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 Bryan, Chief Executive. I'm joined today by our CFO, Kevin Levine and our Head of IR, Linda Caroll.
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 $110,000,000,000 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, etcetera. 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 curated 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 growing need for more AI development tools and services, such such as data audit, data management, model testing and life cycle management. Our growth rate reflects the market. We've grown revenue at 0.38% 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 to the opportunity before us. We invested 10.8 percent of revenue in product development in the first half of this year. Welcome to Jafar Sagaraju 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 Product led business announced in May this year is well underway. We now cover more data types and our language based origins, text, speech, image, video, three-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 SKU in project delivery to the and half.
Group revenue of $196,600,000 was down 2% on the first half of last year due to lower global revenue as a result of our major customers prioritizing new non advertising 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-nineteen impact. In contrast, new markets revenue of $47,800,000 was up 31.5 driven by China, new enterprise customer wins and product led growth including many new projects for on our platform, reflecting their investments in non advertising 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 $68,000,000 in cash and no debt as of the 30th 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 and 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 and crowd underpin the strength and scalability of our business. We're able to respond to all data types 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 $148,800,000 was down 9.2% on last year. This revenue derived from the work we do on our customers' platforms and typically with 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 concerns. Their investments and includes many new use 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 is relevance.
Our platform covers all data types and many use 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 and 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 privacy concerns. Our large customers rely on ad based revenue. We expect revenue from ad related projects to grow in the In the first half of twenty twenty one, we derived $20,300,000 from 100 projects that commenced this half. The balance Our global revenue, dollars 150,800,000 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 ads applications, showing that our ad based customers are investing in new areas.
We do
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 and e commerce. Slide 12 now and our push into new markets is going well. New markets capture the success of our product led and customer expansion and includes product based revenue from our global customers along with revenue from our enterprise China and government divisions. New markets grew strong this half as illustrated on Slide 13, up 31.5% on the first half last year.
Growth was driven by a combination of factors, 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 and government divisions. Both are growing well at 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 byproduct. To slide 15 now and two 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 It's progressing extremely well, maintained its very high growth rate of 60% quarter on quarter. Growth is coming from China's tech giants, 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 to local requirements and to protect 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 It is growing at double digit rates and continues to add new customers across a wide variety of use cases. The breadth of use case that shows how many ways AI is being deployed. The opportunity before us and the value of adding more data types and capabilities such as of Quadrant that we announced today and will 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 font of 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 to build an increasing variety of AI products that benefit their customers and their businesses.
The more we can support and this journey, the better. Tijartha Sageraju 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's thrilled to be joining us because she sees training data as the key challenge for anyone developing AI.
Our product led strategy aims to achieve We're using our products to digitize and improve the productivity of our internal and cloud operations, and we're developing products to add and these combined to enable us to deliver more high quality training data to our customers to help them achieve their AI objectives. We're investing in this strategy with 10.8 percent of revenue invested in product development this half, up from prior periods. Our product suite on Page Page 20 includes Appen Connect, which is our crowd management platform that enables us to operate at scale our annotation platform that provides the tools workers use and our customer interface and a number of new products Appen Intelligence, a suite of machine learning models that pre label data and automates internal functions, in platform audit that analyzes training data sets for quality and bias and Appen Mobile that provides greater utility to our crowd workers and enables a growing set of data collection projects. Our own use of machine learning is fundamental to our scalability and growth. Slide 21 shows several applications of our over 20 machine learning models.
The first four examples of the through project speed and quality. Slide 22, in further support of our product led direction expansion of our training data capabilities. Today, we announced the acquisition of Quadrant, a leading provider of high quality location data. Location data is many applications, including in e commerce, supply chain and delivery, mapping and marketing and advertising. For example, the rapid rise of home delivery services means that delivery companies need more granular location data, not just the address of the restaurant, for example, but exactly where the pickup point is in order to streamline the pickup and delivery process.
Over to Slide 23. Quadrant is a crowd based business like Appen and the combination Their innovative technology in our global crowd enables us to collect and provide high volumes of granular location data in almost any around the world. We're very excited by the combination of Quadrant and Appen and the opportunities in location data. As a global and responsible company, we have the opportunity to contribute beyond our core business. Slide 24 highlights our work with the World Economic Forum on Responsible AI, an initiative that is setting standards to ensure that AI for the benefit of all.
It also shows our approaches to reduce emissions and the risk of modern slavery. Further And over the page to slide 25, we're supporting our crowd workers in a variety of ways, including providing work and income to many that don't have opportunities to earn. Our partnerships with diverse communities provide income and opportunities around the globe. I'll now hand it over to take you through the financials in more detail.
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 'twenty 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 that Ad related projects are expected to grow in the second half of twenty twenty one, 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 a 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 growth investments in FY 2020 and the investments in new markets in the first half of twenty twenty one. This is represented mainly in employee expenses. The other expenses line in the P and 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 for the 2020 long term incentive plan. A true up adjustment was processed in the first half of twenty twenty one. And a higher cost base. Further to that, underlying NPAT reduced 35%, announced in May. A restructure charge of $2,300,000 has been taken in the half.
This charge reflects costs incurred in the half as well as the provision for costs 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 twenty nineteen. On Slide 28. In the first half, we invested $21,200,000 in product development, representing 10.8 percent of revenue. This focus is important to drive customer growth and repeatability as well as quality improvements and margin expansion. Since FY 2019, we have strategically invested in engineering resources to develop new products and enhance existing ones.
53% of product spend was capitalized First half consistent with the FY 2020 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 layers 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 3 to talk about our balance sheet. Our balance sheet of cash collection management. The decrease in trade receivables of $9,500,000 results from lower revenue and effective conversion of invoices to cash. Contract assets represent work completed half year end, pending satisfaction of customer billing Invoices have subsequently been invoiced in respect of this work and the majority of these invoices have been made. 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 current value of An interim dividend of AUD0.045 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 twenty twenty one due to lower revenues and higher costs. The comparative 1H 2020 cash flow from operations benefited from favorable receipt timing differences. However, cash conversion continues to be effective with 101% of EBITDA being converted into operating cash flow in the The cash balance of $66,000,000 included a repayment of borrowings of 23 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.
Thanks, Kevin. Over to our outlook right now on number 32.
First of all,
our full year underlying EBITDA guidance will by investments in Quadrant to the tune of $2,000,000 adjusting our current range of $83,000,000 to 90 to $81,000,000 to $88,000,000 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 $360,000,000 at August 2021. Now this is 10% above the order book last year of $328,000,000 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 SKU, which is weighted to Q4 due to our customer delivery schedules for e commerce, digital ads and 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 The new 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 of twenty twenty one with and the savings from the first half restructure flowing in 'twenty two, and we expect those to be reinvested. Finally, we expect full year underlying EBITDA margins to be line with last year.
To conclude, we have a leading position in a dynamic market with strong long and tailwinds. Please turn to the final slide, number 33. We are the world's largest player in the dynamic 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 their wide ranging investments in AI and their need for high quality training data and our track record of delivering 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 are pleased to be involved in important initiatives such 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.
Your first question comes from Gary Cheriff from RBC. Please go ahead.
Good morning, Mark, Kevin, Linda. A few questions. The first one 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 twenty twenty one. I mean, I look on Page 9 of your slide.
It looks like it's Down about 25% to 30%. Just wanted to confirm that. And secondly, what have the big tech And I said to you in relation to ad related revenue, in terms of when it might shift back to historic growth levels?
Yes. Hey, Gary. So you're correct. Yes, that drop is clearly visible on Page 9. The customers that 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 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.
Okay, understood. Investment, flagged high levels of investment continuing. How do you give the market confidence on those spending levels, just given the customer base typically 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?
Yes. The macro trends give us a lot of confidence, Gary. I mentioned
in the
presentation the Incoming Executive for Product Management, Sujatha Sakharaju. 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 as the or training data rather as the biggest challenge It was a big challenge to solve, sorry. And I recall the same conversation with Wilson, our CTO, When I first met Ian, he was very enamored with the fact that we were solving the training data problem because it's at the heart of every piece of AI That's going to be the case for many years to come. Gary, the other thing
as well is the investments are geared towards the new markets and We're showing strong growth in that and look to entrench our market position and to continue to grow 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 on what revenue they did in the last 12 months, what their cash burn was over the period? And the next Questions in relation to Quadrant around use cases just to maybe facilitate understanding?
Yes. So the numbers are small And it's an early stage company, but it's got some really exciting technology. Couple of use cases, the one 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 inside 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.
If you're an advertiser and you want to put a billboard up and you want to know how many people move past this street corner versus how many people move past that street 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 on autonomous vehicles. We've done some work in this area around the exact location of electronic vehicle charging points, for example. As we demand more and more from our technology for many reasons, knowing where people are and where they need to go is super
Gordon. And does I mean, when
I think about that geolocation data, I mean, Google and Appen 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 In terms of what Quadrant are providing, like is that level of geolocation more granular or something? What's the difference?
Yes, that's precisely it. It's more granular. So on a map 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 With the driveway for returns sorry, for maintenance, with the We're in new sales made versus used car sales. 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.
Okay. Yes, that makes sense. And last one for me, and sorry to take up so much time, but the integration of How are you thinking about that into existing platforms or will it be standalone?
So it will be standalone in the near term. The integration is a pretty I touched 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 as is with a very light integration right from the start.
Your next question comes from Lucy Huang from Bank of America. Please go ahead.
Hi, Mark, Kevin and Linda, thanks for taking questions. So I just have 3. So first, 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 to revenue versus ad revenue. So do we think that gross margins will, I guess, tighten? Or is there scope kind of expansion over time.
And then secondly, you mentioned that you've won 34 new customers in the new services business. Just wondering if you could give us some color around the average contract sizes of these contracts. Are they relatively
Yes.
Have they been growing in size more recently? And then thirdly, you mentioned that there's about 31% of committed revenues in Global Product. So just wondering, what are these commitments like? Are they annual commitments or multiyear commitments? Just some color would be great.
Thank you.
Yes. Thanks, Lucy. I hope I remember all of those. I'll start with the last one for 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 2020.
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 The project and the mix of locations, for example. Some locations yield higher gross margins and 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? The New customers.
New customers,
sorry. Yes, so look, new customers typically start off small. They can be tens of 1,000 or 100 of 1,000. 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.
Great. Thank you.
Thank you. Your next question comes from Quinn Pearson from Credit Suisse. Please go ahead.
Hi, good morning. Thanks I guess just firstly, with regards to what's a pretty substantial second half profit skew. There's 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 4th 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 Bridging items come to fruition and I guess what's different this year than last year?
Thanks. Yes. Thanks, 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 the 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 two things are super important. The strength to 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 is very consistent with prior years.
So 2020 aside, it's very consistent 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 and 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 So very mindful of last year's experiences, but there's a number of factors that go into our confidence for this year.
That's very helpful color. Thank you. I guess secondly with regards to the cost out, so I guess the $15,000,000 of cost out more kind of I guess on the services side, guess, does that mean it's 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 Related to that, I'm just
wondering if there's a little bit
of kind of mismatch that will occur in the second half such that some of that will maybe be backed from a profit perspective? Thanks.
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 explained 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.
Okay. So just to clarify what I heard. So the bulk of the actual realizing of the cost out will be in the next year as well?
Yes. Yes.
Okay. Thank you. And then and 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 winning and Winning and gaining share. I guess, can you talk us through how you feel your current tech platform and tech capabilities compare to key peers? I'm cognizant one angle is that you have a, I think a competitive advantage by being able to access a high quality crowd.
But just particularly on the technology side How do you think you compare to peers? And what, if any, case are there to fill? Thanks. 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 in public 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 Where we have the advantage is 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 It 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 our certainly our view of our competitors is they tend to be focused on So we feel pretty good about our technology and you're absolutely correct that our crowd capabilities are pretty So from our perspective, we have a really good set of capabilities, the combination of technology and crowd to tackle for many, if not all use cases that we're seeing.
Helpful. Thank you for your time.
Thanks, Quinn.
Thank you. Your next question comes from Josh Kanarkis from Barrene Joey. Please go ahead.
Hi, Mark and Kevin. Thanks for taking my question. 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.
Josh, We call out 10.8 percent of revenue in the first half and that's been edging up, which I We'd continue to invest into product. We haven't disclosed the exact amount over time, but product investment is super important.
Yes. I mean, With the introduction of a new SPP product, there will be a lot of new initiatives and so obviously a lot of direction that we will work with her on into the future.
Okay, great. And just further into that, I guess, it looks when you look at the new products, some 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.
Yes. As Kevin said, Sujata is going 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 roadmap is still under development, Josh, there's plenty of directions that we can go.
Great. And just obviously, you've mentioned a bit of detail around the acquisition quadrant. If we look at other adjacencies and how you're thinking about the sort of M and A strategy, is that a fair assumption that you're also looking at things up In terms of the value and services around the algorithms themselves? Or is it more so around the data provision? Thanks.
In the near term, it's more around the data provision. We see that as a 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 is a lot of exciting things in that space. There is a lot of early things in that space. We think our most exploitable near term opportunities are around data So that's our focus for now and we'll tackle up stack areas as Sujatha comes on
And just final one, just on China, just the lazy 5.8 times growth on the period. And I I guess we're keen to understand a little bit about what you're seeing from the end customer trends, the expansion within the existing customers, just maybe a little bit more color on the growth opportunity there.
Yes, it mirrors what we've seen in the U. S. In terms of the trends and 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 One thing we've been very careful to do in China is to It's 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 and I think we talked about this in prior periods. Clearly, we bring a strength in our of international capabilities, but we're winning a lot of local language work as well. So the summary It's not dissimilar to the U. S. Pattern 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
Your next question comes from Michael Aspinall from Jefferies. Please go ahead.
Yes. Hi, Mark, Kevin and Hinde. 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 lower growth in global sales and higher growth in new markets had a positive effect.
Sorry, I'm going to have
to either ask either you or Fido to repeat the question.
Yes, it's Ziggy. 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 But that's not coming through. Can you just talk to that a little bit more? I don't think I quite understood what you mentioned before.
Yes. No, 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 start up mode and have lower gross margins.
So the projects in general tend to improve sorry, the gross margins of the projects tend to improve over time as we get more practice in doing what the customer is after and deploy more technology to help them, etcetera. So your intuition is correct in one sense in that product based stuff It's 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.
Okay. No, that makes sense. And on 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 that's $200,000 an applesaucom.
Yes, yes. They all in general, yes. The only thing I would call out is we have a handful of extremely large project. 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 10,000,000, 20 and above 1,000,000 Range is probably more the exception than the rule, but it's very easy to get them into the millions.
Okay. Yes, that's very useful. And year to date revenue and orders in hand plus 10% so which compares to the first half of 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 aside, one minute, have you seen that in the 1st 2 months of the second half?
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 Hi. We are very aware of last year's experience.
So we spent a lot of time with customers, a lot of time monitoring projects, making sure that we
And whether you've seen those improving trends in July August?
Other than what I've said, Michael, no.
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 Here or is that larger 2 HQ just going to be kind of something that exists from here on out?
So the trend into the second half of this year is due to a very firm second half SKU that our 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 Say hi to Ziggy.
Thank you. Your next question
I just have four questions. Just 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 did not have a Q4 SKU and this year you do have it, shouldn't we be going back to FY 19% before which is around 70%. Can you just kind of tell them this match?
Yes, Suraj. So we specifically call out and help guide in terms of that reference point to last year, because it 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 2020 there.
Got it. Second thing on ACV, the committed revenue, that's actually declined from the February levels that you disclosed. I need to understand what's happened there given that's been a key focus.
Yes. So As explained in an earlier question, there are annual contracts and there are automatic renews on those contracts, but not all contracts renew. 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.
Mark, would that be the major customers or the smaller customers? It's
a variety of things.
Right. Third thing, this might be a bit early. Given you're reinvesting the savings, which makes sense. How should we think about FY 'twenty two EBITDA margins sort of indicating that it should be in line with this year? Is that how we should think about
Yes. So, Rod, we're still obviously working through all our planning and initiatives with the 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's the levels of reinvestment and areas that they deployed to and then the revenues that we expect to derive in how much in 'twenty two and how much of that's building revenues beyond
I think also, Suraj, we've been through a couple of rocky halves, second half last year, first half this year. Our confidence around the second half year 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.
Understood. Just last one. Just on the acquisition. Am I right with this not being really an AI data play? It's more data, but not AI data?
It's 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're 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
Thank you. Your next question comes from Bob Chen from JPMorgan. Please go ahead.
Hey, good morning, A few questions from me. You've obviously called out sort of a second half SKU as well as sort of the 4th quarter SKU. Can you talk a little bit about that for the Q4 SKU and how that compares to some of your historical period?
So other than the reference to the first half, second half SKU that I talked about, that is The SKU this year is comparable to prior years before 2020. We always have a degree of the SKU into for the Q4 and a lot of that's driven by the U. S. Retail market. Online advertising ramps up into the 4th quarter.
Searches ramp up into the 4th quarter, e commerce activity and regular retail activity ramps up into the Quarter and that drives a lot of the work that we do. So the SKU from a half on half basis is comparable to pre-twenty years and the Q4, pardon me, is has been a feature of the business for some time.
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 sort of also mentioned that you expected the growth coming through in the second half. I mean, do you expect that Pricing revenue stream to ever get back to sort of a historical level.
So The background to what's illustrated on Slide 9 is if you cast your mind back to the beginning of the pandemic And we pointed out that online ad volumes had taken a hit. It was Perhaps a realization for many companies in the ad in the online ad world that their hyper reliance on that platform It was something they needed to address. And there were other factors as well, privacy, regulatory So from that point onwards, many of the companies in the ad world started investing very heavily in other projects. They're already doing some non ad 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 slides 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 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.
They're going to be solutions that are more cognizant of data privacy, etcetera. But we do expect that those of data privacy, etcetera. But we do expect that those solutions will be data based and will be machine learning based and and that will require training data. So all of that, Bob, is to say that there's some sort of underlying things We go into what's on Page 9, but the reliance that our customers have on advertising revenue makes it extremely likely that revenue will come back and that's what our customers are telling us. And the extent and nature of that come back is still to be seen.
Okay, sure. And I think you also called out in the past that sort of opportunities of government has been a little bit slower than Can you talk a little bit about how big that opportunity is and how that sort of compares to what you were previously thinking?
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 present substantial scale. It's just not moving as quickly as the commercial side of our business. So we're just calling that out.
Okay, great. Thanks guys.
Thank you. Your next question comes from Paul Mason from E&P. Please go ahead.
Hey, guys. Just 3 for 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 and D phase?
So Paul, some of them are in being used in commercial projects, and they are going towards the efficiency those projects. But with any new technology, we kind of start small and grow from there. So not material numbers at this point. The 2 down the bottom are being used across a number of projects and they go to our internal efficiency. For The fraud detection we get a lot of people applying for work for crowd work under multiple names, sometimes hundreds of that they generate automatically.
So we're now able to find that extraordinarily quickly and that benefits in 2 ways or benefits us and the customer in 2 ways. 1, it makes us more efficient. But 2, 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 margin.
Okay, great. Thanks. 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 if you Just point out, if I may, the floor in my logic. So you're calling out similar EBITDA margins to FY 'twenty and the low end of your guidance It's $81,000,000 EBITDA.
So if I use $78,000,000 that's about $475,000,000 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 So if I use like 7%, that's about $350,000,000 And so if I'm sort of thinking that it's $350,000,000 Global Services and about 100 25 to new markets. Blake, is there anything wrong with my logic there?
Paul, I'd say the one thing though is When you're taking the $81,000,000 you're taking the effect of 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 outlooks. I suggest when you're doing that work, work on that original guidance range, which has not been reduced by by the provision, the call out for Quadrant. 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, We then apply that percentage to last year's revenue, all 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 are obviously supporting where we're coming out with the guidance, which is at the lower end of the range. Yes, obviously excluding the Quadrant business.
Okay, great. Thank you. And just the last one for me, just on the revenue plus work in hand number. So I'm going to Translating sort of the February numbers that you used to provide in Aussie dollars to U. S, but it looks like the so the actual dollar gap in February was about 45 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 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 sort of ramped up again in terms of your order book.
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 It reflects the business in a sense, and there's a skew from the first half to the second half as we've explained. So That could explain your conclusions there.
Okay, cool. All right. That's all for me. Thanks a lot.
Thank you.
Thank you. Your next question comes from Ross Barrows from Wilson. Please go ahead.
Hi, good afternoon. Thanks. Just Two super quick ones, both on Quadrant. It's been explored quite a bit already. Just in terms of team size, looks like it's in the mid-20s, but any color you can give around that?
Of that order, Ross.
Yes, it's a small business. Yes.
And then just lastly, the earn out where it does mention it's of 'twenty two and 'twenty three revenue milestones. Just being particular around that, will that be paid to the end of 'twenty three Once both are achieved or is it kind of half after 'twenty two and half after 'twenty three?
It's spread across both.
Yes. Okay. Thanks. Yes.
So 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 on this and the share price around that time.
Yes, that's great. Thank you.
Thank you. Your next question comes from Conor O'Prey from Canaccord Genuity. Please go ahead.
Hi. Maybe just a quick question for Kevin on Share based payments. Apologies if I missed anything you said there, Kevin. Just they were obviously a contributor Are they 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 'twenty?
Sorry, Conor, can you just repeat those numbers again in terms of the comparative metrics and then I'll be able to
Yes. So I think they were 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 And will they continue to contribute in the second half?
No, no. It will be an expense in the second half. So Essentially, there's a 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.
Of a similar magnitude to previous?
Yes, around those levels. Obviously, with exclusion of this particular plan that we've that obviously we've adjusted for.
All right. Thank you.
Thank you. Your next question comes from Suraj Ahmed from Citi. Please go ahead.
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 4th quarter surge, which 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 one that you actually have more work than you expect in the year?
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. 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.
Yes. And the other thing, obviously, it's reflective of the demand volumes that we've been told about. As Mark talked about, In terms of the later stage quality within the pipeline, Actually, 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 change to Q4 in terms of significantly higher than kind of What we've been told right now within obviously there
will be movement there and similarly the other way. And just to remind you, Suraj, The delivery requirements tend to be around the or our ability to deliver, sorry, tends to be around the crowd. And the crowd conflicts up and down pretty quickly.
Yes, got it. Okay. Thank you.
Thank you. There are no further questions at this time. I'll now hand back to Mr. Bryan for closing remarks.
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 is safe 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 to respond to an increasing variety of use cases and opportunities. Thank you to everybody 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.