Customer surveys were once the backbone of quality programs. Today, response rates are collapsing, customers are ignoring them, and contact centers are left wondering how to measure performance without reliable feedback.Fresh from Customer Contact Week in Las Vegas, Amas shares a conversation that kept coming up among industry leaders: transactional surveys are failing. Some organizations have seen response rates drop nearly 90%, creating real problems for coaching, quality scoring, bonuses, and operational decision-making.Bob and Amas explore:Why surveys became the default measure of customer experience.Whether survey fatigue has finally reached a breaking point.Why AI-powered quality monitoring may be replacing traditional Voice of the Customer programs.The hidden flaw in most customer surveys.How changing who the feedback is for—from the company to the individual agent—can dramatically improve participation.The conversation also tackles a bigger question: if customers are giving you their time and feedback, what responsibility do companies have to actually use it?If your contact center still depends on post-interaction surveys, this episode is a timely look at what comes next.

The more important question might be: why are we still struggling with the same training problems we've had for twenty years?In this episode, we tackle a challenge facing nearly every contact center: new hire training that produces high attrition, slow ramp times, and inconsistent performance.The conversation started with a client losing roughly half of its new hires during training and another portion during nesting. Despite new technology, the outcomes felt painfully familiar.We explored some uncomfortable questions:Are organizations hiring the right people for the job?Do recruiters actually understand the roles they're filling?Are training programs teaching agents what to know instead of how to find answers?Why are contact centers still trying to memorize information that changes every few weeks?How much time do leaders spend observing their own training programs?Bob argues that many training failures begin before day one, with hiring processes that prioritize filling seats instead of finding the right fit.We also discuss one of the biggest missed opportunities in modern training:AI is changing how agents work, but many training organizations haven't changed how they train.As AI-powered knowledge systems, agent assist tools, and automation become standard, training leaders need a seat at the table. Yet in many organizations, training teams are disconnected from the technology decisions that will fundamentally reshape agent performance.One of the biggest insights from the discussion:The real opportunity isn't using AI to automate training.It's using AI to automate the things training used to spend time on so trainers can focus on the skills that matter most:Building rapportProblem solvingJudgmentDe-escalationRelationship-buildingHandling difficult conversationsTechnology changes.The fundamentals don't.Topics discussed:Why new hire attrition remains so highHiring mistakes that create training failuresTeaching agents how to find answers versus memorizing answersThe role of nesting and floor supportWhy training content quickly becomes obsoleteThe disconnect between training teams and AI initiativesAgent assist and the future of onboardingTough skills versus technical skillsWhy fundamentals still matter in modern contact centersHow AI should reshape training priorities

Bob just returned from Italy with a story that should make every customer service leader pay attention.At train stations in Venice and Florence, there were no employees to help. Just kiosks. If you wanted a ticket, you figured it out yourself. If you had a question, there was nobody to ask. It wasn't a glimpse of the future. It was the present.That experience led us into a bigger discussion about AI, automation, and what customer service becomes when human interaction disappears.We unpacked a recent Anthropic report showing that customer service roles have some of the highest exposure to AI-driven task automation. But exposure to tasks is not the same as elimination of jobs.The deeper question is this:Is customer service simply a collection of transactions, or is it fundamentally about relationships?We discussed real-world results from an enterprise deployment of agentic AI where:Escalation rates were 4x higher when customers interacted with AI versus humans.Customers were significantly more likely to demand supervisors from bots.Contact volume increased by 50% in less than six months.Companies discovered that delivering bad news remains far more effective when done by a human.History suggests that new channels rarely reduce demand. Email didn't reduce contacts. ATMs didn't eliminate bank tellers. They changed the nature of the work.AI may do the same.At the same time, organizations are racing toward automation while learning that token costs, increased interactions, and customer behavior may complicate the promised economics.The technology is arriving at bullet-train speed.The question is no longer whether AI is coming.The question is:Who are you in an AI-first world?Will your company become a vending machine that happens to sell products?Or will you intentionally preserve the human elements that create trust, loyalty, and relationships?Because customer relationship management was never supposed to become customer technology management.Topics discussed:Anthropic's AI exposure findingsWhy task automation doesn't automatically eliminate jobsThe difference between transactional and relational serviceReal-world lessons from agentic AI deploymentsRising escalation rates with AI interactionsThe hidden cost of token consumptionWhy customers treat bots differently than humansThe future role of human agentsHow leaders should rethink customer service strategy in an AI-first era

AI hype is colliding with operational reality. A shoe company gains $127M in value by saying “AI,” while contact center leaders are told their entire model is obsolete. The shift from CCaaS to “Customer Experience Automation” reframes everything: not just support, but marketing, sales, and service collapsing into one AI-driven layer.The problem: the foundation is broken. Knowledge is fragmented. Customer data is duplicated. Organizations are misaligned.This episode dissects the gap between what the industry is promising and what companies can actually execute—and why customer service leaders are about to become the last line of defense when it fails.Key Quotes“Customer experience automation just means AI is now the one doing the talking.”“Your human agents can’t find the right answers today—but now the AI is supposed to?”“This isn’t a technology problem. It’s an organizational problem.”“If this fails, customer service cleans it up. Again.”“The train is moving. You either help steer it or get run over by it.”Practical TakeawaysStop debating AI capability. Start fixing knowledge.Treat data quality as a blocking issue, not a backlog item.Force alignment between marketing, sales, and service before automation.Assume AI will act autonomously—and design safeguards accordingly.Position customer service as the control layer, not the endpoint.

Exploring the future of AI in customer service, the role of agents, and how technology is transforming contact centers.AI in customer serviceThe role of human agents vs. botsGenerative AI and workflow orchestrationImplications for contact center staffingFuture trends in AI and automation00:00 Introduction and Guest Credibility01:04 The Reality of AI Agents Today01:43 AI as a Smart Assistant in Customer Calls02:35 Agent Interaction and Human Oversight03:34 Issuing Credits and Automation in Calls04:56 Differences from Past AI Systems05:24 Generative AI and Workflow Orchestration06:38 Automating Routine Tasks with API Calls07:21 Focusing on Customer Conversations08:30 The Future Role of Human Agents09:18 The Next Generation of AI in Customer Support09:58 Scaling AI and Multiple Conversations10:57 Supervising Bots and AI Agents11:51 AI in Escalations and Approvals12:30 The Impact on Contact Center Staffing13:25 New Entrants and Innovation in AI14:30 Channels and Self-Service in the Future15:22 Transitioning from Live Agents to Digital Support15:53 Industry Trends and CFO Expectations16:14 Implications for Workforce and Business Models17:08 The Economics of AI and Customer Support18:28 Preparing for the AI-Driven Contact Center19:35 Historical Context and Future Predictions20:15 Limitations and Realities of AI Adoption21:09 Customer Behavior and AI Impact22:04 Self-Service and Customer Expectations22:50 The Extent of AI Automation23:17 The Role of Technology in Customer Support24:43 Amazon’s Approach to Automation25:36 Limitations of Current AI Models26:36 Decision-Making Boundaries for AI27:04 The Human Element in AI-Driven Support28:15 Closing Remarks and Future Outlook

This episode explores the transformative impact of AI on quality assurance (QA) in contact centers. Hosts Amas Tenumah and Bob Furniss discuss how AI is revolutionizing call monitoring, evaluation, and coaching, emphasizing practical steps for leaders to leverage this technology effectively.00:00 Introduction to QA in Contact Centers00:51 The Impact of AI on Quality Assurance03:50 Revolutionizing QA Processes09:09 Shifting Perspectives on QA Monitoring12:39 Leveraging AI for Enhanced Coaching17:40 The Future of QA in an AI-Driven World"You can listen to 100% of calls now""AI can help identify patterns and issues""Show the value your QA team delivers"

Exploring the evolution and challenges of Omnichannel strategies in customer service, from early concepts to current practices. Insights from industry veterans Bob Furniss and Amas Tenumah on what works, what doesn't, and how to focus on the most impactful channels. key topicsOrigins of Omnichannel in 2010Challenges in integrating multiple channelsThe importance of focusing on top channelsCustomer expectations vs. technological capabilitiesLessons learned from industry experiencesChapters00:00 The Origins of Omnichannel05:20 Challenges in Implementing Omnichannel Strategies10:09 Finding Focus in Omnichannel Efforts14:43 The Future of Customer Interaction

key topics summaryIn this episode, Bob Furniss and Amas Tenumah explore the roles and goals of supervisors in contact centers, emphasizing coaching, relationship-building, and strategic management. They share practical tips for setting goals, managing time, and developing future leaders.Goals and metrics for supervisorsTime management and coaching focusBuilding relationships with team and leadershipMentoring future leaders in contact centersStrategic management at the director level sound bites"Make people think for themselves""Be the evangelist for your contact center""Spend time in books and learning"Chapters00:00 Introduction to Remote Supervision Challenges02:24 Setting Goals as a Supervisor05:05 Coaching and Development Focus07:47 Managing Up: Supervisor and Manager Dynamics10:46 Building Relationships with Management13:16 Transitioning to Managerial Goals15:56 Efficiency vs. Effectiveness in Management18:38 The Importance of Relationships in Leadership21:22 Continuous Learning and Development

 summary This episode features a deep dive into contact center KPIs, exploring their flaws and how to measure customer experience effectively. Hosts Amas Tenumah and Bob Furness challenge industry norms and share practical insights for improving contact center performance.  key  topics Flaws in common KPIs like FCR, Service Level, NPS The importance of standardized measurement How to interpret and act on KPI data Practical tips for contact center improvement  resources Contact Center Metrics Best Practices - https://example.com/contact-center-metrics Net Promoter Score (NPS) Explained - https://example.com/nps-explained Standardizing Contact Center KPIs - https://example.com/kpi-standardization  

Summary In this conversation, Amas Tenumah and Bob Furniss discuss the complexities of performance management, particularly focusing on forced distribution and its implications on employee evaluation and coaching. They explore alternative approaches to performance evaluation that prioritize individual performance over comparative scoring, emphasizing the importance of quality conversations in coaching. The discussion highlights the detrimental effects of scoring systems on employee morale and the need for a shift in focus towards meaningful feedback and development.   Forced distribution can hinder team dynamics and employee morale. Performance should be evaluated based on individual contributions, not relative rankings. Coaching conversations should focus on quality and empathy rather than scores. Removing scores from evaluations can lead to more productive discussions. HR policies often prioritize consistency over individual performance nuances. Employees are aware of compensation disparities and may leverage offers from competitors. Quality conversations can improve coaching outcomes significantly. The focus should be on the overall experience rather than just numerical scores. Feedback mechanisms should be separated from compensation discussions. A shift in focus can lead to better employee engagement and performance.