The News: Zendesk announced its intention to acquire quality management platform Klaus. The addition of Klaus will augment Zendesk’s workforce engagement management (WEM) capabilities and give analytics on both human and digital agent performance. The acquisition is expected to close Q1 2024. More information on the acquisition can be found in this press release.
Zendesk to Acquire AI-Driven Quality Management Platform Klaus
Analyst Take: Assessing quality during customer interactions can provide the foundation for insights that can be used to tweak operational processes, alter training, investigate supporting technologies and support changes that will result in positive customer experiences. However, it can be a challenge as contact centers expand their digital channels, resulting in increasing amounts of interactions to assess and the complicating factor of agents working in conjunction with digital agents and other tools.
Broader View of Quality Across Interactions
Zendesk’s acquisition of quality management software provider Klaus will work to address the challenge of tracking quality across the rapidly rising number of interactions. According to the companies, it is typical that only 1%-2% of customer experience interactions are scored, which is not enough to provide a broad enough view to find trends and problem areas. Klaus says that its AI technology can score 100% of customer support conversations. The technology also drives those assessments towards action by:
- Pinpointing and filtering out positive or negative sentiment
- Identifying outliers and churn risks
- Zeroing in on conversations that need review, which can include those with digital agents and outsourced teams
- Automatically setting up review assignments with full visibility into goal completions
This will add up to faster action to address problems, some of which may previously have been hidden in a sea of interaction data.
This quality focus will also be supported by the capability to provide 360 degree feedback, by pulling together internal quality reviews with customer satisfaction scores. Additionally, a key performance indicator (KPI) dashboard can help users tease out the relationships among scores such as CSAT, First Call Resolution, and Net Promoter Score, helping companies focus attention on top priority issues.
Assessing Bot Performance Issues
One area of function addressed with this acquisition is the ability to monitor and assess the quality and effectiveness of bot interactions, which increasingly are used as a primary method for deflecting voice, chat, and message-based inquiries. Klaus’ technology should help organizations dive deeper into the elements that affect the user experience with chatbots, particularly around identifying the language, phrases, or structure of the interaction that may cause customer sentiment to turn negative, thereby driving customers to seek a human agent.
Further, because the technology can assess both digital agent conversations and live agent conversations, assessments of entire customer interactions can be made, taking into account all factors (including wait time, dwell time between responses, transfer time, etc.), and how bots and live agents interact with customers based on these factors (e.g., a live agent that does not acknowledge customer frustration with a long wait time or interaction that has had multiple escalations may encounter worsening customer sentiment).
Bias and Inconsistencies Eliminated
One of the challenging aspects of using AI to assess the quality of an interaction is ensuring that scoring for tone and empathy are not unfairly influenced by accents, speaking styles, or vernacular, which could put some human speakers at a disadvantage. Mervi Sepp Rei, PhD, head of Data Science at Klaus, told us that, “Ensuring a bias-free assessment of agent interactions has been the primary objective for Klaus from the outset.” Rei added, “The guiding principle behind our automated evaluation system is to entrust decisions to AI when it comes to identifying positive elements, while reserving negative judgments for human review.”
Furthermore, Rei said that Klaus leverages the capabilities of large language models (LLMs) to help conduct evaluations of interactions in which accents, speaking styles, and vernacular could come into play, and added that because these LLMs are trained on “diverse content, encompassing different dialects, language variants, and content from memes to academic papers,” they therefore help to ensure a high level of comprehension for non-standard content.
Rei noted that Klaus uses a sophisticated AI pipeline that processes content before any assessment occurs, and flags instances of highly deviant interactions in which AI assessment might be prone to significant errors, thereby preventing them from proceeding through the machine language (ML) assessment models. Rei also said that an agent’s past scores or historical quality metrics do not impact new evaluations, preventing the occurrence of an analytical snowball effect.
All told, Klaus appears to be taking a measured and thoughtful approach to leveraging AI to conduct assessments, while maintaining the necessary guardrails to ensure that bias that can unfairly impact human workers does not creep into the models. “We maintain a clear separation between machine decisions and human assessments, clearly delineating which evaluations are automatic and which are done by humans so that they can be interpreted separately,” Rei said. “AI decisions never supersede specialist assessments, and our dashboards feature key performance indicators to monitor the alignment between AI and human assessments.”
Zendesk Builds its WEM Capabilities
Robust workforce engagement management capabilities are a critical backbone in good customer service, making it an area that many contact center technology companies have been putting increased focus on. The addition of Klaus to Zendesk brings other capabilities that will span both customer and employee experience. One intersection points is coaching and learning. The assessment of the interactions will help to find areas where coaching might be needed. This does not have to be a negative; it can be supportive by helping to find areas where knowledge gaps exist to ensure agents are trained appropriately. The data can also be used as an ongoing prompt for a more regular cadence of actionable feedback.
Zendesk and Klaus had a pre-existing partner relationship, with Klaus also an alumni of Zendesk’s Startup Incubator program. This acquisition will slot in nicely with Zendesk’s June 2023 acquisition of Tymeshift, broadening WEM capabilities to support both customers and employees. As companies face increasing pressure for productivity and efficiencies, this data-driven approach will benefit to companies by getting to the critical “action” piece of post-assessment faster and with more focus.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Other Insights from The Futurum Group:
Zendesk Helps Companies Give Employees a Smoother Workday Experience
Zendesk Acquires Workforce Management Software Provider Tymeshift
Zendesk AI Enhances AI Tools for Bots and Agent-Driven Interactions
Image Credit: Zendesk
Author Information
Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
As a detail-oriented researcher, Sherril is expert at discovering, gathering and compiling industry and market data to create clear, actionable market and competitive intelligence. With deep experience in market analysis and segmentation she is a consummate collaborator with strong communication skills adept at supporting and forming relationships with cross-functional teams in all levels of organizations.
She brings more than 20 years of experience in technology research and marketing; prior to her current role, she was a Research Analyst at Omdia, authoring market and ecosystem reports on Artificial Intelligence, Robotics, and User Interface technologies. Sherril was previously Manager of Market Research at Intrado Life and Safety, providing competitive analysis and intelligence, business development support, and analyst relations.
Sherril holds a Master of Business Administration in Marketing from University of Colorado, Boulder and a Bachelor of Arts in Psychology from Rutgers University.
