Good afternoon and welcome to Nerdy Inc. Q4 Earnings Call Annually. All lines have been placed on mute to prevent any background noise. And after the speakers' remarks, we will conduct a question-and-answer session. [Operator Instructions] Thank you. I will now turn the call over to TJ to begin today's call. TJ, you may begin.

Good afternoon and thank you for joining us for Nerdy's Fourth Quarter 2022 Earnings Call. With me are Chuck Cohn, Founder, Chairman, and Chief Executive Officer of Nerdy; and Jason Pello, Chief Financial Officer. Before I turn the call over to Chuck, I'll remind everyone that this discussion will contain forward-looking statements, including but not limited to expectations with respect to Nerdy's future financial and operating results, strategy, opportunities, plans and outlook. These forward-looking statements involve significant risks and uncertainties that could cause actual results to differ materially from expected results. Any forward-looking statements are made as of today's date and Nerdy does not undertake or accept any obligation to publically release any updates or revisions to any forward-looking statements to reflect any change in expectations or any changes in events, conditions or circumstances on which any such statement is based. Please refer to the disclaimers in today's shareholder letter announcing Nerdy's fourth quarter results and the company's filings with the SEC for a discussion of the risks. Not all of the financial measures that we will discuss today are prepared in accordance with GAAP. Please refer to today's shareholder letter for reconciliations of these non-GAAP measures. With that, let me turn the call over to Chuck. Chuck?

Thanks, TJ, and thank you to everyone who has joined us today. Over the last 10 months, we've been working to transition our products and revenue model toward long-term recurring always on relationships with our customers. We believe this change would benefit our consumer and institutional customers and our business model by shifting to longer-term relationships that supported evolving learner needs states. We created new subscription and recurring revenue products, including learning memberships for consumers and on-demand and teachers products for institutional customers that were built specifically to address the ongoing support we believe both types of customers desired. We shared that this new focus would require a short-term hit to revenue recognition because our packaged model has a more front-loaded revenue recognition associated with it than the learning membership model where subscription revenue is recognized linearly over time. We estimated that by month six for a given learning membership customer the cumulative revenue would catch up and surpass that of a given package customer, a phenomenon we call the J-curve. We expected that by the start of the second quarter in 2023 the cumulative build of recurring revenue from learning membership customers would cause us to return to growth in our consumer business, as well as for the total company. But now with the product suite and revenue model, we believed would position us for higher levels of growth, profitability, and predictability in the years to come. I am pleased to share that we have made substantial progress in the fourth quarter and our shift to an always-on business model is ahead of plan. Learning membership adoption continuous to exceed our expectations demonstrating higher conversion, engagement, and customer retention than our former package model, which in turn has led to meaningfully higher customer lifetime value and operating leverage. We…

Thanks, Chuck, and good afternoon, everyone. I'm pleased to be speaking with you today about Nerdy's strong fourth quarter performance and our outlook for the first quarter and full year of 2023. Our team continued to make substantial progress against our business model evolution. And as Chuck mentioned, the accelerated transition to recurring revenue streams, including learning memberships continued in the fourth quarter, reflecting the strong adoption we've seen from consumers during the back-to-school season and fall semester. Notably, we haven't observed any discernible macroeconomic pressure on demand for our products. And as we've shared in the past three earnings calls, this evolution toward learning memberships resulted in lower near term revenue and adjusted EBITDA. However, we expect that it will ultimately allow us to generate superior long term customer unit economics and drive higher levels of growth and profitability given the positive customer economics we're experiencing. This shift in revenue recognition is reflected in our revenue growth rate for the three and 12 months ended December 31. Expenses as a percentage of revenue also reflect the impacts of lower near term recognized revenue in the denominator for rate based expense calculations as we continue to progress through the J-curve during the fourth quarter. It's important to keep this in mind as we discuss our financial results for the period. In the fourth quarter, we delivered $41.8 million, results that were above our guidance range of $39 million to $41 million, reflecting stronger than anticipated active learning memberships, which totaled over 20,000 as of December 31 and continued strength in lifetime value performance from learning numbers. It also reflected the growth we're experiencing in our institutional business, which delivered revenue of $4.4 million, representing 10% of total revenue during the fourth quarter and record bookings of $11.3 million. On our…

Thanks, Jason, and thanks again to all of you for joining us today. As always, we appreciate your interest in Nerdy and look forward to continuing the dialogue during this exciting time for the company. With that, I'll turn it over to the operator for Q&A. Operator?

Thank you. [Operator Instructions] The first question we have from the phone line comes from Doug Anmuth with JPMorgan. Your line is open.

Great. Thanks so much for taking the question. So it's good to see the learning membership transition tracking ahead of schedule, just as you complete the J-curve transition. I guess thinking bigger picture, can you just walk us through more around your long term strategic vision for the subscription model? How you could potentially iterate around pricing and structure of memberships? And then what are the key investments to get there? Thanks.

Thanks, Doug. This is Chuck. Great question. So the way that we're thinking about this is that, learning membership is an all-encompassing comprehensive solution that supports students across multiple academic calendar years, multiple subjects, allows for them to engage across different learning modalities. And you can access any of 3,000 different subjects worth of tutoring, more than 250 live classes per week. We have asynchronous diagnostic tests. We have code verse and other coding related content. We have star courses and other on demand lessons. And our goal is to continue to add more value each and every quarter and allow for people to learn however they want, whenever they want and support them in a way that really fosters academic success and learning. And so we're going to continue to lean into additional product capabilities and bring them together in a way that really feels holistic and makes it easy to access. Some of those could include things like our AI generated lesson plans, our AI tutor solution that we're working on right now. But also just continuing to build out the content coverage that we have in areas like our class selection as an example, we'll continue to get more and more different classes that are relevant for each different audience. So we're going to be testing price, we're going to be testing contractual terms, we're going to be adding different content to see what really resonates. And as we look at some of the tests that we've done already year to date, we're really excited about that as a vector of growth and how we can kind of play with different elements to find the right fit for a given audience segment so that we can drive conversion improvements and ultimately build a high net promoter score product that people are super excited about.

Yes. And Doug, maybe -- this is Jason. I would add to that. One of the things we're seeing about learning membership model. We've mentioned this in the past. We're seeing longer duration and higher lifetime value customer relationships, enhanced gross margin, vendor marketing efficiency, we're getting better forecasting visibility, we're expanding into new [TAM] (ph) here. And so because of that during the first quarter, we transitioned all of our existing customers to learning memberships as well as our test prep audience to learning memberships, which we're really excited about as we evolve towards 100% of our consumer customers being on learning memberships by the end of 2023.

Great. Thank you both.

Thank you. Your next question comes from Ryan MacDonald of Needham. Please go ahead when you're ready, Ryan.

Hey, guys. This is Matt Shea on for Ryan. Thanks for taking the question and congrats on the quarter. I wanted to start with the institutional business, Varsity Tutors for Schools. Nice to see some contract wins and some on demand and teacher assigned contributions, which I would assume help unlock some of the COVID related learning loss relief budgets. When you're seeing clients adding these new offerings, what are purchasing habits looked like? And if you had success, seeing clients utilize that learning loss budgets? And then are you seeing more one year deals or schools trying to lock in that functionality for a multi-year period?

Thanks, Matt. Good question. So earlier -- so this past, call it, six months ago or so, we started shifting our focus from selling exclusively high dosage tutoring of [indiscernible] up to one to five group tutoring online. Two, instead also selling on demand and Teacher Assigned as you noted. And so those are district wide solutions that are available to the -- they're basically sold top down to superintendents and then are available to all students within a school district. So that is a multi-model shift where we started focusing on those bigger school districts. And we also started focusing on bundled solutions. And those are really more strategic conversations that we've had in the past. And it was a different way of partnering and selling into schools. And we've actually seen really, really good traction there. And so, there's more than 100,000 students that have access to these products. You referenced the specific funding type, one of the things that's interesting about some of these new products that align to the curriculum within school is that, there's a variety of different funding sources that can actually be used. Not just I think the [SR3] (ph) funds that you're specifically referencing. And they're embedded in the workflow of teachers and in the actual classroom. And we're seeing really good adoption out of the gate and feel good about how our ability to provide teachers leverage and provide schools with an effective tool for helping students learn and remediate loss even before it occurs actually is a very durable solution that superintendents are really excited about. So some of those could be multiyear deals, that is something we're hearing more and more, but there's a variety of different funding sources and the new products that we built specifically aligned towards those long term recurring partnerships with school districts.

Got it. That is helpful. And then jumping over to the consumer business. Learning memberships, we were surprised to see $350 average revenue per learning -- per revenue per learning membership, which was higher than the six to 12 monthly plan listed on your guys' website and then the rough math off of the $87 million run rate and 20,000 learning members gets you to a number even higher than $350. So curious, does this suggest more customers are adopting shorter duration plans or are they choosing to purchase more hours than the base six to 12 month subscriptions currently offer? Thanks.

Yes, good question. And when we first introduced learning memberships, we had basically the most simplistic version of it possible. There was kind of a one size fits all frequency and initially that only included one-on-one tutoring. And then over the course of the next several months as we head into to back-to-school, we started adding additional product capabilities that included the tutor chat, essay review, Codeverse, async, diagnostic testing and other product capabilities, but we also started leaning into additional frequencies. So that means you can purchase the ability to have a higher volume of consumption. And so what we saw was many of the learning membership customers in Q4 started skewing towards higher consumption models that allowed them to get higher levels of academic support than be the case in the base model you're referencing. So that was simply a function of us blending towards higher average revenue customers because there are higher frequencies. The interesting thing though is we're going to continue to test a variety of different flavors and memberships to drive both conversion and retention in addition to continuing to optimize the revenue per member metric. So we're not specifically trying to maximize average revenue per member, we're trying to maximize the contribution profit per visitor and build a big and profitable business. But certainly, we're very pleased with level of uptake in some of these higher frequency products in the quarter.

Thank you. Your next question comes from Eric Sheridan of Goldman Sachs. Your line is now open.

Thanks so much for taking the questions. I want to come back to the comments you made about the AI driven products. You made that announcement in the period running up to the earnings report and then we talked about a little bit in the prepared remarks. Can you talk a little bit about maybe past investment cycles around AI and machine learning? And how should we be thinking about AI and machine learning as cornerstones of your investment policy going forward? And then coming back to the way you framed it, how should we thinking about it as an add on to product enhancements, personalization and cost efficiency maybe beyond just the next six to 12 months when you think about more AI and more machine learning tools being deployed on the platform? Thanks so much.

Thanks, Eric. Great question. So we started leveraging machine learning, probably about six or seven years ago to identify patterns that wouldn't be otherwise possible for a human to detect. And so one of the first use cases we have that also ended up being one of our highest leverage applications of AI related to the match between a learner and an expert where that relationship and that connection is incredibly important in terms of compatibility to the extent to which a learner and expert want to continue working together over time. And when we can get that match right, we are rewarded with high lifetime value relationships, high net promoter source and a much better unit level economics as a result of a customer getting a great experience. And so one of the things that occurred was we started instrumenting the business in more and more places than to capture information that could ultimately inform that match as well as other ways that we can leverage all that data available to better improve personalization. So over the course of, call it, three years, I think we saw at least a 30 plus percent increase lifetime value at that point simply through [indiscernible] matching, if not, more. And also, we were able to remediate all sorts of different bad things that could happen in the customer experience and just overall polish the experience from the end users perspective. So that was one example. But we use that [indiscernible]. So we use it for customer propensity modeling, we use it for lead scoring and figuring out the most appropriate way to put energy against different customer types and interactions. We use it for our adaptive diagnostic testing that's used to assess both expert capabilities, as well as what students do or…

That was super helpful. Thanks so much for all the color.

Thank you. We'll now have the next question from Brett Knoblauch from Cantor Fitzgerald.

Great. Hi, guys. Thanks for taking my question. I guess first on the institutional side, obviously, a very strong quarter. I was just curious how many of the 70 deals that you executed were of new customers versus, I guess, re-signing existing customers?

Sure. So about 40 of the contracts were new customers, 15 of them were on demand contracts and we had one teacher assigned deal, which was an important milestone.

But -- and then I guess if we look at -- sorry, go ahead.

No, I was just going to say, look, we're really pleased with the pace that the team is putting in place. The products are resonating in the market. Now the Teacher Assigned is lives and people can experience it. We're having, I would say, deeper and broader conversations with more small districts, especially as they think about where they're going to put this kind of technology into play next year at the start of the school year.

Perfect. That's helpful. And then on the average monthly revenue of $350, I guess, where would you expect that to trend? I know you talked about a bit of self-service and some pricing model iterations. I was just curious that you'd expect that number to kind of remain where it is, trend up, trend down? Or how should we think about that?

Yes, I guess I would say -- I would expect it to remain pretty consistent. And I mentioned that because there's going to be some higher priced products. So we just moved into the test prep audience, that's a higher price product that generally has higher frequency because people are looking to study over a shorter period of time. And then that will be offset by some lower priced products, especially as we move seasonally throughout the year to try to drive retention. So think about maybe a more casual language audience where you have lower frequency one on one sessions, but then you get all the benefits of the classes and being able to talk live with peers in a forward language. So net-net, I would expect over the course of 2023 remains within the $350 range. But there's going to be some puts and takes that are both higher and lower to try to drive adoption and retention.

Yeah. The 1 thing I would add is, it's early days and based on some of the tests that we're running and how we think that we can modify learning memberships to appeal to different specific audience segments. We think that there is a big opportunity to just continue to test different modifications of memberships where we might be able to drive huge conversion improvements for certain segments, whereas in other segments where there may be some more kind of standard answer margin as group of people related to certain frequency, there's less deviation. But it's early days, we're going to take some big swings. And we think that conversion in addition to just maximizing the revenue per member per customer on average is a really big lever. So we're going to be testing there as well.

Okay. Understood. Thanks guys and congrats again.

Thanks, Brett.

Thank you. We now have Maria Ripps of Canaccord. Your line is open.

Great. Good afternoon, and thanks so much for taking the questions. First, given that the membership model is becoming sort of a meaningful portion of your revenue base, what kind of assumptions are embedded in your sort of full year guidance from the renewal rate standpoint given that some of your early cohorts will be coming up renewal this year?

Yeah. Good question, Maria. I think just as Chuck mentioned, it's still early days as it relates to renewal rates from learning memberships. We continue to see strong retention. We continue to develop new and unique products to roll into the learning memberships to drive engagement and adoption. The one thing I'd caution on is, we haven't experienced the end of one school year in the transition across the summer to another school year. And so the guide appropriately from our perspective takes into account that unknown. Certainly, we're doing a lot from a content and programming perspective, whether it's classes or enrichment versus academic subjects during the summer months, increased prevalence from star courses, to drive engagement. But that is the one unknown that I would just caution you guys when we think about modeling the summer months [indiscernible] from school to school year.

Got it. That's very helpful. And then could you maybe talk about your rationale to transition your test prep customers to learning membership sort of understanding that the unit economics and sort of customer LTVs of memberships are more attractive. Just maybe talk about why it may make sense to -- for Test Prep product sort of given that those are less recurring by nature?

Sure. Yep. Happy to answer that. So the way we approach transitioning all of the audiences so far was by methodically AB testing the different audience segments to understand better conversion and then unit level economics associated with the old and new model. And then once we had confidence that it was trending to stat sig, we would then kind of flip over to the new model that we believe was the superior economic model and also one that we think serves as a great platform for innovation that we've seen actually delights our customers a lot more. So in the case of Test Prep, where we've actually transitioned 100% of all new customers thus far this year to learning memberships. That's an area where we think that there's higher lifetime value, there's going to be higher gross margin, there's going to be happier customers, we can continue to add more value to the actual subscription itself and enhance it over time. And then there's operational efficiencies that come with getting a higher proportion of the total consumer customer base over to one operating model so that you can simplify and streamline and become more efficient as well. So the rationale was simply kind of better across all fronts. But that's the bar that we'll hold ourselves to as we continue after the year with that remaining customers. So we have high confidence in the path to 100% subscription on consumer. And we already saw more than 50% of recognized revenue in this past quarter come from learning memberships, which is up from 18% in Q3 and 2% in Q2. So we feel really, really good about that, Maria.

Got it. Thank you so much for the color.

Thanks, Maria.

Thank you, Maria. We now have Andrew Boone with JMP Securities.

Hi, guys. Matt on for Andrew. Thanks for taking my question. Just understood your target for just EBITDA profitability in 2023. But with strong LTVs and now you're growing debt, just on retention of LTVs, is there an opportunity for you guys to lean more heavily into marketing spend? And just how are you thinking about this in 2023? Thanks.

Yeah, absolutely. Great question, by the way. One of the things that is a top goal around here for this year is becoming profitable. So we're doing everything we can to pull that forward. What we are seeing is great LTVs, especially relative to our old package model. If that continues and we fully expect that it will, we'll consider reinvesting some those dollars back into marketing in the back half of the year. But for now, we want to make sure that we can achieve profitability as quickly as possible.

Thank you. We now have Mario Lu of Barclays. Your line is now open.

Great. Thanks for taking the questions. The first one is on the full year revenue guide of 20% growth. I was just curious what was kind of the embedded percentage for institutional revenue for that full year number? And then, also, if there's any, like, change [indiscernible] plan dollars being deployed to Nerdy Services to kind of get to [indiscernible]. Thanks.

Hey, Mario. Thanks for the question. Yes, so embedded in the guide at the midpoint of 195 for the full year would be 15% of that total mix would be associated with the institutional business that represents about 50% growth year over year. So we're really excited about the opportunity for that business to delivered at a higher rate this year. And then when you think about funding sources within the institutional base and Chuck touched on this a little bit earlier, not only do you have the [American Rescue Plan] (ph) or SR3 funds, of which only 19% have been deployed as of October 2022 with the latest information we were able to garner. You've also got Title 1 funding, which is evergreen. And if you look at the most recent [indiscernible] budget passed about a quarter ago, it included $19 billion of Title 1 funding. And we expect that to continue to grow over time. And then lastly, I think the most important part is, because our solutions are embedded in the classroom workflow, and they support teachers, schools are using their own operating budgets to purchase these new exciting products. Especially, as it relates to Teacher Assign as a supplement to teachers in the classroom. Effectively, the way we think about it -- I think the way school districts are thinking about it is they get a co-teacher or someone that can be an extra set of hands for the teacher in the classroom during the school day so that those teachers don't have to stay beyond normal school hours, which we think and school district partners think will help drive future retention, which we think is just an added benefit.

Great. Thanks, Jason. And then just one on, the shareholder letter mentions, Nerdy is like the only company that currently combines live learning and AI technology. I know it's still early, but can you talk a bit about how large of an advantage this is, having this unique combination in terms of the client, both experts and learners?

Yeah. We're -- we outlined in this idea several years ago that we call AI for HI or artificial intelligence for human interaction. And the big idea here is that, in a world where instruction and expertise transfer occurs online that you can digitally enhance it and augment it in ways that simply are possible offline and give superpowers to both experts and learners in ways that are highly addictive. And so we think that that human element and the fact that we've focus on scaling relationships over time is highly defensible. And we'll continue to be able to lean into additional forms of personalization and add additional product value over the course of the next year. So one of the things that really excited about as it relates to generative AI is the ability to produce content at near zero cost that is highly relevant for what is occurring in that moment in time. But there's many, many honestly dozens of specific applications that we've already thought of and we're just trying to prioritize the most important approach just to make sure that they ultimately manifest themselves and think that customers value or that kind of add to retention and NPS and other things that would be a signal of great progress there. So one of the things that we've done though that I think really important is that, we've instrumented the business in a way that allows for us to take advantage of the fact that there's vertically integrated marketplace model where we can see exactly what's happening on both sides of the network. So if you think about what's maybe even different about this model than other marketplace model that might exist is, the learning actually occurs on the platform. So both the live tutoring itself and recorded video sessions, as well as then all of the learning as it relates to diagnostic testing and progress over time. And we are actually capturing all of that information and storing it and then we're able to leverage it in ways that enhance personalization as we find application. So we feel like we're well suited to run our head here and we plan to be aggressive on leveraging some of these new advances in AI to add value to customers much like we have in the past.

Great. Thanks, Jeff.

Thank you. That does conclude our Q&A session and conference call. So please have a lovely day, and you may now disconnect your lines.