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Operator: Good morning and welcome to Wiley's Second Quarter and Fiscal 2026 Earnings Call. As a reminder, this conference is being recorded. All lines have been placed on mute to prevent any background noise. After the speakers' remarks, there will be a question and answer session. At this time, I'd like to introduce Wiley's Vice President of Investor Relations, Brian Campbell. Please go ahead.
Brian Campbell: Good morning, everyone. On the call with me today are Matthew Kissner, President and CEO, Craig Albright, Executive Vice President and CFO, and Jay Flynn, Executive Vice President and General Manager of Research and Learning. Note that our comments and responses reflect management views as of today and will include forward-looking statements. Actual results may differ materially from those statements. The company does not undertake any obligation to update them to reflect subsequent events. Also, John Wiley & Sons, Inc. provides non-GAAP measures as a supplement to evaluate underlying operating profitability and performance trends. These measures do not have standardized meanings prescribed by US GAAP, and therefore, may not be comparable to similar measures used by other companies, nor should they be viewed as alternatives to measures under GAAP. We will refer to non-GAAP metrics on the call, and variances are on a year-over-year basis and will exclude divested assets and the impact of currency. Additional information is included in our filings with the SEC. A copy of this presentation and transcript will be available at investors.wiley.com. I'll now turn the call over to Matthew Kissner. Thank you, Brian. Hello, everyone, and welcome to our Q2 earnings update.
Matthew Kissner: Before I get into results, which were highlighted by strength and momentum in research and AI, but also declines in learning, let me briefly touch on our agenda. I'll start by outlining what's happening in learning and how we're addressing it. Next, I want to address the questions we've gotten from prospective investors about the unique durability and resilience of the research business and the positive role AI is playing. As you will see, we believe AI is an accelerator for our research core. Building on this, investors naturally want to learn more about our AI growth strategy. So we're going to spend a little time this morning addressing those topics in more detail. I'll also talk about how we're executing on our full-year commitments and walk through our overall growth drivers. Craig will review our performance, operational excellence, and margin expansion initiatives as well as our outlook for the year. Now on to our purpose, which is to unleash the power of science. It means transforming trusted scientific knowledge into practical tools and intelligence that solve real problems. We're moving with urgency to integrate scientific research into new technologies to revolutionize R&D across corporate, academic, and government markets. It's a paradigm shift and we're at the center of it. Never has the trust and accuracy of information mattered more. Our customers range from Nobel laureates to early career researchers, from Fortune 500 innovation teams to government research bodies, all relying on us to ensure scientific excellence and turn scientific knowledge into competitive advantage. Let's turn to the quarter. We saw a mixed revenue picture, with strong growth in research and good momentum in AI, offset by market challenges in our learning segment. I'll dive into learning in more detail on the next slide. Research publishing delivered strong 7% growth on worldwide demand to publish, read, and license. Volume remains at record levels worldwide. We executed another AI licensing project for an existing LLM customer this quarter, putting us close to $100 million of AI training revenue in less than two years. Our corporate expansion is accelerating with new subscription customers and a strong pipeline. We continue to advance our strategic partnership with AWS, Anthropic, and Perplexity, and added Mistral AI during the quarter. We delivered strong earnings growth as we continually address our overall cost base, reduce our corporate expenses, and drive disciplined capital allocation. Our Q2 adjusted operating margin was up 250 basis points to 18.8%. We increased our share repurchases by 69% this quarter to $21 million. We see our shares trading well below our assessed true value, which positions buybacks as an efficient use of capital. Through the half, we've returned $73 million to shareholders in buybacks and dividends, and our current yield is around 3.9%. Finally, we expect to drive leverage materially lower this year. Our strong balance sheet is expected to get even stronger. I want to acknowledge our challenges in learning before getting into the positive developments this quarter. Those of you who know me know that I'm not one for spin. Let me just say it's been an unusual year for learning, driven by a set of external factors which began in the first quarter. First, across the industry, we've seen a significant change in inventory management from Amazon. We've seen this before, and it's an abrupt challenge to manage through. Second, consumer spending is soft and professional books are somewhat cyclical. It's the only consumer cyclical part of our business. Third, we've seen enrollment challenges in select Wiley disciplines, namely computer science, down 8% in the fall semester. Computer science has been an important growth area for us, particularly with digital courseware. Fourth, corporate spending and hiring is soft, and that means lower consumption for our personality and team development programs. Many of these factors are macro-related and we'll be watching how these trends play out for the balance of the year. From a mitigation standpoint, we're ruthlessly prioritizing to where we see upside, including inclusive access and other digital offerings and instituting pricing strategies, category optimization, and targeted marketing campaigns. We expect learning declines to moderate in the second half as inventory actions stabilize, although revenue is expected to be down for the full year. Cost actions will help offset any top-line impact. Let's turn to our key strategic priorities and value creators and the execution of our fiscal 2026 commitments. As always, our first objective is to lead in research. It was a strong quarter for research with 7% revenue growth in research publishing and 220 basis points of EBITDA margin improvement. We continue to drive above-market growth in submissions, up 28% and 12%, respectively. Remember that 80% of our volume comes from outside the US, and strong demand is evident across all regions with double-digit submissions growth in China, India, Japan, the UK, Germany, and the US. Higher volumes are leading to both double-digit growth in author-funded open access and compounding growth in our recurring revenue models. Our second commitment is to deliver growth in AI and adjacent markets. We executed another licensing project for LLM training, with $6 million realized in the quarter and $35 million year-to-date. On the innovation side, we're now at 30 plus publisher partners for our Nexus content licensing service, and we're in active discussions with others. As a reminder, this is where we combine our content with that of our publishing partners and license it to AI model and application developers. We also launched our AI gateway, an interoperable content enrichment and delivery platform in partnership with AI ecosystem players like Anthropic and AWS. Our corporate expansion continues with eight customers subscribing to our knowledge feeds with strong interest across multiple verticals. Our third commitment is to drive operational excellence and discipline across the organization. Craig will run through this in more detail. But we've made terrific progress in reducing our corporate costs and improving our research margin. We still have work to do, but we're pleased with our progress so far. Let's talk about our resiliency across economic cycles and AI as a tailwind. What makes research different? First, peer-reviewed publishers set the global standard for scientific excellence, distinguishing solid research from world-changing discoveries. At the center of this ecosystem are Wiley journals, independently rated and widely recognized, forming a lasting competitive moat. Tens of millions of researchers worldwide know and trust these journals, and peer review is at the heart of it. An industry survey found that 94% of the researchers who participated believe peer review is essential for maintaining control and quality in scientific research. Second, peer-reviewed content is a must-have for institutions and increasingly corporations, through both good times and bad. Research is the core of a university. Over 10,000 research universities around the world subscribe to our portfolio of journals. Researchers at these institutions must have unfettered access to these journals, and they get it through multiyear digital licenses. Today, institutional customer retention is above 99%. In addition to universities, R&D-centric corporations are now exploring integrated feeds of this content for their AI models and applications. Third, publishing is essential for a researcher's career and for global recognition of scientific achievement. For example, tenure often requires seven to nine publications, and a strong publication record is key when applying for academic positions. Publishing in a top-tier journal brings international acclaim while also serving as the main way to demonstrate the impact of research and secure additional funding. Fourth, research output is ever-increasing, driven by global R&D spend. Remarkably, article output has grown every year since 1944, with the exception of a slight dip in 1971. Moreover, the rate of research output is expected to accelerate given the increasing importance of science and the rise of AI. Our analysis found that 84% of researchers are now using AI in their work, up from 57% last year. Another study showed a threefold increase in the number of papers by researchers who use AI. Fifth, research evolves constantly. An estimated 14,000 new articles are published daily worldwide, making recency critical for AI. In high-stakes fields like life sciences, AI systems must continuously incorporate the latest findings to remain reliable and effective. Finally, published research is protected under IP copyright law, and its use must be authorized. We've talked about the Anthropic copyright settlement, the largest in US history. Beyond this, approximately 60 copyright lawsuits are currently underway involving AI. Let me run through our key differentiators as we transition to an AI economy. Why do we consider it a long-term tailwind and a growth engine? First, we provide access to much of the world's trusted scientific, technical, and medical content through our own portfolio and that of our publisher partners. We are a big three global publisher at a time when quality and scale matter most. We are further differentiated by our top position in fast-growing knowledge domains, chemistry, material science, oncology, technology and engineering, food science, and finance and economics. We have strong long-standing relationships with researchers, institutions, societies, and funders across the globe. We're the society partner of choice in the industry. And our platforms host nearly 50% of the world's English language journals. We're a first mover with LLM developers in building out AI models and applications. So much so that other publishers want to be part of our licensing network. We're a pioneer in securing strategic partnerships with the world's most advanced AI innovators. The first research publisher to be on the AWS Marketplace and Claude for Life Sciences. Finally, rather than develop and compete through closed platforms, we're partnering with others through a CapEx light and open platform approach. This strategy allows us to leverage existing infrastructure while enabling broader collaboration across the research ecosystem. An open platform accelerates innovation by allowing multiple partners to contribute and build upon shared capabilities, reduces our capital requirements, and creates network effects that benefit all participants, ultimately delivering more value to researchers than any single organization could achieve alone. Let me walk through our three growth factors. Content, platforms, and markets, and the drivers underneath them. As you can see here, some of our drivers are enabled by last trends in our core research business, and some enabled by the use of AI. In content, we're expanding our journal portfolio and brands into fast-growing STM fields, as with our advanced brand. We continue to license our proprietary content and others for LLM models and corporate applications. In platforms, we have our research exchange publishing platform, our AI gateway, and future growth opportunities with data products. I'll talk to the first two in the coming slides. On the third, we see proprietary data as a competitive moat over time as we deeply embed ourselves into the workflows of our corporate customers. For example, we have the most comprehensive spectral database collections in the world for chemists and other researchers. In markets, there are two growth drivers. The first is geographic, where we see a targeted expansion globally as China, India, and Brazil invest to become superpowers in science and technology. China is now the number one source of research output in the world. India and Brazil are showing strong double-digit submissions growth and expansive nationwide agreements. The second growth driver is building a significant presence in high-stakes corporate research, through the use of AI and data analytics. As noted, corporate makes up 80% of total US R&D spend but is only 10% of our revenue base today. Although it's early days, corporate R&D represents a substantial future growth opportunity for us. Let's take a step back and review our content licensing models. We think about the market in two waves. The first is licensing archival content to train large language models. This quarter, we realized $6 million of licensing revenue with an existing LLM customer and $35 million year-to-date compared to approximately $40 million in fiscal 2025. We continued to have active discussions with model developers, although these opportunities remain hard to project. The second wave is in licensing a knowledge feed of our content for vertical-specific AI applications. R&D-intensive corporations are then able to integrate this knowledge into workflows to identify breakthroughs, speed up product development, and lower costs. As noted, we currently have eight customers, including the European Space Agency, Novartis, and Regeneron, among others. We expect this number to ramp up as these vertical applications advance. Today, we're in active discussions with companies ranging from energy to pharma to consumer staples. An example of our corporate strategy is our recent agreement with IQVIA, a leading provider of clinical research services to the life sciences industry. IQVIA will bundle our clinical outcome content with their clinical research capabilities to deliver one-stop solutions for pharmaceutical companies. It's an important example of the corporate R&D opportunity for Wiley as we turn knowledge into real-world impact. During the quarter, we continued to add partners to our Nexus licensing network and launched our AI gateway content enrichment and distribution platform. On Nexus, we generated $16 million of revenue year-to-date, all of it in Q1, and continue to build out our partner network of 30 plus high-impact book and journal publishers with more in the pipeline. Onto our AI gateway, which is complementary with large language models. You can think of this service as a Wiley content repository that can be accessed by an API connector through platforms like AWS Marketplace and Claude for Life Sciences. Users with a subscription can run queries through the connector to retrieve highly relevant information from our platform. Importantly, as these involve retrieval augmented generation, or RAG models, our content supplements the model to provide more accurate trustworthy results, but is not absorbed in the model. Unlike closed ecosystems that require researchers to adopt proprietary tools, Wiley's AI gateway is differentiated for its openness, partnership, and interoperability. We also envision it for other publishers who want to leverage our technology and infrastructure to make their content available for corporate and other AI applications. We're currently in user trials with corporate R&D researchers and academic institutions. I'll turn to our research exchange platform where 65% of our journals are now live. The main point I want to emphasize is that this transformative publishing platform goes beyond efficiency and lowering our cost to publish. It's also about driving incremental revenue growth. As an example, the platform will deliver a best-in-class user experience from submission to acceptance, enabling us to attract new authors, drive more volume, and manage it more efficiently. With AI incorporated across the platform, we will improve submission capture, automate refer and transfer, and improve our turnaround times. As a reminder, about 70% of articles submitted to Wiley are rejected mainly due to improper fit. Through the AI functionality we introduced, we can now transfer these articles to more appropriate journals within our portfolio. We are rapidly scaling delivery of these new features and services. We believe that researchers and other professionals want trusted content that integrates with their own tools and their LLM of choice. And so we're partnering with AI players, remaining agnostic, and carving out our own critical niche. Recently, we added Mistral AI to our base and became the first research publisher to list a full-text agent knowledge base with AWS, enabling AI agents and applications on the AWS Marketplace. We have won new corporate customers through the Marketplace and are in active dialogue with others for our own subscription knowledge feeds. Also note, we are the first research publisher to have our connector featured on Claude. All good momentum. To summarize, I hope you can see why we're fully confident in our research core and excited about the expanding AI opportunities in front of us. I'll now turn the call over to Craig.
Craig Albright: Thank you, Matthew, and hello, everyone. My focus is straightforward. Continue to drive discipline across the organization, challenge complexity, and shift our portfolio toward high-margin, high-ROIC business models. We're making real progress on multiple fronts, but we have more work ahead. Turning to our second-quarter results. It was a strong quarter for our research business and a challenging quarter for learning. At the same time, we continued to deliver material margin expansion. Adjusted EBITDA grew 8%, and adjusted operating margin expanded 250 basis points to 18.8%. This reflects disciplined cost management, technology transformation, and AI-driven productivity gains. Themes, I'll expand on in a moment. As well as the benefits of our product profitability actions to shift toward higher-margin businesses. Let me walk through segment performance starting with research. Research delivered 5% growth and a 220 basis point improvement in EBITDA margin to 33.5%. Demonstrating our continued operating performance and cost improvements. Research publishing was particularly strong this quarter, driven by record submissions, solid growth in our recurring revenue models, and 28% growth in author-funded open access. AI revenue in research publishing totaled $5 million of our $6 million licensing project this quarter, reflecting continued demand for AI LLM training. Calendar year 2026 subscription renewals are underway, and while it's still early, renewals are tracking steadily worldwide, including early commitments from large institutional customers, such as the regional consortium in Australia and New Zealand. We'll have a fuller picture in March when the majority of our renewals are complete. Research solutions declined 6% due to lower corporate spending on advertising and recruiting. We expect improvement in the second half driven by strong pipelines in spectral data products for OEMs, and managed advertising and knowledge hub solutions for pharma and healthcare customers. Through the half, research revenue and adjusted EBITDA were up 5% and 8%, respectively, with EBITDA margin improving 60 basis points to 30.9%. Now let's turn to learning. Learning was down 11% in the quarter, driven primarily by headwinds in professional and academic as well as prior year AI revenue of $4 million. Professional declined 16% impacted by retail channel dynamics, particularly with Amazon inventory adjustments and softer consumer spending. Print was the main driver, followed by assessments due to a soft corporate environment. We're responding by reorganizing our editorial focus toward higher-value authors and accelerating our shift toward digital products, where we see stronger demand and better margins. Academic declined 8%, also affected by retail dynamics, and an 8% enrollment decline in undergraduate computer science, which pressured our ZiBooks STEM courseware. That said, our strategic inclusive access program continues to grow revenue by double digits with a healthy pipeline. Through the half, learning revenue was down 10%, with adjusted EBITDA down 12%. Segment EBITDA margin declined 80 basis points to 34.4%. We're taking targeted actions to stabilize revenue and protect margins in the second half, including tighter cost discipline and accelerating product repositioning. Let me turn to operational excellence, which remains central to our margin expansion story. We're driving three major initiatives. First, technology transformation. We're building an AI and data-enabled technology organization, consolidating locations, rationalizing our application footprint, and refocusing our enterprise modernization effort to be more flexible and cost-effective. This is a multiyear transformation that will materially reduce our cost base. Second, ongoing cost discipline. We continue to deliver savings from prior actions while managing expenses tightly. This quarter, unallocated corporate expenses on an adjusted EBITDA basis declined 18% or $8 million, driven by targeted actions in technology, HR, and finance. Research has been a particular success story where we've driven both cost improvements and 220 basis points of margin expansion. Third, AI-driven productivity. We've established an AI center of excellence to automate manual processes and fundamentally change how we work. We're deploying AI agents, building an active user community, and delivering measurable productivity gains. A clear example is our customer service transformation and partnership with sales where we're seeing meaningful efficiency improvements. These efforts are ongoing and will continue to drive margin improvement as we scale them across the organization. Let's turn to our financial position and capital allocation. Free cash flow was a use of $108 million, a 17% or $22 million improvement from the prior year. As always, cash flow is seasonally negative in the first half due to journal subscription timing. We collect the majority of our cash in Q3 and Q4. CapEx was $31 million, compared to $36 million in the prior year. When combined with the capitalized cloud spend reported in cash from operations, total CapEx and cloud investment was $38 million for the half, down from $42 million in the prior year. On capital allocation, we continue to deploy capital strategically. We acquired the high-impact journal, Nanophotonics, which strengthens our physics portfolio and positions us at the forefront of the fast-growing optics and photonics field. We'll continue to opportunistically pursue acquisitions of high-impact journals and collections where we see strategic value and attractive financial returns. Share repurchases were up 69%, to $21 million or $35 million year-to-date, compared to $25 million in the prior year period. With our new 10b5-1 plan, we're now active throughout the year. Our dividend yield is around 3.9% supported by a healthy payout rate and we continue to reinvest in organic growth initiatives. Finally, our leverage continues to improve. Net debt to EBITDA was 2.0 times on a trailing twelve-month basis, down from 2.2 times in the prior year. We expect leverage to decline materially by the end of fiscal year 2026. Turning to our outlook, we're reaffirming guidance for adjusted EBITDA margin, adjusted EPS, and free cash flow, while narrowing our revenue outlook to the lower end of the range. Let me walk through the key metrics. Revenue growth is now expected to be in the low single digits, down from our prior range of low to mid-single digits. Research demand is tracking better than expected, but as discussed, learning will be down for the year. The second-half declines will moderate. We expect AI revenue to be moderately ahead of last year's $40 million. Adjusted EBITDA margin of 25.5% to 26.5%, up from 24% last year. Adjusted EPS of $3.90 to $4.35, up from $3.64 last year. And free cash flow of approximately $200 million driven by EBITDA growth, lower interest payments, and favorable working capital. CapEx is expected to be comparable to last year's total of $77 million. One note on quarterly phasing, we anticipate Q3 will be lighter than typical due to the timing of AI project revenue which creates a year-over-year headwind of approximately $9 million in research. Growth is weighted to Q4 driven by journal renewal timing, customer pipeline conversions, and research solutions and learning. As always, we encourage you to focus on full-year performance as the best measure of our progress. With that, I'll pass the call back to Matthew.
Matthew Kissner: Thank you, Craig. Let me briefly review our key takeaways before I open the floor to your questions. We're delivering strong growth and momentum in research, supported by robust demand and the disciplined execution of our strategy. Our leadership position in AI continues apace, with another LLM training agreement in Q2 and increasing momentum for our subscription knowledge feeds in corporate R&D. Our strategic partnerships with AI innovators are starting to yield early results, and we're making good headway with our innovative publishing and aggregation platforms. We're focused on our fundamentals and delivering strong earnings growth, material margin expansion, and cash flow improvement, for reinvestment and return to shareholders. As I said before, continuous improvement is a way of life for us now. Through the half, we returned $73 million of cash to shareholders in dividends and share repurchases. Our balance sheet continues to be a foundational strength as we further reduce our leverage. And finally, we're confident in our long-term direction, driven by our unique right to win in research and transformative opportunities in AI. I want to thank you all for joining us today for your interest and for your investment. And special thanks to our Global Wiley colleagues for all they do to make us a very special company with a very special past and a very meaningful and promising future. I want to wish all of you a happy and healthy holiday season and a momentous New Year. I'll now open the floor to questions.
Operator: At this time, I would like you to press star then the number one on your telephone keypad. Your first question comes from Daniel Moore with CJS Securities.
Daniel Moore: Thank you. Matthew, Craig, Jay, good morning. Thanks for the questions. Start with the research side. Research revenue grew, you know, 5% ex-currency, driven by OA and mixed model, which is great to see. Does that feel like the right place to be? Just wondering if there could be some incremental upside to that type of growth. Not necessarily next quarter, but over the next, you know, near to midterm. Just given the strong and continuing high double-digit growth that we've seen in article submission over the past few quarters.
Brian Campbell: Brian, I do believe that your line may be muted. Ladies and gentlemen, please hold and the conference will resume momentarily. Thank you for your patience.
Daniel Moore: It's unmuted. Can you hear us at all?
Operator: Yes. You can go ahead.
Matthew Kissner: Alright. Great. Thank you. Sorry, Dan. We had a little technical glitch here. Let me begin and then ask Jay to comment. You know, the market typically grows. You know? Fixing. You can hear us now? Can you hear us now, Dan?
Daniel Moore: Yes. Okay. Good. Sorry.
Matthew Kissner: You know, we think we're gonna be growing at the top of the market growth, if not I think there's a potential to outperform given our strong article roles. I mean, that's a very powerful leading indicator here. So let me ask Jay to maybe add a little color to that.
Jay Flynn: Yeah. Hey, Dan. You know, last quarter, we characterized, and I think others in the space characterized it, overall market growth sort of trending between 3-4%. We thought we'd be at the high end of that. And as you saw, 5% in the quarter, 7% for research publishing in the quarter. You know, underpinned by really strong metrics as you talked about. We're cautiously optimistic, but we're just getting into the renewal season now. As you know, we're beginning dialogue and beginning the conversations executing renewals for calendar '26. Obviously, feel good about the performance in Q2 for research and in particular, in research publishing. And, you know, we'll leave it at that for now. But I feel like, you know, at the top end of the market, is a comfortable place for us. And we'll watch how it develops as the renewal season comes in.
Daniel Moore: Very helpful. I appreciate the color on AI, not only the license revenue but, you know, the other opportunities. Just maybe a little bit more color around $6 million in revenue that you booked during the quarter. It sounds like it was with an existing LLM customer. Talk about the pipeline of opportunities. Are you seeing customers like that sort of come back for additional sites to the Apple? And I think you said full year, you know, up modestly versus the $40 million, which would imply, you know, something about $5 million in licensing for the back half of the year. Just want to make sure that's correct.
Craig Albright: Yes. Good morning, Dan. Craig Albright here. So I think you got the read right. You know, the $6 million deal, we feel really good about. It was majority Wiley content. It was a repeat customer. And, you know, it was a good signal that there continues to be some length in the LLM training model that we've talked about in the past. We have also talked about the fact that this is a bit lumpy. You know, that it's hard to predict exactly when the deals come in. We want to make sure they're the right kind and the right, you know, guardrails kind of put around them, and that's what we continue to do. We guided to moderately up year over year. We have a continuing pipeline that we're working, and I think the way you phrased it is about right. Let me turn it over to Jay and see if he doesn't add anything else.
Jay Flynn: Yeah. Thank you. Thank you, Craig. Dan, you've called it right based on what we reported and what we're guiding to. But I think for me, you know, I want to make one additional point, which is that, you know, our commitment both to investors, but also to ourselves is to generate meaningful deep relationships which drive recurring revenue and to continue to come back and learn from these partnerships to drive our own product innovation pipeline. So it's no coincidence that, you know, we're doing training deals, but we're also partnering with AI native companies. It's no coincidence that once we've established those partnerships, we've developed a strategy that relies on openness, that relies on meeting users where they are using the tools that they want, and then using both of those things to go into corporate R&D and to help corporate customers achieve their aims more quickly, cheaper, and with an increasing degree of confidence. So we feel good about all three of those opportunities and as we get through the rest of the year, you know, hope to talk more about all three of them as it relates to fiscal '27. But, you know, we'll keep it at that for now and want to reaffirm your read on where we're guiding to now.
Daniel Moore: Understood. Helpful. Switching gears to learning, obviously, it remains challenged. Maybe your best guess for how much of the decline is due to sort of end market demand versus inventory management at large retailers, Amazon specific, in the channel. And I think you said, you know, that headwind should moderate in the back half. But, you know, the absolute any additional color there would be helpful.
Matthew Kissner: Yeah. Let me spend a few minutes and then turn it over to Craig and certainly Jay. You know, I spent a week at the Frankfurt Book Fair in October, talked to other publishers, and everybody is seeing the impact of this in, let's call it, change in inventory strategy just because of the importance of Amazon in this business. Our early indications are that that ordering pattern is starting to normalize. And we don't see any change in end-user behavior. In other words, are people reading books? You know? So there's no reason to believe that there's kind of been an abrupt structural change at this point in time. But we are learning and keeping our eyes on this. So, Craig, Jay, anything you want to add to this?
Craig Albright: Yeah. No. I think, Matthew, you covered it well. You know, we don't give guidance specifically on segments, you know, Jay highlighted earlier here, you know, that there are some headwinds here in learning. We expect those to normalize, as Matthew said. Still likely to be down for the year. But I think we view it more as cyclical than structural in terms of what we're seeing in terms of the trade business. There are parts of it in terms of enrollments in higher ed where we've got our closer eyes on to see if there's some other shifts going on there that we have to kind of continue to stay focused on more structural. But at this point, I think the majority is leaning towards cyclical. We've seen these kinds of cycles in the past. And we happen to be at the kind of bottom of one of those cycles. But all the indicators are that there should be some normalization and recovery here.
Daniel Moore: Helpful. Well, kudos for maintaining the guidance given those, you know, those headwinds that certainly a little bit stronger than, you know, what we thought a couple of quarters ago. Maybe just one or two more. You stepped up the pace of buybacks during the quarter. Free cash flow guide implies something well north of $300 million in free cash flow coming in the back half of the year. Given that and the health of the balance sheet, do you anticipate ramping that pace further as we get, you know, how are you sort of weighing the, you know, accelerated buybacks versus delevering as we look at the back half of the year? Thanks again for all the color.
Craig Albright: Great question, Dan. Thank you. As we've said in the past, we have a very disciplined approach to capital allocation. And the opportunity we have certainly with the cash flow guide that we're giving is, yes, that we could continue to use some of that towards share buybacks. We want to maintain between, you know, our growth opportunities internally. We want to make sure that we continue to manage the leverage ratio at the right levels. But we do see opportunities. And I would say in that front, we continue to be opportunistic. You know? We're now in the market every trading day of the year. With our 10b5-1 plans. When the prices are attractive, you know, we have shown already that we are more aggressive in terms of share repurchases. I think we'll continue to look opportunistically going forward as well. But we feel good about the pace we're on with our return to shareholders, and we're going to continue to maintain that discipline.
Daniel Moore: Alright. Now I'll circle back on the same follow-up. Thank you.
Operator: There are no further questions at this time. I'll now turn the call back over to Mr. Kissner for any closing remarks.
Matthew Kissner: Yes. I want to thank you all for joining us. Once again, I want to wish you and your loved ones a healthy and happy holiday season. We thank you for partnering with us on this journey, and we look forward to updating you on our progress at our March call. Have a great holiday.
Operator: This concludes today's conference call. Thank you for participating. You may now disconnect.