Introduction
Contact centers face an increasing number of challenges as the expectations around omnichannel support and smoother customer journeys have increased. This trickles down to the agent level as employees are faced with increasingly complex interactions, often across different channels. It is a difficult job and retention and turnover continue to be problems for contact centers.
This past year saw a lot of focus on how AI can help support agents once they are in a job and provide a better customer experience (CX). However, a critical piece of an agent’s employee journey is before they are already in place taking calls. This includes milestones such as hiring, onboarding, and training, and these steps are especially important to the future success of an agent.
Zenarate Founded to Support Agent Training and Deliver CX
The Futurum Group was recently able to chat with Zenarate cofounder and CEO Brian Tuite to learn more about the company and get a demo of the AI Coach solution. This solution takes aim at the contact center challenges mentioned above and works to not only help hire and keep the right people in place, but to also improve call resolution rates, CSAT, and speed to proficiency.
Cofounder Tuite came from a contact center background and saw firsthand the challenge of harnessing training best practices so that other agents could benefit. Tuite also saw agents come through the contact center who had great potential but struggled to maintain and build skills. Says Tuite, “I am a big believer in practice to develop skills and improve performance, and I knew there was a better way to train and support agents.” Using this learning-by-doing approach, Zenarate has developed a solution that allows for in-depth natural language roleplay and skill coaching.
Tuite likens this approach to being a flight simulator for customer engagement, allowing agents to get immersed in all the types of calls that they might encounter on the job before they take their first live call. The approach is scaffolded, allowing for agents to:
- Roleplay using their own words without reading a script
- Use AI Coach to simulate varying personas, call paths, and call types to allow for diverse types of branching scenarios and micro learning
- Receive call skill and screen navigation coaching during the actual role play, allowing trainees to learn fast and certify to talk to a live customer
AI Coach can be used for pre-hire screening, new hire training, and tenured agent upskilling.
“With the increasing amount of complexity in contact centers, it can take agents up to nine months to become fully proficient at their jobs. The use of our simulation training solution can help companies make sure they are hiring the right people, provide new hire agents the skills training they need to deliver the best service possible, and support agent development throughout their career,” said Tuite.
Flexible, Targeted, and Company-Driven Training Development
Traditional forms of contact center training often involve human-human role playing, which can be awkward and is also hard to scale. AI Coach is asynchronous and can be done from home, or in the office, requiring no personal or account information and no IT integrations. The setup makes it easy for companies to get up and running quickly.
Users of AI Coach own all the content and simulations can be created based on their needs, which could include things like overcoming a sales objection, rolling out a new product, improving collections conversions, decisioning fraud inquiries, and solving complex customer service problems on the first call. The simulations can be very targeted and can also be used to shore up soft skills gaps such as active listening and empathy. The model can consider tone and inflection, and the data provided after completing simulation training clearly shows that the more agents practice, the better they get at delivering soft skills and best and required practices. And potential call skill and screen navigation gaps are easily identified before an agent speaks with their first live customer.
Tying It Together with Live Calls
The benefits of AI Coach can be magnified by tying it together with live call data. Zenarate recently launched this new enhancement, Call Analyzer, that can help support the need for ongoing agent training. With Call Analyzer, AI is used to score customer calls against the same call skills that agents were trained on during their simulation training, plus any new skills that contact leaders would like to assess, and this data is ready for teams to use on a daily basis. Personalized development plans are automatically created for agents that recognizes agents for their call skill strengths and points out their call skill opportunities with recommended simulation training to help close their call skill gaps, helping agents build their confidence and address potential issues that might hinder a positive customer experience.
Zenarate has found success in its approach, having many of the top 20 brands as customers representing a variety of verticals such as healthcare and insurance, telecommunications, travel & hospitality, BPO, and financial services. Its customers have also been reporting positive data including 40-70% faster speed to proficiency by using AI conversation, screen and chat simulation; higher CSAT and call quality scores and lower operating costs due to improved first call resolution and conversion rates. From an employee experience perspective, customers have also reported 10%-40% lower employee attrition.
Supporting Organizational Continuous Improvement Strategies
One of the challenges facing organizations today is the need to deploy continuous improvement mechanisms, particularly around employee training. Training employees once during onboarding, without conducting periodic follow-up training, will make it challenging to solidify best practices, ensure compliance with changing policies or strategies, and more difficult to introduce new technologies, such as the incorporation of generative AI-based assistants. Zenarate’s asynchronous approach to providing AI-based simulation training and coaching can enable organizations to develop agent skill proficiency and deploy new training at scale, and allow organizations to upskill agents at scale, while minimizing investment in human trainers.
Ultimately, AI, natural language processing, and analytics have reached a technological inflection point, where they are capable of handling all but the most challenging edge cases around training. Because they are based around scalable technology, organizations can roll them out across the organization with a relatively negligible cost impact, compared with human-led training programs. As always, organizations that deploy AI-based training need to ensure that the data they are using to power the AI-based coaching solution has been cleaned and vetted to remove instances of toxicity or bias, to ensure that training applications reinforce the company’s desired attributes and tactics.
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:
2023 Customer Experience Trends and a Look Ahead
Balancing Average Resolution Time With CSAT in the Generative AI Era
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.
