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Nextdoor (NYSE: KIND) delivered a robust Q1 2026, marked by record Platform Weekly Active Users (WAU) of 22.3 million and a 14% year-over-year revenue increase to $62 million. Outperforming its guidance, the company achieved near-breakeven adjusted EBITDA, a $9 million year-over-year improvement. This financial progress was driven by a 28% growth in the self-serve channel and significant gains in revenue per employee. CEO Nirav Tolia emphasized the company's unique position in an AI-driven landscape, leveraging its 110 million verified users to provide human-verified local context that synthetic AI cannot replicate. The Ask feature, which utilizes AI to surface insights from 15 years of neighborhood conversations, is a central part of this strategy. Management also highlighted the success of Opportunity Alerts as a high-intent monetization pathway for local service providers. For the remainder of 2026, Nextdoor raised its guidance, forecasting 10% revenue growth and high-single-digit adjusted EBITDA margins. The company remains financially disciplined, with $373 million in cash and a newly authorized $100 million share repurchase program. Despite potential short-term WAU volatility, management is confident that its focus on content relevance and AI integration will drive long-term shareholder value.

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Nextdoor Holdings: Buying Back the Burn with SPAC Legal Ghosts

Full Earnings Call Transcript — Q1 • 2026-05-06

Operator: Good afternoon. My name is Jasmine, and I will be your conference operator today. At this time, I would like to welcome everyone to Nextdoor's First Quarter 2026Earnings Conference Call. [Operator Instructions] You may now begin your conference.
Indrajit Ponnambalam: Thank you, operator. Good afternoon, everyone, and welcome to Nextdoor's First Quarter 2026 Earnings Conference Call and Webcast. I'm Indrajit Ponnambalam, Nextdoor's Chief Financial Officer. With me today is Nirav Tolia, our Co-Founder, Chief Executive Officer, President and Chairperson of the Board. During this call, we may make statements related to our business that are forward-looking statements under federal securities laws. These statements are not guarantees of future performance. They are subject to a variety of risks and uncertainties. Our actual results could differ materially from expectations reflected in any forward-looking statements. For a discussion of the material risks and other important factors that could affect our actual results, please refer to our SEC filings available on the SEC's website and in the Investor Relations section of our website as well as the risks and other important factors discussed in today's earnings release. Additionally, non-GAAP financial measures will be discussed on today's conference call. A reconciliation of these measures to their most directly comparable GAAP financial measures can be found in the Q1 2026 Nextdoor investor update released today. And now I'll turn it over to Nirav.
Nirav Tolia: Thank you, Indrajit, and good afternoon, everyone. I'm pleased to report that Q1 was a standout quarter for Nextdoor. Platform weekly active users reached an all-time high, revenue grew 14% year-over-year, and we delivered meaningful improvements in profitability. Here are the highlights. Platform WAU reached 22.3 million, marking our first positive inflection point in several quarters. Revenue was $62 million, up 14% year-over-year. And adjusted EBITDA was nearly breakeven, a $9 million improvement year-over-year. These results represent a real step change in the business. And what's especially encouraging is the momentum we built as the quarter progressed. In our last earnings call, we laid out the 5 key drivers of our investment thesis. In Q1, we delivered material progress across each of them. Let me walk through that progress focusing on the first 3, and we start, as always, with our unique core asset. Nextdoor is built on a verified address-based neighborhood graph spanning 350,000 neighborhoods, [indiscernible] 110 million verified neighbors, roughly 1 in 3 U.S. households. This quarter, we continued to strengthen the integrity of that graph by expanding verification for both neighbors and local businesses. That's what keeps Nextdoor real and what makes every recommendation alert and conversation on the platform meaningful. Next is high intent engagement, where we are revitalizing the core community experience. We introduced threaded conversations, pinned comments and smarter linking. We added richer media in the feed and improved performance through latency and infrastructure work. And for the first time, we began down ranking self-promotional content. At the same time, Nextdoor continues to show up when it matters most. As we saw again this quarter, engagement increases during severe weather events and moments of local need. During the winter storms, neighbors turned to our platform for real-time updates on road closures, power outages and which local businesses were still open. This was yet another example of how our product can serve as an essential lifeline for communities. Our third driver is monetization pathways, and Q1 was an important proof point. We entered the year with a clear thesis. Closing the monetization gap does not require a step change in user growth. It requires better matching of intent to outcomes. And in Q1, we saw that working across multiple surfaces. For example, local service providers reaching neighbors at the moment they're actively asking for recommendations and seeing strong engagement and conversion as a result. I will leave it to Indrajit to cover the fourth and fifth drivers, our validated business model and founder's mentality. But as we look towards Q2, we will stay focused on continuing the momentum. Our priorities include improving content relevance, deepening engagement, expanding recommendations, strengthening distribution and advancing our AI and machine learning capabilities. Speaking of AI, I would like to close with why I'm more confident than ever in Nextdoor's position in an AI-driven world. As machine-generated content increases, truly verified human content becomes more scarce and more valuable. We've spent 15 years building a network of over 110 million verified neighbors across 350,000 neighborhoods. That network generates first-party content that is continuously refreshed, rooted in real identity and grounded in local context. That foundation puts us in a uniquely strong position. AI allows us to unlock significantly more value from that network by making it easier to find relevant information, summarize conversations and connect neighbors to the people and insights that matter most in their local community. But what truly differentiates Nextdoor is the connection to the people behind that information. The neighbor who knows the best contractor, the parent a year ahead of you making the same school decision, the local business that others genuinely trust. That's also what powers our recommendations experience. When a neighbor asks for a plumber or a babysitter, they're not just getting a list, they're getting trusted input from people nearby who've actually made that choice. AI can make these connections faster, more relevant and more accessible, but it cannot replace the trust and context that comes from real neighbors. And that combination, AI-powered discovery built on a foundation of verified local identity is what gives us confidence in Nextdoor's position in the years ahead. With that, I'll hand it over to Indrajit to walk through the quarter in more detail and discuss our outlook.
Indrajit Ponnambalam: Thanks, Nirav. As Nirav described, Q1 was a strong quarter that reinforced the progress we are making across the business. Let me walk you through the details. Q1 Platform weekly active users, or WAU, which measures users who engage directly on the Nextdoor app or website was 22.3 million. This represents a meaningful sequential increase from 21 million in Q4, reversing the prior sequential trend and hitting an all-time high for Nextdoor. Year-over-year Platform WAU was up slightly from Q1 2025 to 22 million. This sequential improvement reflects the compounding impact of the product investments we've made over the past several quarters, more relevant content, smarter notifications and an overall better user experience. As I've said before, Platform WAU is a lagging indicator of the product investments we're making. We are encouraged by the sequential improvement, although we continue to expect short-term fluctuations in WAU in the coming quarters. Turning now to revenue. Q1 revenue was $62 million, up 14% year-over-year. This represents a significant acceleration from Q4's 7% year-over-year growth and finished well ahead of our guidance range of $57 million to $59 million. Q1 is historically our softest quarter for advertising demand, which makes this performance especially encouraging. Revenue growth was broad-based. Our self-serve channel continues to be a growth engine, growing 28% year-on-year and now comprising roughly 68% of total revenue, with continued improvement in advertiser performance, revenue yields and retention. Every major monetization channel contributed to growth this quarter from small local advertisers to large national brands. Our ad stack improvements, including AI-assisted targeting and optimization and new ad formats are delivering measurable results for advertisers of all sizes, increasing eCPMs while reducing lower quality backfill. Outside the U.S., we also expanded self-serve into Canada and brought click optimization to the U.K., our first ML-powered performance product in that market, delivering meaningful CPC reductions in our beta period. Q1 GAAP net loss was $11 million or a negative 19% margin, representing 22 points of year-over-year margin improvement. Q1 adjusted EBITDA was near breakeven at negative $200,000. This compares to the negative $4 million to $6 million we guided to last quarter and represents an approximately $9 million improvement year-over-year. Even in our seasonally softest quarter, we achieved near breakeven adjusted EBITDA, a meaningful milestone that underscores the operating leverage in our model. We continue to drive productivity improvements across the organization. Revenue per employee increased 31% year-over-year in Q1, building on the gains we've driven over the past 2 years. Turning to capital allocation. During Q1, we repurchased 17 million shares for $29 million at an average price of $1.69 per share. We ended Q1 with $373 million in cash, cash equivalents and marketable securities, and we continue to have no debt on our balance sheet. Today, we are also announcing that we have authorized a new $100 million share repurchase program effective through June 2028. This gives us the flexibility to act opportunistically while preserving our ability to invest in growth and pursue strategic opportunities. As Nirav outlined, these financial results reflect drivers 4 and 5 of our investment thesis in action. A business model validated through the improved operating leverage in our financial results and the discipline around trade-offs that aligns network health with maximizing long-term shareholder value. Now let me turn to our financial outlook. Given the momentum we are seeing, we are providing guidance for both Q2 and updating our full year 2026 outlook. For Q2 2026, we expect revenue of $71 million to $73 million and adjusted EBITDA of $4 million to $6 million. Based on our strong start to the year, we are raising our full year expectations. We now expect to achieve approximately 10% revenue growth for the full year and an adjusted EBITDA margin in the high-single-digit range, up from the mid-single-digit margin guidance I provided in our last earnings call. This reflects our expected revenue trajectory, continued operating discipline and expanding leverage we are seeing across the business. Now let's turn to some Q&A, which we will structure in a similar manner to last quarter. We'll start by taking live questions from our covering analysts. After that, we will take some questions submitted by our investors. With that, operator, let's open the line for questions.
Operator: [Operator Instructions] Our first question comes from Jason Kreyer with Craig-Hallum.
Jason Kreyer: Great. Nice work. Wanted to start on the Platform WAU and maybe if you can just unpack the turnaround there. I'm curious the strategy, how the strategy evolves to take 100 million users that are on the platform and get more of those into that 20 million WAU and grow the more engaged audience over time?
Nirav Tolia: Okay. Thank you for that question. And this is really kind of our primary objective at Nextdoor, which is making the most of not just our total registered audience of now over 110 million verified users but also attracting new users. Now what I'll say is much of the work that we've done over the last 2 years, has been on, I'd say, repairing the foundation and putting ourselves in a position where we can reduce the things that we know may use short-term engagement but don't lead to positive NPS over time. And so you may have seen some things that made WAU go down. You may still see some things that make WAU go down. Over time, though, we're pretty confident that we're building a better foundation, not just for our existing users but to then enable us to resuscitate the lapsed users because there's a pretty big gap between 22 million and 110 million registered and then ultimately to attract new users to the platform as well. I will mention that we have not been aggressive about trying to remarket to the lapsed users because we don't believe that the product is in a position yet where we're playing from a position of strength. But I'm delighted to say that we're seeing some results now that tell us that we're headed in the right direction. And that's why WAU trended up, and we feel really good about that.
Jason Kreyer: Can you perhaps just double-click on kind of the platform and what's not where you want it, but what it takes to get where you want it, so you're more aggressive on that WAU growth?
Nirav Tolia: Sure. It's actually pretty simple. We boiled it down to kind of one very critical user need. And that is when our neighbors come to Nextdoor, they want relevant content. And so if you're in a neighborhood that's not very active, it's hard for us to show you relevant content. If you're in a neighborhood where the discussion is varying off topic, you're not going to necessarily get relevant content. If you're in a neighborhood who hasn't visited in a long time and we don't have very good no model for you, we can't show you relevant content because we don't know exactly what you're looking for. Those are all things that we're addressing. We're up-leveling the quality of content overall so that everyone has an opportunity to see more relevant content. We're focusing on neighborhoods that have less liquidity so that when those neighbors visit the platform, they find great content. And we're investing a ton in machine learning and profiling our neighbors in a way that we can personalize the experience and find the content that they're looking for. But it really all comes back to one very simple thing, which is the more content we have, the better we can be at targeting that content and making it relevant to our users. And so most of our efforts are around increasing the quality of content on Nextdoor. And we need to increase quantity as well, but we're taking a quality-first view there.
Jason Kreyer: That was great. Nirav, one follow-up maybe. Just you'd mentioned that momentum had built as the quarter progressed. Can you just elaborate on what transpired over the course of the quarter that improved that performance?
Nirav Tolia: Yes. I'll give you something that we didn't talk about in the results that I think is a leading indicator that makes us very optimistic that we're headed in the right direction. And it's something that we wouldn't typically report because it's an early thing that then leads to lots of chain reactions on the platform. But that metric is we grew the number of unique contributors over this period of time. And what that means is we grew the number of people who are adding content to the system on Nextdoor. We have a base of really great high-frequency users who create a lot of the content. In fact, if you look at most of these user-generated content platforms, 1% of the users create 99% of the content. The same is going to be true of Nextdoor. But if we can grow that base, then we start to see lots of really positive effects. And in this period, we were able to grow that contributor base that resulted in more content, which resulted in more reasons for people to visit Nextdoor, more relevant content when they visit Nextdoor and all good things start to happen on the platform. And so one of the things that we've done over the last 2 years is we've gone pretty deep to understand the core aspects of the foundation of the system, so we can go and fix root causes versus just deal with a superficial layer on top. WAU in and of itself, it's actually an output metric. It's not an input metric. An input metric is how many unique contributors do you have. And when we see that number growing, we have a lot of conviction that we're headed in the right direction.
Operator: Our next question comes from Jamesmichael Sherman-Lewis with Citi.
Jamesmichael Sherman-Lewis: Great to see the result. First, Nirav, revisiting your closing commentary on AI and Nextdoor trusted human content, could you talk more broadly about how you see the Nextdoor evolving, particularly following the introduction of features like threaded conversation and pinned comments but also as you onboard more publishers and reduce self-promoted content? What's changing?
Nirav Tolia: Yes, that's a great question. And I'll just elaborate a little bit on the closing about AI because I've never actually been more bullish on the AI future for our industry and I've also never been more bullish on our opportunity to be a big part of that. Because I truly believe we're one of the few companies that can use the power of AI, which is furnishing machines and technology, but combine it with verified human content, data and profiles to really create kind of the best of both to take the best of technology and the best of humanism and provide the best solution for users as a result. The feed itself will continue to be more personalized. So how do you use AI and really machine learning in a feed? You don't want the same experience for every user on Nextdoor. The users who really want news, they should see a lot of news. The users who actually want a lot of neighborhood conversation, they should see a lot of neighborhood conversation. The history of Nextdoor has been that everyone in the neighborhood saw exactly the same feed. Well, that is no longer the case, and we see much better outcomes using AI to personalize the feeds. That's number one. Number two, we will increasingly be experimenting with summarizing the feed by using AI so that you can get the value of reading lots of threads in a smaller little concise nugget. Now you see this all over the web, right? And so we should be doing this on Nextdoor as well. We need to make sure that we do it in the right way so that contributions and the ability to reply to these threads continues to happen. But we're seeing, I think, some encouraging different results and experiments that we're doing that give us the conviction that we can use AI in one of the most powerful ways that you can use it, which is to summarize and make more useful existing user-generated content. The final thing I'll say is we're starting to think a little bit more deeply about are there services other than the feed that can be really valuable on Nextdoor, whether that's your messaging inbox or whether that's another surface altogether such as groups or for sale and free. And we're very, very early, and that's just exploratory. But what we're realizing is we have more than the feed as a resource on Nextdoor. We have multiple surfaces and we can use AI across all of those services, and we're doing the same thing. We are taking the best of AI technology, which summarizes and make things more personalized and make things more relevant, and we're combining that technology with verified human content that's proprietary that we generate from people that we know well. And we think that's long term and unbeatable combination.
Jamesmichael Sherman-Lewis: That's very helpful. I appreciate the color. Second question here. On your pillar for multiple monetization pathways, I realize we're very early days here, but things like opportunity alerts or maybe even a subscription offering could be interesting. Is there ultimately a meaningful non-ad revenue opportunity in the future?
Nirav Tolia: Yes. I'm glad you asked that question because opportunity alerts has definitely been a big bright spot for us. And we are increasingly thinking about not just investing in the feed advertising revenue stream because that's growing. As you see, it's very vibrant, and we're performing for our advertisers. But we do believe that whether it's lead gen or things that we haven't even thought of, there are non-ads, nonfeed revenue opportunities inside Nextdoor. Opportunity Alerts is one of the first, and it's something that is very powerful because it has strong product market fit. Opportunity Alerts works because neighbors come to Nextdoor looking for service providers, and we can go proactively to service providers and tell them that we will connect them or match-make them between the neighbors and the service providers that want to serve those neighbors based on expressed intent. And so it's really good for neighbors. It's really good for the service providers, and it performs. And we see that both in the pricing as well as the retention. And so it's still early for Opportunity Alerts, but it is certainly one of the more exciting monetization vehicles that we've seen over the last couple of months.
Operator: Our next question comes from Naved Khan with B. Riley Securities.
Ryan James Powell: This is Ryan Powell on for Naved. So first, we are wondering which of the new features you have launched or resonating most with users and how it's impacting the product pipeline? And then second, breaking down advertiser growth between large versus small advertisers on the platform?
Nirav Tolia: Okay. Thank you for the question. I'll take the first and then Indrajit will take the second. We have a number of questions that were submitted by our investors. And so I'm going to come back to this in a little bit more detail, but I'll just start by saying that one of the features that our users are really excited about and I'm most excited about is a feature called Ask, which utilizes AI to take existing content from the 14 or 15 years of conversations that we have between neighbors, between verified human neighbors on our platform and uses that information to proactively answer questions either on demand in an agentic way or when neighbors come to Nextdoor and just post in the feed. And so I'll talk more about that because the question was asked by one of our investors as well. And so give us a little bit of patience on that, they are much a much more elaborate answer, but that is a feature called Ask. And I'll just say that the really exciting thing about the feature is that it has given us many new ideas on how to deploy AI into the consumer experience. And so while you hear a lot about AI transforming companies operationally, making them more efficient, making them more effective in the way that they do their workflows, we're doing that at Nextdoor, but we're also using AI inside the product itself. And that's what's really exciting about Ask because it's one of the first features we've seen where we can combine the power of AI with the user-generated content that has been our bread and butter for the last 15 years and create a better experience for users. I'll let Indrajit talk about the composition of advertisers.
Indrajit Ponnambalam: Yes. So it was a very good quarter on revenue growth, as you saw a 14% growth, and it was pretty broad-based across all of our revenue channels. So that's very encouraging. I'd say our strongest growth is probably in our direct sales business with our larger advertisers. Home services continues to be a standout category for us, but we saw quite a bit of growth in other categories such as telco and tech, healthcare, financial services, all performed well, sort of broad-based portfolio strength. We saw a big uptake in advertiser interest in our video products. So that's very encouraging year-over-year. And you saw in my comments that self-serve continues to sort of be a larger share of our ad revenue as it's not necessarily managed to shrinking, but self-serve is increasing that's showing sort of advertisers are interested there. SMB also grew and we saw strength across the board there, too. So home service being the strongest category. We saw meaningful increases in average spend per advertiser year-over-year, which is also encouraging for us. And then finally, search also, we sort of improved our monetization in search. So I would say it's a pretty broad-based solid quarter for us.
Operator: There are no questions registered. [Operator Instructions].
Indrajit Ponnambalam: Great. Thank you, operator -- all right, I'll jump in. Thank you, operator. As I mentioned, we are now pleased to answer some questions that investors have submitted to us in the last couple of weeks. So actually our first two questions come from Eric Jackson, one of our investors. So first question, can you share more about the traction you are seeing on local business inventory, including onboarding pace and retention and marginal contribution economics?
Nirav Tolia: Okay. I'm going to take that question. And I want to start by saying that we think of our opportunity with small and local businesses as a genuine win-win-win. And I'll explain what I mean by that. It's a win for local businesses because they largely lost their traditional advertising channels. There's no more Yellow Pages. The big platforms have largely left them behind. And so we can fill the gap there for them and give them a cost-effective and highly performant way for them to reach their customers. And this is a win for neighbors because neighbors genuinely want to find and support businesses that they can trust that are in their local area. And because of the way Nextdoor works, neighbors are recommending these businesses. They're vouching for them. And so it's a great match between well-performing businesses and neighbors who are looking to spend money where they live. Finally, it's a win for Nextdoor because this market reinforces our core mission of strengthening local communities, not to mention that it's structurally efficient to operate because it tends to be in the self-service category. On the specifics, I'll say that spend per advertiser is growing, which is a really positive signal. Churn is roughly in line with what you'd expect in this part of the market, but it's still higher than we'd like. And that's an area of continued focus. Now speaking of these structural events that I talked about, serving local businesses is a very efficient model for us. There's less overhead, better unit economics as we scale, and it's a key driver of the self-service growth that you've been seeing in our business. This really happened for a number of quarters now. We're still early, but the signal is positive, and this is an area that we're definitely leaning into.
Indrajit Ponnambalam: Let me go to our second question on AI features, what are the early engagement metrics? And how is that translating to monetization, if at all yet?
Nirav Tolia: Okay. I'm excited to talk about one of the features that I mentioned already Ask because I do believe that it opens up lots of different opportunities for us. So Ask is this exciting feature. And what's exciting about it, as I said, is the way that it's evolved because it says a lot about where we're headed. We launched it as an AI assisted. We actually called it phase. It was part of the new Nextdoor that we launched. Neighbors can ask questions and get answers generated from 14 years of verified neighbor conversations. It was a local agent. But it was real people from real neighborhood. It wasn't the open Internet. And so that local authenticity is something that we felt then and we understand today is absolutely true is something that just can't be replicated. As we watched how users engage with this gave us a new idea. Why wait for people to find the feature, which was outside of the feed and then ask a question? It turns out there are conversations happening in the feed every single day. Members aren't online at that particular moment to respond. So we've begun to embed Ask directly into those gaps. And here's the important part. We use the power of AI to summarize and surface real answers and they are real answers from that 14-year corpus. So it's neighbors answering neighbors. It's just happening asynchronously, all enabled by AI. The results have been very encouraged. Engagement's up, there are more comments, the quality of the conversation goes up, and there are more organic mentions of businesses. This has really given us a playbook for how we keep deploying AI across the product in ways that feel very native and differentiated to who we are. There was that mentioned about monetization. I just want to say monetization is not a near-term objective for Ask, driving engagement is. Because ultimately, when neighbors are actively asking for recommendations and getting real answers from their neighbors, that is exactly the high intent environment our advertisers value. And we will develop the commercial layer on top of that healthy foundation.
Indrajit Ponnambalam: Our third and final question came from a few investors. And the question is regarding your path to profitability and free cash flow is the past primarily revenue-led? Or are there structural cost reductions coming? So why don't I take this one as it's a great note to end our Q&A on. So first, just as a reminder, we are already operating cash flow and free cash flow positive on a trailing 12-month basis. So the path to growing free cash flow is really about compounding what's already a good start. Second, to address the question directly, we expect revenue to be the primary driver. Our business is beginning to demonstrate meaningful operating leverage, which means incremental revenue growth flows through to the bottom line at quite an attractive rate, which is encouraging. But that being said, we're not standing still either on the cost side. We will continue to leverage AI and many other technology advances to optimize how we operate, and we expect that discipline to be a consistent feature with how we run the business going forward. So with that, Nirav, I'm going to turn it over to you for closing remarks.
Nirav Tolia: Okay. Thank you, Indrajit. And I want to thank all of you for joining us today. This was a fun one because Q1 was the strongest first quarter in our company's history. Platform WAU inflected positively, reaching 22.3 million. Revenue grew 14% year-over-year, and adjusted EBITDA came in near breakeven in what is typically our seasonally softest quarter. Most importantly, as you heard from Indrajit, we're raising our full year outlook. And those are the numbers we think they tell a clear story. Now what gives me the most conviction is not just a quarter. It's the moment we're in. As AI makes the digital world more synthetic, the network that is real, local and human becomes more valuable. And that is Nextdoor. That is what we're here to build. We know there's still significant work ahead to fully realize our potential, and we're going to remain focused on executing with ambition and discipline. But I think you've seen today that the progress is undeniable. So we thank you for listening and for your support. We look forward to continuing to share the progress.
Operator: This concludes today's conference call. Thank you for your participation. You may now disconnect your lines.