(NAS:EGAN) eGain: The Rise of Knowledge Management Systems

Neutral rating on eGain (NAS:EGAN) this month. Through extensive research, analyses, and speaking with IR, our initial hypothesis for a “buy” rating did not materialize. Our principle: if we don’t add it to our portfolio, no “buy” rating. Learn more about why we publish neutrals here

Thesis

EGAN provides workflow solutions for contact centers, known as Knowledge Management Systems (KMS). These systems aggregate up-to-date information enabling customer service agents to deliver high-quality responses to customers. With the rise of generative AI, enterprises increasingly recognize the value of such solutions, leveraging AI agents to provide superior customer interactions at reduced costs—a technological sea change. While eGain has strong offerings in this space, its ability to capitalize on growing demand is constrained by a top-down leadership approach and intense competition from incumbents like Salesforce. Although initial program wins are promising, we await further evidence of execution before considering a position.

Company Background

EGAN has been listed on the Nasdaq for nearly 30 years. During the dot-com bubble, it reached a valuation of nearly $2 billion before collapsing and never returning to those levels. Originally an email management service, eGain has since pivoted to helping enterprises enhance customer service experiences while reducing operational costs. The company operates through two primary segments, each contributing roughly 50% of its revenue: its KMS (more info below) and its Conversation Hub (this aggregates customer messages from different channels, like chat, email, and social media, into one place) While these segments have been historically stable, the Conversation Hub segment faces increasing competition from smaller point solution providers, whereas the relevance of its KMS offerings continues to grow.

eGain’s KMS solutions cater to companies with complex customer service needs, requiring accurate and standardized responses. These are typically large organizations (with over 5,000 employees) operating in regulated, B2C industries such as financial services, insurance, healthcare, and utilities.

What is a KMS?

A KMS is designed to curate any and all information customer service agents might need to assist current or prospective customers. This information involves: standard procedures, business operations, benefits, billing, claims, and authorization protocols. A KMS is the data backbone for customer service agents.

Contact centers, where customer service representatives address customer inquiries, often face challenges like inconsistent responses and difficulty in identifying the best answers—key contributors to poor customer experiences. A KMS addresses these pain points by integrating with enterprise software like Salesforce and ServiceNow through APIs. After each customer interaction, the KMS updates the associated CRM profile with relevant data. Below is a visual representation of a typical KMS workflow that EGAN produces.

Companies without a KMS often rely on customer service agent training, where knowledge resides in the agents’ heads rather than in a centralized, easily accessible repository. Alternatively, they may use basic scripted software that lacks robustness and offers only templated responses.

The reason why KMS systems are not prevalent as one might expect is because implementing a KMS typically requires a months-long process (around six months) involving the creation of a dedicated knowledge team. This team collects and curates knowledge across the organization and ensures it remains up-to-date, as information becomes outdated over time. However once implemented, a KMS improves Net Promoter Scores by improving the customer experience. An effective KMS significantly improves first-call resolution rates, increases call throughput by reducing average handling time, minimizes the need for extensive agent training, and enhances customer satisfaction.

The Impact of Gen AI on KMS

While companies are eager to adopt generative AI for customer service and other tasks, accurate inference without hallucination requires training on the latest high-quality enterprise data—this is where a KMS becomes critical. A KMS ensures access to accurate, regulation-compliant, and policy-aligned data while establishing guardrails to maintain reliability. Additionally, a KMS creates a closed feedback loop, enabling continuous improvement of generative AI models based on customer interactions and responses. As such, a KMS is essential for effectively integrating generative AI into enterprise workflows.

Along with increasing demand for KMS, Generative AI has also transformed the implementation of a KMS. It simplifies KMS onboarding by automatically organizing and classifying large datasets, generating user-specific guides, and creating conversational interfaces for smoother adoption. AI-driven features enhance usability, lowering barriers to employee engagement and improving overall system efficiency.

EGAN’s Strategy

EGAN’s strategy has evolved with the rise of generative AI. As building a KMS has become less resource-intensive, management is shifting focus from a traditional salesforce to a self-serve model. Sales dollars are being redirected toward product and brand marketing, with increased investment in these areas. This shift also enables EGAN to target smaller businesses (SMBs) with approximately 1,000 employees, as its offerings are now better suited for these customers.

Generative AI has also created opportunities for EGAN to expand beyond the contact center industry. A notable recent win includes a large data center field service operator, highlighting field service as a significant adjacency to customer service that can benefit from enhanced knowledge management solutions.

EGAN faces challengers on two fronts: competition from smaller point-solution vendors and large enterprises like ServiceNow, PegaSystems, and UiPath. These competitors are expanding into the KMS space, recognizing its critical role in enhancing generative AI performance and unlocking its value. To differentiate from these larger incumbents, eGain is adopting two key strategies: positioning itself as a lower-cost alternative and offering a solution that avoids lock-in with a single CRM vendor.

Opportunities

Gen AI has Increased the Importance of KMS systems

eGain’s KMS offerings are more relevant than ever, supported by strong enterprise relationships. A major shift underway is the adoption of AI Agents in place of customer service agents. These conversational agents can deliver optimal answers at a fraction of the cost—around 1/5—offering an unbeatable combination of improved customer experience and reduced operational expenses.

The Expansion of KMS to the Enterprise

With generative AI, a centralized knowledge repository is becoming increasingly valuable to employees. It shortens onboarding times and, in a world of remote work and accelerating industry dynamics, equips employees with the most accurate and up-to-date information. This capability provides a significant competitive advantage that companies are eager to maximize.

Headwinds

Half of EGAN’s Business is in Decline

The Conversation Hub segment is roughly 50% of EGAN’s business and is declining at a rate of around 7% annually. It is primarily being leveraged for cash generation to fund their KMS product development. EGAN is making significant investments with plans to launch AI Agents next year. However, any missteps could leave it in a precarious position, facing subscale operations and declining revenues. Although the company’s $70 million cash balance provides a modest buffer, its share buyback policies could deplete this reserve rapidly.

Management Leads in a Top-Down Fashion

CEO and Founder Ashu has led EGAN since its inception. Observing the frequent turnover of SVPs and employee feedback, it is clear he maintains significant control over the company, a dynamic unlikely to change. His track record of performance has been underwhelming, with the company’s growth stagnant over the past decade. While Ashu is product-oriented, his ability to inspire or implement transformative change remains in question.

Conclusion

The rise of generative AI has amplified enterprise interest in such KMS offerings, creating significant growth opportunities. However, EGAN’s ability to capitalize on this trend is constrained by its top-down leadership approach and strong competition from incumbents like Salesforce and other CRMs. We would need to see proof of execution and product market fit before initiating a position.

INVESTMENT DISCLAIMERS & INVESTMENT RISKS
Past performance is not necessarily indicative of future results. All investments carry significant risk, and it’s important to note that we are not in the business of providing investment advice. All investment decisions of an individual remain the specific responsibility of that individual. There is no guarantee that our research, analysis, and forward-looking price targets will result in profits or that they will not result in a full loss or losses. All investors are advised to fully understand all risks associated with any kind of investing they choose to do.