-related revenue being, call it 25% group revenue. Has there been any insights in terms of your discussions with Facebook in terms of volumes for calendar year 2022 versus last year, given that they're clearly a big contributor to your ad-related revenue?
The order book number is obviously inclusive of a lot of work with our major customer. I think that's probably the best answer I can give you there, Garry. You can draw some inference from the size of the order book number.
Yeah, no trouble. Last one on China. Maybe let us know who some of those customers are, and if you could provide us any detail on the margins, gross margin or EBITDA margin, that would be beneficial?
Yeah. You know, many of our customers, as you know, are building future-facing products, and they're not keen for us to talk about who they are. We've managed to get permission for a number of logos, as you can see throughout the deck. None from China, though. I can tell you that all of the China tech giants are our customers. I can also tell you that the major mobile companies are our customers, as are the major autonomous vehicle companies. You could probably find a bunch of them pretty quickly, just with some searching. In terms of gross margins and EBITDA margins, we haven't disclosed those, but I can say that we're still investing into China.
I can also say that the gross margins are improving. That said, the focus in China is very firmly on growth and you can see that that's paying dividends for us.
When you talk about, you know, some of those large Chinese tech giants, is there any reason why then you'd classify China as being non-global in terms of when we segment them as customers? I just noticed that in terms of that non-global customer base, you flagged it's China as being non-global. I would have thought some of those Chinese tech giants would be.
I guess it's in the name. I mean, our global customer base is the five big U.S. giants because that's where we derive the bulk of our revenue, and everything outside of that is non-global. Some of our customers outside of that are sizable, but just by our definition, the global is those five U.S. tech giants. I assume that did, Garry.
Yes. Sorry. Yep. Fine from me. I thought the moderator had cut me off, but yes, that's great. Thank you.
Thank you. Ladies and gentlemen, that was the last question for today. I'll now hand back to Mark Brayan for closing remark.
Yeah, thank you very much, and thank you everybody for joining the call today. As I said earlier, we are pleased with our results this year and firmly focused on those five-year goals to reiterate to at least double our 2021 revenue by 2026, to have 1/3 of our revenue from our non-global customers. As per the response to Garry there, the globals are the big five U.S. tech giants and have 1/3 of our revenue from outside of that. Finally, to continue to be a profitable company with an EBITDA margin target of 20%. Thank you once again, and I'm looking forward to meeting you in one-on-one meetings that we may have. Thanks very much.