Earnings Transcript for APPEF - Q2 Fiscal Year 2021

Operator: Thank you for standing by, and welcome to the Appen Limited First Half '21 Results Conference Call. [Operator Instructions]. I would now like to hand the conference over to Mr. Mark Brayan, CEO. Please go ahead.

Mark Brayan: Thank you, and hello, everybody. Welcome to the conference call for Appen's first half results for 2021. Before I start, I hope you're all safe and well in the pandemic and for those in Australia and during the lockdown as best as you can. My name is Mark Brayan, Chief Executive. I'm joined today by our CFO, Kevin Levine, and our Head of IR, Linda Carroll. Our presentation was loaded to the ASX website this morning, and I'll be referring to it throughout. We'll take questions after the presentation. Just as a reminder, all of our financials are in U.S. dollars. So to Page 3 to start, we operate in a dynamic, growing and exciting market. We provide training data for artificial intelligence and counts the world's largest tech companies amongst our customers. Training data is essential for the development of AI products. There is no other way to build AI than with training data. Just as we learn from books, conversations and classes, AI learns from data and improves with the amount and the quality of that data. Our market sits within a broader AI ecosystem that's forecast to grow to $110 billion by 2024. The market is growing due to an explosion in AI use cases, including areas where we have deep experience, such as speech recognition, chatbots and search engines to new applications, including augmented and virtual reality and geolocation data. AI mimics many things that humans do such as speech vision, decision-making, et cetera. So the need for human curated data is very strong. It offers the highest quality outcomes. We're able to provide large diverse sets of human curate data via our global crowd. But our customers want large volumes of quality data very quickly. So we blend our crowd and our own AI to increase the volume and speed of data provision with techniques such as AI-based pre-labeling for example. Beyond data, there's a growing need for more AI development tools and services such as data audit, data management, model testing and life cycle management. Our growth rate reflects the market. We've grown revenue at 38% annually over the last 5 years, and our new markets are up 31.5% half-on-half. This is driven by sales into our enterprise China and government markets as well as product-based revenue from our global customers. We continue to invest to make the most of the opportunity before us. We invested 10.8% of revenue and product development in the first half of this year. Welcome to Sujatha [ph] as our Head of Product Development, and today announced the acquisition of Quadrant to expand our location-specific data capabilities. To Slide 4. Our transformation to a product-led business announced in May this year is well underway. We now cover more data types and our language-based origins, including tech speech, image, video, 3-dimensional LiDAR data, augmented and virtual reality data geolocation data, which range from satellite imagery to granular on-the-ground points of interest. Our ACV is growing up 16% in the half, and we're adding to our customer base with 74 new customers this half, and that improves the resilience of our business. To Page 5 and the result highlights. As we advised in February, first half earnings were impacted by the skew in project delivery to the second half. Group revenue of $196.6 million was down 2% on the first half of last year, due to lower global services revenue as a result of our major customers prioritizing new nonadvertising product developments. Global Services revenue includes the work we do for our global customers on their platforms and includes many of our large relevance programs related to digital advertising and search. Group revenue growth was also dampened by the strong result in the first half last year that had negligible COVID-19 impact. In contrast, new markets revenue of $47.8 million was up 31.5%, driven by China, new enterprise customer wins and product-led growth, including many new projects for our global customers on our platform. Reflecting near investments in nonadvertising products. Underlying EBITDA for the half was impacted by the higher first half cost base and our restructure in May resulted in changes to the cost base that will yield benefits in 2022 and those benefits will be largely reinvested. Our balance sheet remains strong with $68 million in cash and no debt as of the 30th of June '21. We're also pleased to provide an interim dividend to shareholders of $0.045 per share. Over the page to Slide 6, and our key focus areas provide a road map for the rest of the presentation. We're focused on maintaining and strengthening our core as the global leader for AI training data. We continue our expansion into new markets and our ongoing development towards a product-led future. Page 7 emphasizes strength of our core business. We've grown at a compound rate of 38% over the last 5 years to become the world's largest provider of training data. Our technology in Crown underpin the strength and scalability of our business. We're able to respond to all data types and use cases because of these core assets. Our customer relations are also key to the strength of our business. We are trusted and relied upon to deliver high-quality data fast and cost effectively and securely. Our focus on responsible and unbiased AI is essential for our customers. Page 8 -- and you can see that our Global Services revenue of $148.8 million was down 9.2% on last year. This revenue derived from the work we do on our customers' platforms, and typically includes our large relevance projects was down as a result of our customers prioritizing new product developments as they diversify beyond ad-related products in response to regulatory scrutiny and ongoing privacy concern. Their investments in new product development is visible in our global product revenue on the right-hand side of the page. This revenue is derived from global customer projects on our platform and includes many new used cases. This revenue is growing at 32% annualized compound growth and is an increasing proportion of our global revenue. Some of our large customers have in-house platforms for certain use cases such as relevance. Our platform covers all data types in many used cases and provides utility unavailable with in-house platforms. Page 9 illustrates the impact of changes to the online landscape. The revenue we derived from ad-related projects was down this half as customers prioritize their resources towards new product development. Non-ad related revenue was up half-on-half reflecting our customers' ongoing commitment to AI product development and maintenance. We mentioned in prior releases that our results were impacted by the deferral of a few large projects. This chart shows that those large projects predominantly adjusted ad-related and reflect market forces, including increased regulatory scrutiny and privacy concerns. Our large customers rely on ad based revenue. We expect revenue from ad-related projects to grow in the second half of this year, but at a lower rate than non-ad projects. Slide 10 further dissects the direction of our large customers. In the first half of '21, we derived $20.3 million from 100 projects that commenced this half. The balance of our global revenue, $150.8 million came from 185 existing projects. This shows the extent of development in new projects and that projects can start small and grow over time. Also, 97 of the 100 new projects cover a range of non-ad applications, showing that our ad-based customers are investing in new areas. We do see some new ads projects though. We expect that the future ad solutions that solve regulatory and privacy issues will be data and machine learning based, and our capabilities and strong relationships set us up nicely to support our customers on these projects. Slide 11 shows some of the use cases we're working on with our global customers and illustrates the range of applications from augmented and virtual reality to geolocation in e-commerce. Slide 12 now, and our push into new markets is going well. New markets captured the success pardon me, of our product-led and customer expansion strategies and includes product-based revenue from our global customers, along with revenue from our enterprise China and government divisions. New markets grew strongly this half as illustrated on Slide 13. Up 31.5% on the first half last year. Growth was driven by a combination of factors that mainly China, enterprise and global projects on our technology platforms. New Markets EBITDA reflects the ongoing investments to grow product-based revenue and further diversify our customer base. We won 74 new customers in the half, giving us over 320 active customers. The chart on the right shows a solid start to the year with respect to new customer wins. Slide 14 breaks out our global product in Enterprise China and government divisions. Both are growing well, 32% and 27% annually, respectively. Product revenue is more retentive than services revenue and the fluctuations in the global product chart are due to variations in data volumes that occur as part of the natural life cycle of an AI product. To Slide 15 now and 2 views of our committed revenue. Annual contract value or ACV on the left, and how that translates as a percentage of our total revenue on the right. Progress this half hasn't been as rapid as prior halves, but we are nonetheless very pleased that we've improved revenue quality and visibility. China on Slide 16, is progressing extremely well, maintained its very high growth rate of 60% quarter-on-quarter. Growth is coming from China's tech giants, new customer wins, and we are building a good position in the autonomous vehicle market. Our team in China have their own technology stack to give them the agility they need to respond to local requirements and to protect the customer data. We use a crowd in China for many tasks, but are also leveraging facilities to protect customer data and respond efficiently to some use cases such as computer vision. Slide 17 now and our Enterprise division is growing at double-digit rates and continues to add new customers across a wide variety of use cases. The breadth of use cases shows how many ways AI is being deployed. The opportunity before us and the value of adding more data types and capabilities such as the acquisition of Quadrant that we announced today and we'll discuss in a few slides. Our government business on Slide 18 is ramping, but not as fast as planned due to the slower nature of government purchasing and a cautious approach to doing business in the pandemic. We're actively engaged in projects directly with agencies through contractors and with government research labs, and they have been the form to many impactful technologies over time. Overall, we're well positioned and optimistic about the government market. To Page 19 and the opportunity before us is simple. Our customers need large volumes of many different data types of high-quality training data to build an increasing variety of AI products that benefit their customers and their businesses. The more we can support them in this journey to better. Sujatha will soon join us to lead product management. She has 20 years' experience in engineering and product management in areas including search and AI. She told me the other day that AI will change the way we live and we're still in the very early stages of its adoption. She is thrilled to be joining us because she sees training data is the key challenge for anyone developing AI. Our product-led strategy aims to achieve 2 things

Kevin Levine: Thank you, Mark, and good morning, everyone. So on to Slide 26. Different dynamics in the first half of last year make comparison with the prior period challenging with respect to revenue and costs. 1H '20 revenue split was 49%, as compared to the historical split of around 44%, which is closely aligned to how the split is forecast for this year. As Mark has explained, first half revenue has been impacted by a range of factors, resulting in reduced ad-related revenue from our global customers. Outside of ad-related projects, where we derive 75% of our global services revenue, we have had strong growth in new projects and expect it to continue. Ad-related projects are expected to grow in the second half of 2021, but at a lower rate than non ad-related projects, and our new markets growth has also been strong. Cost of sales, which is comprised of payments to our crowd workers increased as a percentage of revenue from 59.4% in the comparative period to 61.6% in the current half. This was impacted by the mix of customers and projects comprising the revenue, impacted by the decrease in global services revenue and the number of early-stage new projects. Operating expenses for the first half were higher due to the fully annualized impact of growth investments in FY '20 and the investment in new markets in the first half of '21. This is represented mainly in employee expenses. The other expenses line in the P&L reduced mainly due to lower recruitment job board expenses. The overall expense increase was partly offset by a true-up adjustment of share-based payment expenses. Similar to impairment testing, share-based payments need to be assessed. Following an assessment of the probability of achieving hurdles for the 2020 long-term incentive plan, a true-up adjustment was processed in the first half of 2021. Underlying EBITDA margin of 14.1% was impacted by lower revenue and gross margin and a higher cost base. Further to that, underlying NPAT reduced 35% additionally impacted by increased amortization of product development investment. In relation to the organization restructure announced in May, a restructure charge of $2.3 million has been taken in the half. This charge reflects costs incurred in the half as well as a provision for cost to be incurred in the second half. The effective tax rate of 20.5% was down from the prior corresponding period. 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, the normalized tax rate is around 28%. On to Slide 27. We continue to focus on driving efficiency and productivity in our core expenses to facilitate continued growth investments. Core expenses as a percentage of revenue have been reducing since the second half of 2019. On Slide 28. In the first half, we invested $21.2 million in product development, representing 10.8% of revenue. This focus is important to drive customer growth and repeatability as well as quality improvement and margin expansion. Since FY '19, we have strategically invested in engineering resources to develop new products and enhance existing ones. 53% of products spend was capitalized in the first half, consistent with the FY '20 rate, reflecting our commitment to development of new products and tools. We expect product development spend and the associated capitalization rate in the second half to be in line with the first half. On to Slide 29, to talk about our amortization policy. We take a conservative approach to amortization in that we commence amortizing product development in the year in which the spend originates. The purpose of this slide is to show how we effectively apply our amortization policy. The table on the left shows how the annual amortization expense each year is comprised of the different lows of expense pertaining to the years in which the spend was capitalized. The chart on the right shows the amortization rate per annum, i.e., 33% relative to the amounts capitalized in each year. On to Slide 30 to talk about our balance sheet. Our balance sheet remains strong and resilient with no debt. Cash on hand at year-end increased by $5.5 million to $66 million through effective cash collection management. The decrease in trade receivables of $9.5 million, results from lower revenue and effective conversion of invoices to cash. Contract assets represent work completed at half year-end, pending satisfaction of customer billing milestones. Invoices have subsequently been invoiced in respect of this work and the majority of these invoices have been paid. Noncurrent 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. An interim dividend of AUD 0.045 in line with the 2020 interim dividend has been declared and is franked to 50%. On to the cash flow on Slide 31. Cash flow from operations reduced in the first half of '21 due to lower revenues and higher costs. The comparative 1H '20 cash flow from operations benefited from favorable receipt timing differences. However, cash flow conversion continues to be effective with 101% of EBITDA being converted into operating cash flow in the half. The cash balance of $66 million included a repayment of borrowings of $23.5 million in August 2020 in respect to the Figure 8 earnout payment. Cash has been effectively deployed for product development tax, dividends, operating expenses and growth investments. I'll now hand you back to Mark. Thank you.

Mark Brayan: Thanks, Kevin. Over to our outlook slide now on #32. First of all, our full year underlying EBITDA guidance will be impacted by investments in Quadrant, to the tune of $2 million, adjusting our current range of $83 million to $90 million to $81 to $88 million. On that aside, we're maintaining our guidance range, but expect to be at the lower end of the range due to the ad-related project impacts. Our order book comprised of year-to-date revenue plus orders in hand is at circa $360 million at August 2021. Now this is 10% above the order book last year of $328 million, and that's in U.S. dollars, and that was 79% of last year's full year revenue number. The forecast is supported by a stronger order book, higher confidence in the pipeline and the flagged second half skew, which is weighted to Q4 due to our customer delivery schedules for e-commerce, digital ads and search programs. Note that the order book numbers do not include any revenue from Quadrant. It's also worth noting that the H1 to H2 revenue split is in line with historic splits. 2020 excluded and gross margins are expected to improve in H2 to levels consistent with last year. On expenses, we see modest expense growth in the second half with the savings from the first half restructure flowing in '22, and we expect those to be reinvested. Finally, we expect full year underlying EBITDA margins to be in line with last year. To conclude, we have a leading position in a dynamic market with strong long-term tailwinds. Please turn to the final slide #33. We are the world's largest player in the dynamic and growing market for AI training data. Our market-leading crowd and technology combined to give us an unrivaled set of capabilities to respond to an increasing variety of use cases and opportunities. We are responding to and navigating the evolving needs of our major customers with agility and pace albeit with some near-term impact. We have confidence that they are wide-ranging investments in AI and the need for high-quality training data and our track record of delivery and strong relationships will drive future revenue and demand for us. We continue to invest in new technology and market expansion and are seeing the fruits of those investments in areas from machine learning-based productivity improvements to rapid sales growth in China. We welcome the team from Quadrant to Appen and look forward to working with them and winning in the location data market. We're pleased to be able to support our global crowd, and I'm pleased to be involved in important initiatives such as the World Economic Forum's promotion of responsible AI standards. Finally, I'd like to thank everyone at Appen for their passion, expertise and friendship. Thanks and well done. I'll now hand it back to the moderator to take questions.

Operator: [Operator Instructions]. Your first question comes from Gary Sherriff from RBC.

Garry Sherriff: Mark, Kevin, Linda, A few questions. The first 1 in relation to ad-related revenue. Can you maybe just clarify for us how much of the ad-related revenue was down in the first half of '21? I mean I look on Page 9 of your slide, it looks like it's down about 25% to 30%. I just wanted to confirm that. And secondly, what have the big tech customers said to you in relation to ad-related revenue in terms of when it might shift back to historic growth levels?

Mark Brayan: Yes. Garry. So you're correct, yes, that drop is clearly visible on Page 9. The customers -- the projects that are skewing to the second half are generally related to ad and search programs. And a big part of that reason, and this is why we see some seasonality year-on-year is retail towards the end of the year, especially in the U.S. So e-commerce ramps up, traditional retail ramps up as customers look at events like Black Friday and Christmas and the like overseas. So we see a seasonality in general. And this year, we're going to see a little bit more of that. And that's been advised by our clients from the beginning of the year.

Garry Sherriff: Okay. Understood. Investment, you flagged high levels of investment continuing. How do you keep the market confidence on those spending levels, just given the customer base typically don't give you much revenue visibility. I mean put another way, what gives you the confidence that spending more will lead to more customers and revenue?

Mark Brayan: Yes. The macro trends give us a lot of confidence, Garry. I mentioned in the presentation, the incoming executive for product management, Sujatha, she's been involved in artificial intelligence for many years, and she jumped at the chance to work with us because we're at the beginning of the AI journey in her view, and that's just from tech to across the spectrum of opportunities. And she sees data labeling is the -- or training data rather is the biggest challenge to solve to the biggest challenge to solve, sorry. And I recall the same conversation with Wilson, our CTO when I first met him, he was very unarmored with the fact that we were solving the training data problem because it's at the heart of every piece of AI, and that's going to be the case for many years to come.

Kevin Levine: Garry, the other thing as well is the investments to gear towards the new markets. And obviously, we're showing strong growth in that, and look to entrench our market position and to continue to grow the revenue there through the investment.

Garry Sherriff: Okay. And final question on quadrant. And apologies, I haven't been all through your pack yet, but I couldn't see any financials on Quadrant. Could you maybe give us a sense of what revenue they did in the last 12 months, what the cash burn was over the period? And the next question is in relation to quadrant around use cases, just to maybe facilitate understanding.

Mark Brayan: Yes. So the numbers are small, and it's an early-stage company, but it's got some really exciting technology couple of used cases, the 1 I alluded to in the presentation. So the delivery person that wants to pick up the restaurant meal, if they park their bike and dash in side to get the meal knowing exactly where to pick up that meal it could be at the back of the restaurant. It could be at the side of the restaurant, speeds up and streamlines the delivery process. The other application of location data is just knowing where people are and where they move. So if you're an advertiser and you want to put a billboard up and you want to know how many people move past the street corner versus how many people move past that street corner. So that's another area that they work in as well. So we're pretty excited about it. We see a lot of demand for it, by our customers that produce map basis, for example. And it feeds into many industries, e-commerce, supply chain and logistics, even autonomous vehicles. We've done some work in this area around the exact location of electronic vehicle charging points, for example. So as we demand more and more from our technology for many reasons, knowing where people are and where they need to go is super important.

Garry Sherriff: And does -- I mean, when I think about that geolocation data, I mean, Google and Apple already have got that information. I'm just trying to figure out how and I assume they sell some of that information to businesses already. How is it different in terms of what Quadrant are providing? Like is that level of geolocation more granular or something? What's the difference?

Mark Brayan: Yes, that's precisely. It's more granular. So in automate base, you can get the address of a particular business. So just say you're a car dealership. You get the address of the car dealership. But the more granular data might be always the driveway for returns -- or sorry, for maintenance with the -- where new sales made versus used car sales. I think also about internal location data, so in shopping malls and the like. That doesn't appear by and large, on current map basis. So we're getting strong demand from our largest customers for this sort of data.

Garry Sherriff: Okay. Yes, that makes sense. And last 1 for me, and sorry to take up so much time. But the integration of Quadrant, how are you thinking about that into existing platforms? Or will it be stand-alone?

Mark Brayan: So it will be stand-alone in the near term. The integration is a pretty light touch initially, we get our sales teams working together so we can get them inside of our customer base, and we invite or they rather invite members of our crowd into their system as and when required. Over time, we'll look for tighter integration, but the beauty of it is that it will work out is with a very light integration right from the start.

Operator: Your next question comes from Lucy Huang from Bank of America.

Lucy Huang: Mark, Kevin, Linda. I just have three. So firstly, in terms of gross margin, so how should we be thinking about gross margin in the medium term, particularly as new services becomes a bigger contributor to revenue versus ad revenue. So do we think that gross margins will, I guess, tighten? Or is there scope for kind of expansion over time? And then secondly, you mentioned that you've launched 34 new customers in the new services business. Just wondering if you can give us some color around the average contract size of these contracts? Are they relatively had they been growing in size more recently? And then thirdly, you mentioned that there's about 31% of committed revenues in Global Products. So just wondering, what are these commitments like are they annual commitment for multiyear commitments? Just some color would be great.

Mark Brayan: Yes. Thanks, Lucy. I hope I remember all of those. I'll start with the last 1 first, typically annual contracts and typically with an automatic renew. To the point on gross margins, we point out in the outlook slide that the gross margins are expected to improve in the second half, consistent with FY '20. Going forward, gross margins depend upon a couple of things. They depend upon the extent to which we can deploy technology to enhance the work of the crowd worker. It can also sometimes depend upon the nature of the project and the mix of locations, for example. Some locations yield higher gross margins than other -- others. So there's a variety of factors. Overall, our strategy is to get gross margin expansion by using technology to enhance the crowd worker. And the second question was new customers. Sorry. Yes. So look, new customers typically start off small. There can be tens of thousands or hundreds of thousands. And that's the nature of the development of AI, it's somewhat experimental in its nature. So a customer might have a concept for a product. They come to us, they collect some data. They build a model, they see how the model performs. And then they may keep collecting the same sort of data or they may collect additional data or they may collect different data altogether. But until that product starts to deliver the performance they expect, the projects tend to stay relatively small in the tens or hundreds of thousands before they grow beyond that into the millions.

Operator: Your next question comes from Quinn Pierson from Credit Suisse.

Quinn Pierson: I guess just firstly, with regards to what is a pretty substantial second half profit SKU. There are some bridging items on the outlook slide, which is quite helpful. But I guess the year seems to be setting up quite similarly to last year, which resulted in a fourth quarter downgrade. And so I guess my question is just kind of in simplistic terms, I guess, how do we get more comfort that, I guess, the second half bridging items come to fruition? And I guess what's different this year than last year?

Mark Brayan: Yes. Thanks, Quinn. There's a few points most importantly is the strength of the order book. So the order book is stronger this year than last year in terms of the quality of that order book, the orders that we have in it, for example, -- But also there's strength in the pipeline, which is the gap from the order book to the full year number. We have -- our deals are in certain stages, if you will. And we have more late-stage deals in that pipeline this year versus last year. So those 2 things are super important. The strength of the underlying order book and the gap to the full year number is much more late stage in its development. The second thing that's important is the split from the first half to the second half is very consistent with prior years. So 2020 aside, it's very consistent with the years prior to that. And then the third thing is the conversations we're having with the customer. Clearly, last year, we were a bit surprised by some movements late in the year from the customer. So we've been very close to the customer throughout this year, and we're tracking the work that we're doing with them very closely, and we're monitoring demand on a very, very granular level to make sure that we don't bump into the same problems as we did last year. So overall, we have strong confidence in the pipeline. We have strong confidence in the order book. We're very close to the customers in this regard. And the things that customers tell us are very consistent with the way the year has played out to date. So very mindful of last year's experiences, but there's a number of factors that go into our confidence for this year.

Quinn Pierson: That's very helpful color. I guess, secondly, with regards to the cost out. I guess the $50 million of cost out more kind of, I guess, on the services side. I guess, does that mean fully action? So are we now at that run rate? And then can you talk us through the deployment of that more into the product side. And I'm just, I guess, related to that, I'm just wondering if there's a little bit of kind of mismatch that work here in the second half, some of that will maybe be banks from a profit perspective?

Mark Brayan: So the bulk of that will be actioned next year or will come to fruition next year, and the bulk of that will be reinvested into the business most probably into product development. The technology base that we're building is super important for the growth of the business in order to, as explain to Lucy's question, automate many of the functions that we have internally and with our crowd to expand our gross margins. So all of that -- not all of that, sorry, the bulk of that benefit will flow through next year and the bulk of it will be reinvested into product.

Quinn Pierson: Okay. So just to clarify what I heard. So the bulk of the actual realizing of the cost out will be the next year as well?

Mark Brayan: Yes.

Quinn Pierson: Yes. Okay. And then just lastly, so with regards to some of your new markets, to me, it seems like the quality of the platform itself is kind of key to the winning and gaining share. I guess, can you talk us through how you feel your current tech platform and tech capabilities compared to keep you. Cognizant 1 angle is that you have, I think, a competitive advantage by an to access high-quality crowd. But just particularly on the technology side of things because how do you think you compare to peers? And what, if any case there to fill?

Mark Brayan: Yes. We run a fairly regularly updated matrix of features and functions across our competitors to the extent that we can find information about them to public sources. And our view is that we compare very well with all of our competitors. Some of them have particular strengths in particular areas. Typically, they start off in an area such as computer vision, and they build strong capabilities in those areas, where we have the advantages that we can cover multiple areas, and we're adding to those areas such as the addition of Quadrant. And our ability to go across such a broad variety of data types and use cases is extremely important because the use cases are expanding, as we explained in the presentation, and there are very few, if any, opportunities that we have to walk away from compared to -- certainly, our view of our competitors is they tend to be focused on a particular area and a particular niche. So we feel pretty good about our technology, and you're absolutely correct that our crowd capabilities are pretty extensive as well. So -- from our perspective, we have a really good set of capabilities, the combination of technology and crowd to tackle many, if not all, use cases that we're seeing.

Operator: Your next question comes from Josh Kanakis from Baron Joy.

Unidentified Analyst: Just firstly, on the new product and investment. Could you give us a bit of an idea of how you're thinking about that level of investment as a percentage of sales moving forward, please?

Mark Brayan: Josh, we call out 10.8% of revenue in the first half, and that's been edging up, which I think is visible on 1 of the finance slides 28. So you've seen that pick up as a percentage of revenue over time. I expect that we'd continue to invest into product. We haven't disclosed the exact demand over time, but product investment is super important.

Kevin Levine: Yes. I mean, obviously, with the introduction of a new -- product, there'll be a lot of new initiatives. And so obviously, a lot of direction that we will work with her on into the future.

Unidentified Analyst: Okay. Great. And just further into that, I guess, it looks when you look at the new products and good granularity around I guess, getting further up the value chain in terms of that relationship on the build of the algorithms as well. When you compare it to peers, say, for example, like scale AI, what do you see as sort of some of the road map of new products or services that you see selling to your customer base over the next sort of 2 to 3 years?

Mark Brayan: Yes. As Kevin says, Sujatha is going to have a big influence over where we head in that direction. And as we identify in the deck, there's a big opportunity beyond the collection and labeling of data into all other facets of helping people build AI. So that road map is still under development, Josh, but there's plenty of directions that we can go.

Unidentified Analyst: Right. And just obviously, you mentioned a bit of detail around the acquisition of Quadrant. If we look at other adjacencies and how you're thinking about the sort of M&A strategy, is that a fair assumption that you're also looking at things upstream in terms of the value and services around the algorithms themselves? Or is it more so around the data provision?

Mark Brayan: In the near term, it's more around the data provision. We see that as a very very valuable and very doable thing for us. Heading up stack into the world of models and other things is something that is going to be firmly on Sujatha's desk once you start because there's a lot of exciting things in that space. There's a lot of early things in that space. We think our most exploitable near-term opportunities are around data sources. So that's our focus for now. And we'll tackle up SAC areas as Sujatha comes on board and get a feel for things.

Unidentified Analyst: Great. And just final one, just on China, just the lazy 5.8x growth on the period. And I guess we're keen to understand a little bit about what you're seeing from the end customer trends expansion within the existing customers, just maybe a little bit more color on the growth opportunity there.

Mark Brayan: Yes. It mirrors what we've seen in the U.S. in terms of the trends in demand for data. We get into a customer with a sort of an anchor project and it grows from there, and then we start growing across the customer into different data types and different modalities. One thing we've been very careful to do in China is to add a lot of customers outside of our -- outside of the tech giants. So we've got a really good foundation in autonomous vehicles, which is very exciting. We're also pleased that we're winning not just -- I think we talked about this in prior periods. Clearly, we bring a strength in our international capabilities, but we're winning, winning a lot of local language work as well. So the summary is it's not dissimilar to the U.S. patent of sort of land and expand, if you will, but we're also making sure that we win plenty of new customers to grow our customer base.

Operator: Your next question comes from Michael Aspinall from Jefferies.

Michael Aspinall: Yes. It's Mark, Kevin and Linda. You've touched on it a couple of times, but I don't think I quite understood just on the data collection I would have thought about that. I would have thought lower growth in global growth and higher growth in market had a positive market. So I'm going to have to either ask either you or -- to repeat the question.

Unidentified Analyst: Yes, I'll go again. I would have thought that lower growth in Global Services and higher growth in new markets would have had a positive mix effect on gross margin. But that's not coming through. Can you just talk to that a little bit more. And I don't think I quite understood what you've mentioned before.

Mark Brayan: Yes. No, sorry. Thank you. So the -- some of the global services projects have been going for some time and have very good gross margins. Many of the new projects are in startup mode and have lower gross margins. So the projects in general tend to improve -- or sorry, the gross margins of the projects tend to improve over time. As we get more practiced in doing what the customer is after and deploy more technology to help them, et cetera. So your intuition is correct in 1 sense in that product-based stuff is going to have higher margins. But there's the timing elements of the projects that means newer projects have lower margins and more established ones have higher margins.

Michael Aspinall: Okay. No, that makes -- And I mean, following on from that, on Slide 10, you show revenue from projects starting before 2021 and the revenue split. Are those newer projects structurally smaller than those started to prior 2021? Or could the average size grow to that of what you see in the kind of the older project bucket? I think it's about $800,000 versus $200,000 to.

Mark Brayan: Yes, yes. It's -- they all -- in general, yes. The only thing I would call out is we have a handful of extremely large projects. So we have a set of very large projects, and it's not all projects are going to get to that very large stage. So it's not unusual for projects to start in the tens of thousands, get to the hundreds of thousands, get to the millions. Getting them to the 10, 20 and above million range is probably more the exception than the rule, but it's very easy to get them into the millions.

Michael Aspinall: Okay. Yes. That's very useful. And year-to-date revenue and orders in hand plus 10% of, which compares to the first half minus 7%. That implies kind of 20% revenue growth in the second half. If I just put kind of the pipeline and the order book as side mean -- Have you seen that in the first 2 months of the second half?

Mark Brayan: So our confidence in the second half is very solid. As explained earlier, the order book is better than last year, the pipeline, which is the gap between the order book and the full year number is more advanced than last year. So our confidence is high. We are very aware of last year's experience. So we've spent a lot of time with customers, a lot of time monitoring projects, making sure that we don't run into the same issue as we did last year.

Michael Aspinall: Yes. And I mean, just kind of on what happened so far. Are you able to comment on whether you've seen those improving trends in July and August?

Mark Brayan: Other than what I've said, Michael no.

Michael Aspinall: Okay. And then that revenue growth that we're expecting in 2H, 2021, should we expect that to flow through in the first half of next year? Or is that larger to H2 just going to be kind of something that exists from here on out?

Mark Brayan: The trend into the second half of this year is due to a very firm second half skew that our customers called out earlier in the year. Whether that will repeat itself next year is too early to tell. But it's based on the advice from our customers and the projects that they had ongoing and the work that they needed to do on new projects, they wanted to have a heavy skew to the second half in 2021.

Operator: Your next question comes from Siraj Ahmed from Citi.

Siraj Ahmed: Mark and Kevin. I just have four questions. The first one on the work in hand, right, you referred to the last year conversion ratio. But is that the right number to look at? Because given last year does not have a fourth quarter skew in this year, you do have it, shouldn't we be going back to FY '19 and before, which is around 70%. Just can -- match?

Mark Brayan: Yes, Siraj. So we specifically call out and help guys in terms of that reference point to last year because can be a bit confusing. But remember, though, that what we're talking about here is annual numbers, right? So it's kind of very independent of the SKUs between H1 and H2. So hence, the reference to FY '20 there.

Siraj Ahmed: Got it. Second thing on ACV, the committed revenue, that's actually declined from the February level that you disclosed. Can you to understand what's happened there, given that's an key focus?

Mark Brayan: Yes. So there's -- as explained in an earlier question, there are annual contracts and there are automatic renews on those contracts, but not all contracts renewed. There's a churn rate in ACV that every business has to greater or less degree. So yes, your observation is correct, and it's due to not all projects renewing in the period.

Siraj Ahmed: Mark, would that be the major customers or the newer smaller customers?

Mark Brayan: It's a variety of things.

Siraj Ahmed: Third thing, it's maybe a bit early. Given you're reinvesting of savings, which makes sense, how should we think about FY '22 EBITDA margin is sort of indicating that it should be in line with this year. Is that how we should think about it?

Mark Brayan: Yes. Siraj, we're still obviously working through all our planning and initiatives together with our investment and how that's deployed together with obviously, new product initiatives. So I think we'll come out with further guidance into the full year. Yes, obviously, it's going to depend on basically that the levels of reinvestment in the areas that they deploy to and then the revenues that we expect to derive in how much in '22 and how much of that's building revenues beyond that.

Kevin Levine: I think also, Siraj, -- we've been through a couple of Rocky halves, second half last year, first half this year. Our confidence around the second half of this year is very high. And once we get into the second half and towards the end of the second half, we'll have a better view on how things are going to go next year.

Siraj Ahmed: Understood. Just last one, just on the acquisition. Am I right in this not being really an AI data play. It's more of data, but not AI data?

Mark Brayan: It's definitely data, and that data will definitely go into AI in various ways and forms, but it could also be deployed in other ways. So for example, some of the algorithms that drive supply chains. They're not AI algorithms. They are different sort of algorithms, but they also require vast amounts of data. Having said that, search algorithms, for example, that could also rely on location-based data use AI models. So it's a bit of both. But it's definitely a valuable source of data. It's very hard to collect source of data, and it's a very reusable source of data. So whilst our overarching mission is to deliver training data for AI, if we've got data that can be used for other technology purposes, we're happy to be participating in that as well.

Operator: Your next question comes from Bob Chen from JPMorgan.

Bob Chen: A few questions from me. You've obviously called out sort of a second half skew as well as sort of the fourth quarter skew. Can you talk a little bit about that sort of fourth quarter skew and how that compares to sort of your historical period?

Mark Brayan: So other than the reference to the first half, second half skew that I talked about, that is that the skew this year is comparable to prior years before 2020. We always have a degree of the SKU into the fourth quarter, and a lot of that's driven by the U.S. retail market. Online advertising ramps up, into the fourth quarter searches ramp up into the fourth quarter. E-commerce activity and regular retail activity ramps up into the fourth quarter, and that drives a lot of the work that we do. So the skew from a half-on-half basis is comparable to pre 20 years and the fourth quarter -- pardon me has been a feature of the business for some time.

Bob Chen: Okay. Sure. And then just referencing Slide 9 in the pack, obviously, you called out the decrease in advertising-related revenues there. And then you've also mentioned that you expect a bit of growth coming through in the second half. I mean do you expect that advertising revenue stream to ever get back to for the historical level?

Mark Brayan: So the background to what's illustrated on Slide 9 is if you cast your minds back to the beginning of the pandemic. And we pointed out that online ad volumes have taken a hit. It was a perhaps a realization for many companies in the ad -- in the online ad world, but their hyper reliance on that platform was something they needed to address. And there were other factors as well, privacy regulatory scrutiny, et cetera. So from that point onwards, many of the companies in the ad world started investing very heavily in in other projects. They're already doing some non-ad development prior to that, but it ramped up quite considerably. And that had a knock-on effect to our business, which is very visible in the slide on Page 9. So having said all of that, this is not sort of a switch from ad revenue to other revenue. It's the addition of other product revenue alongside, the ad revenue, which is -- continues to grow strongly for our customers. So we anticipate that ads will be a feature of our business and part of our revenue for some time. It's likely that the nature of the projects will change because the underlying solutions will change. Their solutions are going to be reliant on different types of data. There are going to be solutions that are more cognizant of data privacy, et cetera. But we do expect that those solutions will be data based and will be machine learning-based and they'll require training data. So all of that Bob is to say that there's some sort of underlying things that go into what's on Page 9, but the reliance that our customers have on advertising revenue makes it extremely likely that, that revenue will come back, and that's what our customers are telling us. And the extent and nature of that comeback is still to be seen.

Bob Chen: Okay, sure. And I think you also called out in the past that opportunities that government has been a little bit slower than expected. Can you talk a little bit about how big that opportunity is and how that would compare to what you were previously thinking.

Mark Brayan: So we don't see any change in the size of the opportunity, and it's been called out in prior packs. It's just the speed with which that is developing is what we're calling out at the moment. We've got a bunch of projects ongoing inside that market, and some of them are very interesting and in some areas that that present substantial scale. It's just not moving as quickly as the commercial side of our business. So we're just calling that out.

Operator: Your next question comes from Paul Mason from E&P.

Paul Mason: Just three from me. So the first one, I was just wondering if you could talk about Slide 21, a bit more of the ML powered automation project. Are these in commercial production like for client use at the moment? And if so, are they sort of doing anything on your gross margin performance? Or are they still sort of in the R&D phase?

Mark Brayan: So hey, Paul, some of them are in being used in commercial projects. And they are going towards the efficiency of those projects. But with any new technology, we kind of start small and grow from there. So not material numbers at this point. The two down the bottom are being used across a number of projects and they go to our internal efficiency. For example, the fraud detection, we get a lot of people applying for work for crowd work under multiple names, sometimes hundreds of names that they generate automatically. So we're now able to find that extraordinarily quickly, and that benefits in 2 ways, what benefits us and the customer in 2 ways. One, it makes us more efficient. But two, the quality of the work for the customer is far higher. So the short answer is, we are using some of these in production, but it's early days and entry-level projects at this point. So no material impact to gross margins.

Paul Mason: Okay. Great. Now the second one, I just wanted to sort of sanity check my interpretation of your guidance on revenue. I know you haven't provided these numbers, but -- But if you can just point out if I've made a floor on my logic. So you're calling out similar EBITDA margins to FY '20 and the low end of your guidance is $81 million EBITDA. And so if I use 17.1%, that's about USD 475 million revenue. And then in terms of your guidance around the global services revenue, you're still pointing to sort of mid- to high single digits. So values like 7%, that's about $350 million. So if I'm sort of thinking that it's 350 global services and about 125 for new markets. Like is there anything wrong with my logic there?

Mark Brayan: Paul, I'll say the 1 thing, though, is when you're taking the $81 million, you're taking the effective quadrant there. And essentially, we haven't factored in Quadrant into any of the numbers that we've talked about in terms of the revenue outlook, I suggest when you're doing that work, work on that original guidance range which has not been reduced by the provision, the call out for quadrant. So I think that's probably the main thing to talk about. But I think essentially, if we think about the -- I guess the clues or the guidance element that we provided here. Essentially, if we break it down, we're basically saying, look, the order book is up 10% on the prior year. So if that's a proxy for full year apply that percentage to last year's revenue, right? And then the other guidance point, which is around the EBITDA margins in line with last year. And if you do that, then you'll get to numbers that supporting where we're coming out with the guidance, which is at the lower end of the range, this excluding the Quadrant business.

Paul Mason: Okay. Great. And just the last 1 for me. Just on the revenue plus work in hand number. So I'm going to translating in sort of the February numbers that you used to provide in Aussie dollars to U.S. But it looks like the sort of the actual dollar gap in February was about 45%. And in May, at the AGM, it was down to 20% and now it's up to 30 again. Is that sort of reflective -- assuming I've got the February numbers accurate of how your sort of revenue and contracting accumulation has gone and it sort of dipped a bit in sort of March, April, and now it's sort of ramped up again in terms of your order book?

Mark Brayan: I'm not 100% sure of the numbers you're quoting, I don't have everything in front of me, but I think that the order book reflects the business in a sense and has skew from the first half to the second half, as we've explained. So that could explain your conclusions there.

Operator: Your next question comes from Ross Barrows from Wilsons.

Ross Barrows: Just two super quick ones, both on Quadrant, it's been explored quite a bit already. Just in terms of team size, it looks like it's in the mid-20s. But any color you can give around that?

Mark Brayan: Of that order, Ross, yes. It's a small business.

Ross Barrows: Yes. And then just lastly, the earnout where it does mention it's got '22 and '23 revenue milestones. Just as being particular around that will that be paid to the end of '23 once floor achieved? Or is it kind of half after '22 and half after '23?

Mark Brayan: It's spread across both.

Kevin Levine: Yes, Ross, just to clarify on that. So there's measurement periods and then the shares will be issued around the time of those measurements based obviously on the share price around that time.

Operator: Thank you. Your next question comes from Conor O'Prey from Canaccord Genuity.

Conor O’Prey: Maybe just a quick question for Kevin on share-based payments. I apologize if I missed anything you said there, Kevin, just they were to see a contribute even in the first half, but they're going to revert to sort of more like minus 5%, minus 6% in the second half, like that sort of would have been in the half of FY '20?

Kevin Levine: Sorry, Conor, can you just repeat those numbers again in terms of the comparative metrics and then I'll be able to respond?

Conor O’Prey: Yes. So I think there were on a net contributor to EBITDA in the first half. Last year, I think it was minus 10% for the full year. Will they revert to an expense? Or will they continue to contribute in the second half?

Kevin Levine: No, no, it will be an expense in the second half. So essentially, there's that trip adjustment is a point in time in terms of expense up to that point in time, we definitely expect that will be an expense in H2.

Conor O’Prey: Of a similar magnitude to previous?

Kevin Levine: Yes. Yes, and yes, around those levels. Obviously, with the exclusion of this particular plan that we -- that obviously we've adjusted for.

Operator: Your next question comes from Siraj Ahmed from Citi.

Siraj Ahmed: Mark, a quick follow-up. I mean, I know we're not talking about better-than-expected revenue for the second half. But in previous years, you've had a fourth quarter surge is better than expected. Now given you have more confidence in the pipeline, should we be thinking that there may not be a surge if there is 1 that you actually have more work being expected in the year?

Mark Brayan: So that would be a happy problem. At this stage, we've got a lot of confidence in the numbers that we're calling out, and there's a lot of things to support it, including the strong order book and the strong pipeline. As we've seen historically, sometimes the demand goes beyond our expectations. But at this stage, we're calling it the way we are.

Kevin Levine: Yes. And the other thing, obviously, it's reflective of demand volumes that we've been told about, as Mark talked about, in terms of the later stage quality within the pipeline Essentially, what we're saying is this, it's largely based around known demands from what we're seeing right now. So obviously, if there's any change to that up or down, well, obviously, that has to be factored in. But if there is if there is change to Q4 in terms of significantly higher than what we've been told right now within the facility movement there and similarly the other way.

Mark Brayan: And just to remind you, Siraj, the delivery requirements tend to be around the -- or our ability to deliver, sorry, tends to be around the crowd. And the crowd can flex up and down pretty quickly.

Operator: There are no further questions at this time. I'll now hand back to Mr. Brayan for closing remarks.

Mark Brayan: Yes. Thank you very much, and thank you, everybody for attending, including kids and pets. Pleasure to hear everybody and glad to hear that everybody's safe from in the amidst the pandemic. So again, just to reiterate the sort of the closing remarks. We're very pleased to be the largest player in what is a dynamic and growing market of AI training data. Our leading crowd and technology combined to give us a tremendous set of unrivaled capabilities that enable us to respond to an increasing variety of use cases and opportunities. Thank you to everybody at Appen. Thank you to Kevin and Linda for their work in preparing the presentation and the numbers today, and thanks to everybody for attending and asking questions. That's it for now. Thank you. Speak to you all soon.

Operator: That does conclude our conference for today. Thank you for participating. You may now disconnect.