eGain Corp (EGAN) 2026 Q2 法說會逐字稿

Good day, and welcome to the eGain Fiscal 2026 second-quarter financial results conference call. (Operator Instructions)

Please note, this event is being recorded. I would now like to turn the conference over to Jim Byers with Pondel Wilkinson, Investor Relations. Please go ahead.

Thank you, operator, and good afternoon, everyone. Welcome to eGain’s fiscal 2026 second-quarter financial results conference call. On the call today are eGain’s Chief Executive Officer, Ashu Roy; and Chief Financial Officer, Eric Smit.

Before we begin, I would like to remind everyone that during this conference call, management will make certain forward-looking statements which convey management’s expectations, beliefs, plans, and objectives regarding future financial and operational performance. Forward-looking statements are generally preceded by words such as believe, plan, intend, expect, anticipate, or similar expressions. Forward-looking statements are protected by safe harbor provisions contained in the Private Securities Litigation Reform Act of 1995.

These forward-looking statements are subject to a wide range of risks and uncertainties that could cause actual results to differ in material respects. Information on various factors that could affect eGain’s results are detailed in the company’s reports filed with the Securities and Exchange Commission. eGain is making these statements as of today, February third, 2026, and assumes no obligation to publicly update or revise any of the forward-looking information in this conference call.

In addition to GAAP results, we will also discuss certain non-GAAP financial measures, such as non-GAAP operating income. The financial tables included with the earnings press release include reconciliation of the historical non-GAAP financial measures to the most directly comparable GAAP financial measures. eGain’s earnings press release can be found by clicking the press releases link on the Investor Relations page of the eGain website at egain.com. Along with the earnings release, we will post an updated investor presentation to the Investor Relations page of eGain’s website. And lastly, a phone replay of this conference call will be available for one week.

And now, with that said, I’d like to turn the call over to eGain’s CEO, Ashu Roy.

Thank you, Jim, and good afternoon, everyone. We saw good business momentum in our second quarter. Both revenue and profitability exceeded our guidance and street consensus, and we delivered strong operating cash flow. We also drove strong bookings in the quarter, including multiple Global 1000 logos and healthy expansions. Our AI Knowledge Hub momentum continues to grow, with ARR from these customers up 27% year-over-year, and our total AI knowledge ARR now representing 64% of our total SaaS ARR. Finally, we saw more than 50% year-over-year increase in top of the funnel AI knowledge leads. So that’s encouraging.

Turning to business highlights, we saw a couple of trends worth calling out. First, 25% of our new logos in the first half of fiscal 2026 were sourced by partners. This is more than a doubling of our partner-sourced new logos year-over-year. Our partner momentum is building nicely. We also saw enterprise buying bundled alongside the CX deals in a majority of cases in this quarter. This convergence of customer service and contact center buying and enterprise use case-oriented buying is accelerated by what we see as corporate AI teams and their interest in knowledge. This is a development that validates our point of view that a centralized, trusted knowledge foundation is necessary for AI ROI at scale.

Now, let me share some booking highlights for the quarter, starting with new logos. First, we won the enterprise knowledge mandate for one of the largest business software providers in the world. Our knowledge platform will be deployed across over 100,000 users and multiple use cases across CX, employee experience, and AI experience, which now is, as we know, a huge thing. This win also presents us the opportunity to partner with this client to potentially offer our knowledge solution to their global clients. Very exciting for us.

Another one worth calling out is a large US-based manufacturer of kitchen cabinets with over 15 brands and 6,000 employees. This company’s product and policy knowledge was scattered all over, and it was making it very hard for their service teams to access accurate, current answers for long-tail products. As you know, cabinets last for a long time, and service questions can be for products you sold 15 years ago. They selected our AI Knowledge Hub to centralize all the knowledge, drive consistency, and automate their future AI initiatives.

We also signed a couple of new insurance logos during the quarter, including Achmea. This is one of Europe’s largest insurance and financial services groups based in Netherlands. They serve more than 10 million customers. Achmea had been driving a strategic shift towards becoming a digital insurer, with customer experience and self-service adoption as their core priorities. They recognized the need for a knowledge-as-a-service partner, and they selected us to accelerate their digital insurance journey.

Our platform now will power 21,000 users across Achmea, including customer service and contact center use cases, but not just customer service. We are also seeing good momentum with credit unions. One of them that I want to call out is Oregon Community Credit Union. They serve over 250,000 members in Oregon, Idaho, and Washington.

They recognized the need to modernize their knowledge system, and they selected us, again, for our open architecture and AI capability. Yet again, in this case, eGain will be used to support all enterprise use cases, including contact center use cases, where we are integrated and connected into the Genesys CCaaS platform.

So this convergence that we see of starting with customer service and contact center, but then the knowledge platform being used for all enterprise use cases, is a welcome one for us because we believe that while CX is the most compelling ROI proposition for knowledge, knowledge is not limited in terms of its value within customer experience use cases alone. And so, applying what works in CX across the entire enterprise provides enormous benefit to businesses that are looking to accelerate their AI ambition.

In terms of thought leadership, we more than ever believe that the market is aligning with our view that a trusted knowledge foundation accelerates enterprise AI ROI. This quarter, as I mentioned earlier, we saw more than 50% year-over-year increase in top-of-the-funnel marketing leads and a 23% increase in pure inbound interest year-over-year.

Turning to partnerships, which is a key area for us, beyond our direct go-to-market motions. Our expanding efforts in partner development are bearing fruit. Partner-sourced leads in the first half of fiscal 2026 increased 80% year-over-year. On the product front, as we have mentioned before, we announced our developer-focused offering, the eGain Composer, in October at our customer event in Chicago. eGain Composer now is helping us drive more product sales of the AI Knowledge Hub and attract new ecosystem partners.

We are seeing growing engagement from developers, both from AI groups within enterprises as well as smaller partners who are building bespoke AI solutions for their clients, which are enterprises. As you know, Composer offers modular capabilities on our composable platform to easily build trusted solutions using our knowledge hub. While it’s early days, we see continued and growing interest from smaller partners as well, who want to use Composer to build differentiated capabilities in their own go-to-market offerings. As we execute more go-to-market programs around Composer, we intend to expand awareness among AI stakeholders, increase engagement, and generate early conversations across diverse use cases beyond customer experience and customer service.

I’m most excited about the fact that eGain was once again noted in the right top quadrant, the leader quadrant, in the Gartner’s Magic Quadrant for Generative AI Knowledge Apps. We were also, late last year, named KMWorld’s Leaders Choice Award winner, and this came out in November of 2025.

To conclude, we are executing well on our go-to-market strategies. We are seeing growing brand awareness as evidenced by increase in inbound interest in our products. We are seeing increased opportunities both in our go-to-market awareness and direct marketing activities, as well as partner activities. We are seeing our product-led growth strategy delivering tangible results. And lastly, we see the market converging, centered around CX and customer service, but extending beyond that to cover the entire enterprise for a centralized knowledge foundation that businesses are looking to create, which will then give them the right capability to springboard off for their AI initiatives.

With that, I’ll hand it over to Eric Smit, our CFO, to provide more detail on the financials. Eric?

Thanks, Ashu, and thanks, everyone, for joining us today. Before I begin, I want to mention that we are again using slides to support our earnings call. We believe this will provide helpful context and make it easier for you to follow our results and outlook. In addition to the webcast, you can find the slides in the Investor Relations section of our website under the Updated Investor Presentation.

As Ashu noted, we had strong business momentum in the quarter, with revenue and profitability exceeding our guidance and street consensus, strong year-over-year ARR growth, expanding gross and EBITDA margins, and strong cash flow from operations. Let me share more details about our Q2 financial results before discussing our outlook and guidance for Q3 and fiscal 2026.

Looking at our revenue, total revenue for the second quarter was $23 million, ahead of our guidance and street consensus, and up 3% year-over-year. SaaS revenue increased by 5% year-over-year and accounted for 95% of total revenue, up from 93% in Q2 last year. If we exclude the approximate $600,000 reduction per quarter from our non-core messaging products, which we are sunsetting this fiscal year, then total revenue was up 5% year-over-year, and SaaS revenue was up 8% year-over-year.

Looking at our non-GAAP gross profits and gross margins, total gross margin for the quarter was 74%, up 300 basis points from 71% a year ago. So our SaaS gross margin for the quarter was 80%, up 200 basis points from 78% a year ago. The SaaS gross margin expansion was primarily driven by our product enhancements, which enabled more cost-efficient deployments and delivered operational efficiencies within our cloud and customer support teams.

PS revenue was sequentially lower in Q2, as anticipated, due to the timing of bookings that didn’t close until late in the quarter, as well as the impact of the government shutdown. This contributed to the negative PS margin in Q2. We have right-sized and adjusted our PS organization during Q2, and we’ll see the full quarter savings benefit in Q3 onwards. As such, we expect PS gross margins to return to flat to slightly positive, as we saw in Q1.

Now turning to our operations. Non-GAAP operating costs for the second quarter were $14.2 million, down 3% year-over-year, as we have streamlined and realigned our business operations, increasing our investments in AI product innovation while reducing spend on legacy products. Looking at our bottom line, non-GAAP net income was $3 million or $0.11 per share on a basic and diluted basis, up from $1.3 million or $0.05 per share on a basic basis and $0.04 per share on a diluted basis in the year-ago quarter. Adjusted EBITDA margin for the quarter was 14%, up from 7% in the year-ago quarter.

Turning to our balance sheet and cash flows. For the second quarter, we generated strong operating cash flow of $10.1 million, representing a 44% operating cash flow margin, compared to $6.4 million at 29% operating cash flow margin in the year-ago quarter. Our cash collections have historically been front-loaded in the fiscal year due to the timing of large deals and renewals.

Our balance sheet remains very strong and with a healthy level of cash and no debt. Total cash and cash equivalents at the end of the quarter were $83.1 million, up from $62.9 million as of June 30, 2025. During the quarter, the company did not repurchase any shares of common stock, and as of the end of Q2, we still have $19.7 million remaining available under the company’s current authorized buyback program.

Now turning to our customer metrics. I’ve broken out our AI knowledge ARR metrics from the total metrics to highlight the momentum of our AI knowledge business. SaaS ARR for AI knowledge customers increased 27% year-over-year, while SaaS ARR for all of our customers increased 7% year-over-year. Excluding the non-core messaging products, which we are sunsetting this fiscal year, SaaS ARR for all customers increased 11% year-over-year. Turning to our net retention rates, LTM dollar-based SaaS net retention for AI knowledge customers was 116%, up from 99% a year ago, while net retention for all customers was 101%, up from 89% a year ago. Our LTM dollar-based SaaS net expansion rate was 119% for our AI knowledge customers and 108% for all customers.

Looking at our remaining performance obligations, total RPO increased 15% year-over-year, and our short-term RPO of $53 million was up 4% year-over-year. Now, turning to our guidance. For the third quarter of fiscal 2026, we expect total revenue of between $22.2 to $22.7 million. And as a reminder, the fewer number of days in Q3 has an approximately $400,000 negative impact on revenue for the quarter being compared to Q2.

Turning to the bottom line for Q3, we expect GAAP net income of $1 million to $1.5 million, or $0.04 to $0.05 per share, which includes stock-based compensation expense of approximately $800,000. We expect non-GAAP net income of $1.8 to $2.3 million, or $0.06-$0.08 per share, and adjusted EBITDA of $2.6 to $3.1 million, or a margin of 12% to 14%. Looking at our full year ending June 30, 2026, we expect total revenue to be between $90.5 million and $92 million, representing a return to growth for the year. This remains unchanged from our initial guidance provided last quarter.

We now expect GAAP net income of $4.5 million to $6 million, or $0.16 to $0.21 per share. This includes stock-based compensation expense of approximately $2.9 million, also includes warrant expense of approximately $1.4 million. Our non-GAAP net income of $8.8 million to $10.3 million, or $0.31-$0.36 per share, and adjusted EBITDA of $10.9 million to $12.4 million, or a margin of 12% to 13%. Looking at weighted average shares outstanding, we now expect approximately 28.3 million shares for Q3 and 28 million for fiscal 2026.

So in conclusion, we delivered revenue and profitability that exceeded our guidance. Our AI knowledge ARR growth continues to gain momentum, increasing 27% this quarter and now accounts for 64% of total SaaS ARR. We’re executing well on our go-to-market strategies and seeing positive results, and we are well positioned to capture market leadership in AI-driven knowledge automation and to drive sustainable revenue growth and increased profitability going forward.

Lastly, on the investor relations calendar, tomorrow we will be hosting virtual meetings with institutional investors throughout the day as part of the Oppenheimer Emerging Growth Conference. We hope to see some of you virtually. And next month, we will be at the annual Roth Conference on March 23. We’ll provide more details as we get closer to the date and hope to see some of you there in person. This concludes our prepared remarks.

Operator, we’ll now open the call for questions.

(Operator Instructions)

Jeff Van Rhee, Craig-Hallum

A couple questions for me. First, congrats on the large software deal, and I’d love to hear a bit more about that deal, the cycle, the competitive landscape, what you were replacing.

Sure. This is Ashu here, Jeff. Yeah. So, let’s go in order. So the first thing was, it was a fairly long sales cycle. We’ve been at it for, I would say, seriously, for about a year and a half, but we’ve been talking to them maybe a few months before that. Went through the whole RFP process, and eventually they selected us, so that was one.

The second was, in terms of what we were replacing, they didn’t have an enterprise-wide knowledge platform up until then, but they did have other competitors for AI search in some of their dysfunctional groups. But they didn’t have an enterprise-wide knowledge solution up until then.

And then, Eric, just on the numbers front, just so I’m thinking about this right, the March quarter versus the December quarter, is a clean, sequential compare. We’ve had the full run here of the large JPMorgan deal, and then if I recall, the messaging was gonna sunset in tranches, and I think you had said that was Q1 2027. Just trying to validate if I’ve got all that right.

Yes, that’s correct. Just to be clear, on the non-core messaging, we had 50% of it reduced in the Q2 quarter, and then the balance will be reducing in the first quarter of '27.

All right, got it. And then on the partner side, I mean, obviously having some real good impact. Can you just narrow that down? Is that concentrated within a small basket, or are there any particular partners that are driving the strength on the partner-driven lead gen?

Yeah, the ones that seem to be working, two areas that seem to be quite promising. One is small boutique kind of knowledge consulting shops, which have existing clients, and they are looking to kind of refresh the platform for the clients, and some of the legacy knowledge vendors who these boutique SI shops have worked with. So that’s one area where we are seeing good momentum. And the second area we’re seeing some early but very promising momentum is just pure contact center knowledge deals through sort of the TSD kind of networks.

Yes, got it. Okay, great, I'll leave it there and congrats on the cash flow, guys. Great cash flow there.

Richard Baldry, Roth Capital.

Sort of an esoteric question, but there seems to be a fable developing that people can use AI and sort of instantly create software companies. So could you talk a little bit about the challenges to replicating a system of record class software platform that -- a vibe coding session clearly couldn’t replicate? So you’ve been building this for a decade plus. But I’d like to just put a pin in that myth, sort of one company at a time. So if you can talk about sort of the barriers to -- and the moats around what you’ve built. I think that’d be helpful.

Yeah, that’s a tough one, Richard, but I’ll try to take a crack at it because the fact is that you’re right. Basic programming and even complex programming, given appropriate constraints and very good jumping and kind of coding, if you will. Now with very good programmers -- human programmers on the other side, is accelerating the phase of software creation, which we typically call coding and development, right? So that part is definitely true, and we are taking advantage of it just as anyone else is.

The parts that I think are still seem more work, though I wouldn’t ever say that it’s not solvable because the trajectory seems to be quite interesting, is architecture, understanding of use cases, understanding things that are non-functional in nature in terms of reliability, scalability, performance, and so on, and then putting it all together. But what I’m trying to say is, I think the barriers are definitely coming down for everyone, right? Whether it’s a one-person shop or whether it’s a 500-person shop like eGain, or it’s a 300,000-person shop like Google. And the focus and the use case understanding and the ability to put things together that have proven track record are going to be the differentiators, really.

And then think about internally then, how much do you think you can use the tools internally to either speed up your own feature development and/or lower your cost to deliver the service? And maybe a broader way to think about it is, in a pre-generative AI world, do you think your profitability would be higher, or is it higher in a post world because you can lower some of your internal costs?

I think assuming that pricing holds, we would definitely be more profitable, right? But I do suspect that there’s going to be pressure on pricing over time for all of us, not just eGain. Everyone is gonna feel the pricing pressure. And so I feel like there is a big opportunity to become the enterprise knowledge fabric. Yes, we’re starting from the vantage point of customer service and customer experience, but as I mentioned, you know, a big majority of our deals now are starting in CX, and in the first purchase itself, they end up including enterprise use case.

So I think that it’s a land grab, really, at this point. And so we are focused on this knowledge piece, and we hope to grab more land than others and then play the game as well as anyone else from there on.

Got it. And maybe last for me, the cash piles are building up pretty fast. Any thoughts on the best way to efficiently deploy that in the current environment?

Well, I think, as we said before, I think we will keep focusing on our internal investments to drive the top-line growth. I think we’ll continue to -- on that momentum, I think we’re obviously benefiting from the AI innovations that are sort of helping us save some of those money, even as we’re spending it on R&D and ramping up the teams here in Sunnyvale. I think some of those cost savings are resulting in those improved, profits in the short term, but I think we certainly continue to see that as a primary focus.

We obviously still have the share buyback in place, so we’ll see, whether that’s an appropriate vehicle. And then finally, you know, opportunistically looking at inorganic options. Again, this is not something that’s a primary focus, but of course, we will continue to evaluate those as they come in, as we look forward.

Maybe one last one for me. How are you thinking about hiring plans? You’re sort of midway through the year executing against the plan. When you look forward, whether that’s pipeline-driven, opportunity-driven, do you think hiring will be concentrated in sales and marketing? Do you think there’s a flat period for something like development while you adopt the new tools that are getting you higher throughputs there? And how do we think about that as you head into the second half?

So we’ve been, as Eric mentioned, which we’ve been investing pretty smartly and actively in hiring new talent in product over the last year, right, in locally in the Bay Area. And that has proven -- that’s one fruit. We’re very happy with that. Now, at the same time, we’ve been reducing from some of the other sort of distributed teams that we had. Thanks to automation that we are driving in the business.

So the net impact doesn’t seem like much is happening, but there’s a lot of reallocation going into much more high-end engineering and technology talent on the product side, both in product management as well as, as engineering and architecture and AI. Then moving to marketing, we brought in a new marketing head.

He’s brought in a couple of new people now, and I think marketing is gonna see a lot of increased activity and investment for us in the second half of this fiscal year, right? And then finally, sales, which while we are very happy with the pipeline, I still think that given the way we are product-led now, our sales motions are kind of different. They’re much more expert-led much more specialist-led especially in large organizations, where there’s very early contact with tech and AI folks.

And so the composer proposition is resonating very well, and we are investing in that group, right? So that’s kind of where we are now. As it scales, which I believe it will, then we will add more sort of systematic sales muscle and headcount to meet the demand.

Erik Suppiger, B. Riley Securities.

Yeah, thanks for taking the question, and congrats on a real solid quarter there. One, I just want to be clear, is the deployment at JPMorgan, is that fully rolled out, or is that still in process? Then two, you’d talked about some additional areas for opportunities across the enterprise. Can you discuss what are some of the logical kind of low-hanging fruit once you move past CX?

Sure. So first, on the JPMC question, we are not fully rolled out as planned. We are halfway there, and we expect to be fully rolled out later this year as planned. So that’s good. The second question in terms of other use cases, we are working on a few, Eric. I think, maybe this is a good time for me to mention that we pulled up our Europe-based customer event, which normally we would do in June. Now we’re doing it in May this year, and so we’ll have our eGain Solve customer event in London on May 6 and 7. And those are the two events, one in Chicago, one in London, where we bring out our new products and capabilities.

And so, I’d say we look forward to sharing more in that forum as to what are the other use cases we are looking to roll out. But you can logically think of the other use cases. But to me, the first expansion is gonna be concentric around broadly customer operations as opposed to just customer service and from there on, into other enterprise-facing areas.

Okay. And then, just in terms of some of the wins that you had, are most of those greenfield wins, or are you displacing anybody’s solutions?

I would say that in more cases than not, we are replacing some tactical solution or some big solution that has just run out of gas in terms of new innovation or AI readiness. That’s one of the things we are seeing a lot of is existing CRM solutions in CX areas that just don’t seem to be investing in modernizing and making it AI ready, if you will. And our knowledge automation capabilities are -- and composer capability. These two things are super attractive to businesses that are looking to drive sort of the AI projects with trusted content feeding into those systems. That seems to be one of the big trigger points.

Are customers using CRM platforms for that, and they’re finding that they’re insufficient? Or what is it that they’re trying to use for that?

Say there’s three things, right? One is, they just have a whole bunch of SharePoint, and they have tried RAG, kind of retrieval augmented generation, on top of lots of SharePoint repositories to try to deliver the right content to AI systems on the front end. And they just run out of gas trying to make it work. That’s one. I’m giving you some archetypes here.

So the second is, they have knowledge sitting in Salesforce, and they just run out of patience waiting for Salesforce to deliver to what the commitments have been. Let’s just say that. And the third is, they have tactical or point knowledge management solutions that have not kept pace with the AI expectations that these businesses have. Those are the three, I’d say, most popular ones.

Since there are no more questions, this concludes the question and answer session. I would like to turn the conference back over to management for any closing remarks. Please go ahead.

Well, thanks, everyone, for taking the time today. We look forward to providing you the update when we do our Q3 results. Thanks.

The conference is now concluded. Thank you for attending today’s presentation. You may now disconnect.