eGain Corporation (NASDAQ:EGAN) Q3 2024 Earnings Call Transcript

eGain Corporation (NASDAQ:EGAN) Q3 2024 Earnings Call Transcript May 12, 2024

eGain Corporation isn’t one of the 30 most popular stocks among hedge funds at the end of the third quarter (see the details here).

Operator: Good afternoon, everyone. And welcome to the eGain Fiscal 2024 Third Quarter Conference Call. All participants will be in a listen-only mode. [Operator Instructions] After today’s presentation, there will be an opportunity to ask questions. [Operator Instructions] Please also note today’s event is being recorded. At this time, I’d like to turn the floor over to Jim Byers from MKR Investor Relations. Sir, please go ahead.

Jim Byers: Thank you, Operator, and good afternoon, everyone. Welcome to eGain’s fiscal 2024 third 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, and 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 report filed with the Securities and Exchange Commission. eGain is making these statements as of today, May 9, 2024, 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 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 Release’s link on the Investor Relations page of eGain’s website at egain.com. And along with the earnings release, we have also posted — we’ll 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.

Ashu Roy: Thank you, Jim, and good afternoon, everyone. We saw good momentum in new logo wins and business activity in the quarter, driven by our AI knowledge offering. A McKinsey report from last year talked about the potential of generative AI to revolutionize customer operations functions across the economy and talked about improving customer experience and agent productivity by using generative AI through digital self-service and enhancing agent skills. And it said that there was a potential to deliver $400 billion in savings annually for businesses who today collectively spend $1.5 trillion a year in customer service. I say this because with our latest AI knowledge offering, which is eGain AssistGPT, we are breaking down the technology barrier that prevented companies from delivering trusted answers for customer service at scale.

That barrier was the manual effort in creating and curating knowledge within a Hub that could serve as a single source of truth. As companies are looking to significantly reduce customer service cost, our comprehensive solution delivers on the promise of AI for them to reduce cost of customer service while boosting their customer experience. These are exciting times for us, right? So, looking at our business, we signed some new good knowledge customers in Q3. I’ll mention a few. The first one is the U.S. megabank, so one of the big four. We are starting with them in one of their fast-growing multibillion-dollar divisions. They’re looking to contain their costs as they’re grappling with customer and agent experience in a rapidly growing service group.

Right following that, we have more opportunities with this client in our pipeline and we are looking forward to becoming the platform for AI knowledge across the bank. It’s really exciting for us. megabank is something that we have been working with them for a couple of years now and I’ll talk to that opportunity a little more later on. The next one I want to bring out is a Fortune 100 mortgage financing enterprise in the U.S. We’re starting out with them by replacing an existing solution for conversational service for one of their business units. Over time, the intent is to enable an enterprise-wide capability that is contextual and compliant, available both to customers and employees. The next one I want to mention is a fast-growing U.S.-based property management company.

They see AI knowledge as a core capability to improve customer experience and empower their employees as they are driving growth in a $1 billion business. And the next one, and the last one I want to mention, is a leading manufacturer of high-end bicycles and related products. They’re replacing their current knowledge platform with eGain to deliver trusted answers to customers and agents. Looking at the market, our business activity in this market continues to improve and it improved in the quarter as well. In fact, over the last nine months of fiscal 2024, our new logo and RFP counts, both of them, grew by 50% year-over-year. This reflects the growing trust, sorry, the growing interest we are seeing in knowledge management as a foundation for effective AI use in customer service.

Now, the megabank I talked about that we won in the quarter is a case in point. For the past year and a half, they’ve been running multiple AI initiatives within their business, no surprise, and having run through their exploration and evaluation of AI in their context, they concluded that they needed a knowledge foundation to feed trusted content to their AI tools. In their case, as for most large enterprises, they like our composable architecture so they can plug in their LLMs whenever they are ready for prime time. Most of the new opportunities we are engaging with share this growing awareness of the complementarity of AI and knowledge to deliver trusted answers for customer service. As we all know, customer service is a business function where 80% answer accuracy is not good enough.

With a wrong or thoughtless answer delivered by uncontrolled AI tapping directly into uncurated content would easily result in a lawsuit, or worse yet, sustained brand compromise, a’ la Air Canada recently. Extending our product leadership in the AI knowledge market for customer service, we rolled out our AssistGPT solution in Q3 to help our clients automate knowledge creation and curation. In fact, earlier today on our well-intended marketing webinar, a European client of ours joined us to share their success story and lessons learned as we helped them slash their knowledge build effort by a factor of five and reduced, at the same time, the answer errors by improving quality by 6x using our solution. Our current market position gives us a unique vantage point in the AI knowledge innovation race and so we are taking full advantage of it to enrich our products faster and better, to orchestrate AI and experts to automate knowledge management, thereby driving down the cost of customer service with trusted answers.

To conclude, we see continued momentum in new logo wins and supporting pipeline activities, and as such, we are investing in R&D and marketing to capitalize on this disruptive opportunity. At the same time, we’re keeping a keen eye on costs and making sure that we’re putting all our wood behind this arrow to dominate the AI knowledge market for customer service. With that, I’ll ask Eric Smit, our Chief Financial Officer, to add more color around the financial operations. Eric?

Eric Smit: Thanks, Ashu, and thanks, everyone, for joining us today. Let me provide more details about the financial results for Q3 before discussing our outlook and guidance for Q4 of fiscal 2024. Starting with revenue, total revenue for Q3 was $22.4 million, down 3% year-over-year. Contribution from our Cisco OEM business in the quarter was lower than anticipated due to a timing issue on revenue recognition as Cisco continues to implement its shift from an on-premise model to the cloud. In this quarter, more revenue shifted to rateable recognition than originally anticipated, which caused our revenue to come in below our expectations. And looking at revenue by region, North America accounted for 78% of total revenue this quarter, the same as in the year-ago quarter.

Total revenue for North America was $17.4 million, down 2% from last year, whereas in contrast, total revenue from Europe was $5 million, down 4% year-over-year. Looking at non-GAAP gross profits and gross margins, gross profit for the Q3 was $15.8 million, for a gross margin of 71%, compared to 69% for the prior year quarter. Now, turning to operations, non-GAAP operating costs for the Q3 came in at $13.8 million, a 7% improvement from $14.9 million in the year-ago quarter, reflecting the expense controls we have implemented. Looking at the bottomline, non-GAAP net income for Q3 was $2.6 million or $0.08 per share, up 142% on a dollar basis from non-GAAP net income of $1.1 million or $0.03 per share in the year-ago quarter. Adjusted EBITDA margin for the quarter was 10%, up 500 basis points from 5% in the year-ago quarter.

Turning to our balance sheet and cash flows, we generated $1.7 million in cash flow from operations for the quarter or an 8% operating cash flow margin, up from $905,000 in the year-ago quarter. For the first nine months, cash flow from operations was $17.6 million or an operating cash flow margin of 25%. During the quarter, under our share repurchase program, we repurchased approximately 881,000 shares or $5.5 million, at an average price of $6.26 per share. Of the $20 million authorized $5.7 million remained available under the program at the end of the quarter. Our balance sheet remains very strong. Total cash and cash equivalents at the end of the quarter were $83.1 million, up from $81.3 million a year ago. Now turning to our customer metrics, with our continued focus on knowledge, I will share some additional customer metrics for our knowledge customers.

LTM dollar-based SaaS net expansion rate for knowledge customers was 109%, while our total net expansion rate was 105%. Our LTM dollar-based SaaS net retention for knowledge customers was 97%, while net retention was 96%. Looking at total ARR, SaaS ARR for knowledge customers increased 4% year-over-year, while total SaaS ARR decreased 1% year-over-year. Looking at our remaining performance obligations, total RPO decreased 22% year-over-year to $67.9 million. The decrease was driven by the customer losses we discussed last quarter and the lower number of accounts up for renewal in the quarter. Our short-term RPO was $48.1 million, down 8% year-over-year. Now turning to our financial outlook and guidance, for the fourth quarter, we expect total revenue of between $21.1 million to $21.4 million.

Turning to the bottomline, for Q4, we expect GAAP net loss of $300,000 to $900,000, or $0.01 per share to $0.03 per share, which includes stock-based compensation expense of approximately $1.1 million and depreciation and amortization of $100,000. We expect non-GAAP net income of $200,000 to $800,000 or $0.01 per share to $0.03 per share. For the full fiscal 2024, we now expect total revenue of between $91.5 million to $91.8 million. The slight reduction in full year guidance is to adjust for the accelerated shift in Cisco OEM revenue to a rateable model, where we see — expect to see less revenue up front and more spread across the term of the contracts. We are increasing our guidance for GAAP net income to $5.4 million to $6 million or $0.17 per share to $0.19 per share per year.

We estimate share-based compensation expense of approximately $4.6 million, and depreciation and amortization expense of approximately $400,000 per year. We are also increasing our guidance for non-GAAP net income for the year to $10 million to $10.6 million or $0.32 per share to $0.34 per share. Looking at weighted average shares outstanding, we expect $30.5 million for Q4 and $31.6 million for Q4. In summary, we are pleased with the continued good momentum in new customer wins and business activity in Q4, which continues in Q4, driven by our AI knowledge offering. We continue to generate significantly improved profitability and strong cash flow from operations, while buying back shares of our stock. We continue to invest in knowledge and generative AI capabilities, and with our healthy balance sheet and cash flows, remain well-positioned to capitalize on significant opportunity ahead.

This concludes our prepared remarks. Operator, we will now open the call for questions.

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Q&A Session

Operator: [Operator Instructions] Our first question today comes from Richard Baldry from ROTH. Please go ahead with your question.

Richard Baldry: Thanks. Could you maybe talk a little bit about any changes you’re seeing in sales cycles, faster or shorter? And then, the second would be, I think it was last quarter you talked about the six largest companies you had in trials. A couple were Fortune 30s and a few others were north of $10 billion in revenue, but all would be new logos. Can you talk about how the status of those trials is? Do you think it’s nearing completion? Have any fallen out? Have any added similar large scale? Thanks.

Ashu Roy: Sure. So, a couple of the ones that I mentioned, including the U.S. megabank and the Fortune 100, that’s actually a Fortune 20 company, the mortgage financing company. So. yes, those two did convert. Then we have a couple of the other pilots that we’re going on that are still tracking to close this quarter. That’s good. Interestingly, of those half a dozen that I mentioned, none have fallen off yet. So that’s also promising. We say 75% conversion is where we are at this point with our pilots. But what we’re seeing is with advanced opportunities, the change we are seeing now is that people are making decisions, even though the sales cycles are not shorter, but they seem to be more predictable and That is coming across with the RFPs and just the number of RFPs we’re seeing with larger organizations.

The other thing we are seeing, which I didn’t mention in my prepared remarks, but we are seeing a lot of early conversations which are around where we are prepping for budgeting for 2025. So we are seeing a lot of that as well now. So I think that’s also a good thing for us.

Richard Baldry: And on those larger deals, then, when they move from being trialers to live, we’re talking about the complexities, how long it would take to get into a full deployment for revenue recognition purposes. Do they start with a big bang or will they grow into scale over time? So we have an idea of how those should play in to the P&L over time? Thanks.

Ashu Roy: Most of them start with an initial deployment. That could be still. Our average — I think we have shared this in the past, right? Our average ARR for new logos is in that $200,000 range, right? That’s relatively small for some of these large logos we’re talking about. So the initial deployments tend to be in that zip code, maybe a little north of that in some cases, a little south of that in others, but then the opportunity scales from there.

Richard Baldry: Great. Thanks.

Ashu Roy: Sure.

Operator: Our next question comes from Daniel Hibshman from Craig-Hallum. Please go ahead with your question.

Daniel Hibshman: Hey. Thanks for taking my question. This is Daniel for Jeff Van Rhee. Just on maybe using the U.S. megabank as an example of some of these upsells you have coming down the pipe. I understood that to be, correct me if I’m wrong, an upsell of AssistGPT onto the megabank having already, you said, been using you for several years. How would that upsell compare, say, as a percentage to what they’re already doing with you? Just trying to get a sense for the scale of these wins or maybe just sizing the potential win in terms of five, six, seven figures, et cetera?

Ashu Roy: Got it. So, I think, I may have somehow conveyed the wrong impression. The megabank we’re talking about is a net new logo for us. So that’s one point. But having said that, I can give you a feel for what we are seeing in terms of expansion and existing accounts, which is, I think, part of your question, right? So what we see is with AssistGPT, there’s a lot more excitement to roll out the capability into self-service. So self-service has been an area where there’s been historically a lot of challenge in getting consumers to use your self-service, because it’s still very kind of rigid and not very comfortable conversationally and so we’re seeing that with AssistGPT, that is something people are driving as well.

So that — to us, that is interesting because in our mind, that effectively doubles the proposition of whatever you think you can do on the agent side, you can roughly do the same on the customer self-service side in terms of business value and therefore revenue to us.

Daniel Hibshman: Thanks for that. And then just on the timing headwind in relation to Cisco, just what was the size of that headwind or maybe it’s not exactly sized, just would that have gotten you near, say, the middle or upper bounds of the guide or just having that compare?

Eric Smit: Yeah. No. Good point. It would have got us to the upper end of the bounds probably ahead of the top end of our range.

Daniel Hibshman: Okay. And then just one house cleaning item for me. On the COGS and specifically the service gross margins, do we sort of be thinking of the new levels as sort of a new normal or how should we be sort of thinking about developing?

Eric Smit: So I think this quarter there was some movement where the margins came in certainly lower than where we’ve seen it. So I think looking forward, we would expect that service margins to get back into the sort of high single-digit low-teens range.

Daniel Hibshman: Okay. Thanks. That’s it for me. Thanks, guys.

Operator: [Operator Instructions] And ladies and gentlemen, at this time, I’m showing no additional questions. I’d like to turn the floor back over for any closing remarks.

Ashu Roy: Thanks, Operator, and thanks everyone for listening today. I think an exciting time for us. So I look forward to updating you with our Q4 results. Thank you.

Operator: And ladies and gentlemen, with that, we’ll conclude today’s conference call and presentation. We thank you for joining. You may now disconnect your lines.