From 40-minute wait times to under 60 seconds without adding headcount | Allan Harari

Why CS Playbooks Are Failing Your Team

Most CS leaders respond to scale pressure by automating SMB and protecting enterprise. Leana Hart [https://www.linkedin.com/in/leanahart/], Director of Customer Success at Axon [https://www.axon.com/careers], thinks that binary is costing companies on both ends — and she's spent her career managing the full spectrum, from SMB through Fortune 500 enterprise, to prove it. In this episode, Leana gets specific: the account tiering logic she actually uses, why she thinks the playbook-first approach backfires, and the question she teaches her team to ask customers that surfaces renewal risk faster than any health score. Topics discussed: * Why ARR-based segmentation misses influential smaller accounts and underweights expansion potential in the SMB tier * The 4-signal churn indicator Lena uses to identify at-risk accounts within a high-volume book: support ticket volume, webinar attendance, call recency, and 90-day product adoption trend * Why rigid playbooks create noise rather than behavior, and what she builds instead to get CSMs thinking critically * How quarterly portfolio reviews convert individual CSM wins into trackable revenue impact ahead of QBRs and annual reviews * The direct renewal-readiness question she asks customers mid-cycle, and how to read the hesitation in that answer before it becomes a lost deal * Why SMB retention is structurally worse than enterprise, and the specific investment gap on both sides that drives it * Where tools like Claude and Cursor are already changing what CSMs can do with customer data, and the skill gap preventing most teams from getting there * Why project management is the most under-hired and under-trained skill in CS, especially as enterprise account complexity grows Listen to more episodes:  Apple [https://podcasts.apple.com/us/podcast/ai-cx-innovators/id1802013873]  Spotify [https://open.spotify.com/show/0XpZj9bW7OkgXYgRX4DOTJ?si=14589b77ec1d4d00]  YouTube [https://www.youtube.com/playlist?list=PL6T5PUa9NwVKi275ahocKKL1ZG341d2-u]

How OpenAI won the AI race through experience design, not the model

Vishal Anam [https://www.linkedin.com/in/vishalanam/] has spent 20 years helping global organizations close the gap between measuring customer experience and actually acting on it. As Head of CX Consulting, Research and Analytics at Datamatics [https://www.datamatics.com/get-in-touch/sales-enquiry], he has worked across enough enterprise programs to know exactly where they break down. Most CX programs do not fail because organizations stop caring. They fail because the infrastructure for decision-making never gets built alongside the infrastructure for listening. Vishal makes that case clearly here, and backs it up with specific examples drawn from client work, including a contrarian read on why OpenAI captured early market dominance that had nothing to do with their underlying model. Topics discussed: * Why NPS without decision pairing produces no real change * The cognitive load framework for reducing CX decision fatigue * How macro and cultural factors silently distort NPS scores across regions * The SOP gap that breaks CX programs at scale * Optimization vs. transformation: how to tell which one you actually need * Why OpenAI's early lead came from onboarding design, not model quality * Building the CFO business case around missed revenue, not satisfaction scores * How AI is shifting the analytics function away from normalization toward action * Why promoter neglect is a bigger missed opportunity than most teams realize Listen to more episodes:  Apple [https://podcasts.apple.com/us/podcast/ai-cx-innovators/id1802013873]  Spotify [https://open.spotify.com/show/0XpZj9bW7OkgXYgRX4DOTJ?si=14589b77ec1d4d00]  YouTube [https://www.youtube.com/playlist?list=PL6T5PUa9NwVKi275ahocKKL1ZG341d2-u]

Means, motive, and opportunity: why LendingTree uses a crime framework to train CX empathy

Brock Thompson spent 22 years in digital insurance and financial services, starting as a call center agent and eventually becoming VP of Customer Fulfillment at LendingTree, where he oversees inbound and outbound calls, SMS programs, calls technology, and the company's AI voice division. Having sat on both sides of the phone shapes how he thinks about where technology belongs in high-stakes consumer conversations. In this episode, he gets specific about how LendingTree built and justified their first consumer-facing AI voice product, how they brought skeptical call teams along, and why their approach to AI adoption looks more like a marathon than a sprint. Topics Discussed: * The three-part "stickiness" framework: emotional, technological, and financial * Starting the AI business case with one linear, fully measurable conversation path * "Gut drives the test, data drives the decision" as a buying and build philosophy * Why legal and compliance are the first call, not the last, in any AI rollout * The means, motive, and opportunity framework for training human agent empathy * Where human agents still outperform AI in financial services conversations * Reframing AI to call teams as reallocation of effort, not elimination of roles * Evaluating vendors by whether they understand your actual problem, not just their product * The rule of one: prove it once, measure it once, then scale Listen to more episodes:  Apple [https://podcasts.apple.com/us/podcast/ai-cx-innovators/id1802013873]  Spotify [https://open.spotify.com/show/0XpZj9bW7OkgXYgRX4DOTJ?si=14589b77ec1d4d00]  YouTube [https://www.youtube.com/playlist?list=PL6T5PUa9NwVKi275ahocKKL1ZG341d2-u]

How one IVR change eliminated 2.7 million inbound calls a year

Wes Dudley has spent over 30 years leading CX at scale, including JCPenney, Mitchell Gold + Bob Williams, and Broad River Retail, the largest licensee of Ashley Furniture. He moved ticket resolution from nine days to eight hours, eliminated 2.7 million inbound calls annually with a single IVR change, and built a 750-seat contact center during COVID while call volume jumped from 16,000 to 115,000 calls a day overnight. This conversation covers the specific decisions behind those numbers, including how he sequences people, process, and technology investments, when to keep humans in the loop on high-stakes interactions, and what he looks for in a technology partner after seeing both sides of good and bad ones. Topics Discussed: * Why AI without a defined plan consistently underdelivers * Moving ticket resolution from 9 days to 8 hours through routing, not technology * Eliminating 2.7 million calls annually with one IVR implementation * Three-tier triage model built to absorb a 7x overnight call surge during COVID * PPT framework for sequencing people, process, and technology decisions * How the nature of high-emotion purchases should shape your AI and human handoff design * CX All-Stars identity program and its role in remote team retention * What Wes looks for in a technology partner beyond price and product Listen to more episodes:  Apple [https://podcasts.apple.com/us/podcast/ai-cx-innovators/id1802013873]  Spotify [https://open.spotify.com/show/0XpZj9bW7OkgXYgRX4DOTJ?si=14589b77ec1d4d00]  YouTube [https://www.youtube.com/playlist?list=PL6T5PUa9NwVKi275ahocKKL1ZG341d2-u]

From 40-minute wait times to under 60 seconds without adding headcount | Allan Harari

Allan Harari cut Comerica Bank's contact center wait times from 20-40 minutes to under 60 seconds without hiring additional agents. The transformation required rebuilding foundational infrastructure first—workforce management systems providing real-time data instead of monthly reports, quality assurance platforms generating actionable insights, and AI deployed as agent augmentation rather than replacement. His three-year roadmap prioritized operational discipline over technology shortcuts, recovering 10% capacity through schedule optimization before any AI implementation. At USAA, he led a specialized team handling 40,000+ loss-of-loved-one calls monthly for military families, creating direct experience with where human judgment remains non-negotiable versus where AI accelerates outcomes. His vendor selection framework cuts through sales pitches: define the exact problem, know what success looks like, then ask questions exposing actual delivery capabilities. By choosing no-code solutions managed by frontline staff who understand the problems daily, he avoided the overhead trap of building custom solutions from component pieces. Topics discussed: * Cutting average handle time from 11+ minutes to 7 minutes through technology and contact center hygiene * Recovering 10% capacity by reducing lunch breaks from 60 to 30 minutes with proper scheduling * Eliminating 2.5-minute gaps between calls by fixing telephony auto-in state configuration * Deploying auto-summarization reducing after-call work to 3 seconds instead of manual note-taking across 20 systems * Maintaining 92% CSAT despite 20-40 minute wait times through customer loyalty, then improving speed without sacrificing quality * Leading 40,000+ monthly loss-of-loved-one calls at USAA requiring human empathy for military families accessing critical benefits * Selecting no-code AI platforms allowing frontline staff to design solutions versus hiring engineering armies * Using "box of Legos" vendor evaluation: pre-built capabilities you assemble versus raw components requiring custom development * Defining top three problems keeping you up at night before engaging vendors to avoid broad, unfocused implementations * Building AI literacy by teaching proper prompting techniques rather than expecting plug-and-play magic Listen to more episodes:  Apple [https://podcasts.apple.com/us/podcast/ai-cx-innovators/id1802013873]  Spotify [https://open.spotify.com/show/0XpZj9bW7OkgXYgRX4DOTJ?si=14589b77ec1d4d00]  YouTube [https://www.youtube.com/playlist?list=PL6T5PUa9NwVKi275ahocKKL1ZG341d2-u]