High-Ticket Insurance Sales: Convert More at Scale
Two agents at the same high-ticket sales insurance team work the same leads, sell the same products, use the same tools. One binds a policy on 65% of conversations. The other binds zero. That gap shows up over and over in the data, and it has nothing to do with talent. We scored hundreds of real insurance sales conversations on Insight7’s conversation intelligence platform, every one of them a customer who started a quote through an online comparison tool and connected with a licensed advisor. We graded each conversation across five performance dimensions, then grouped agents into tiers. The behavioral patterns that separate the top 25% from the bottom 25% are consistent, measurable, and coachable. Here’s what the data says actually moves a customer from quote to bound policy, broken into five sections: If you want the full picture, the complete report breaks down all five dimensions with tier-by-tier benchmarks. 1. Finish the funnel before you do anything else This is the single strongest predictor of revenue, and it produced the widest gap in the entire dataset: 204% between top and bottom tiers. Funnel performance measures one thing: does the agent move through all four stages of the conversation, greet, discover, quote, close, and actually attempt to bind? Top agents send payment links proactively, confirm effective dates, and name the next step before the customer asks. Bottom agents stall. Many never present a quote at all. Some quote, then never attempt to close. The result is stark. 65.4% of top-tier conversations bound a policy. 0% of bottom-tier conversations converted. Not a lower rate, zero. The takeaway: before you coach scripts or objection rebuttals, make sure every conversation reaches a close attempt. An agent who never quotes can’t be coached on anything downstream. 2. Ask more, talk less The second-widest gap was discovery and engagement at 111%, and the real signal inside it is who’s doing the talking. Top agents asked 7 questions per conversation, nearly 2 of them open-ended. Bottom agents asked 3, fewer than 1 open-ended. But the sharper number is customer participation: top-tier conversations averaged 16.1 customer turns. Bottom-tier averaged 3.2. That’s a 5x gap. At a 4:1 agent-to-customer talk ratio, you have a conversation. At 12:1, you have a monologue the customer is waiting to escape. This is where empathy becomes something you can actually measure. Agents who ask why the customer is shopping, listen to the answer, and tailor the recommendation close dramatically more often. Discovery isn’t a soft skill. It’s the mechanism that turns a generic pitch into a personalized recommendation. 3. Name the carriers and the numbers Compliance and product presentation showed a 108% gap, and it overturns a common assumption: that thorough, compliant presentations slow down conversion. The opposite is true. Top agents named 1.69 carriers per conversation, stated exact premiums, explained coverage, and compared alternatives. Bottom agents named a carrier on just 0.12 conversations. Most of their customers never even learned who was behind the quote. Specificity builds trust, and trust converts. Compliance and conversion aren’t in tension, they’re aligned. The agent who names two carriers, states the premium, and walks through the coverage limits is also the agent the customer believes. 4. Don’t wait for objections to coach objection handling Objection handling produced the smallest gap in the report, just 21%, and that number is misleading in an important way. Bottom-tier conversations rarely reach the point where objections even surface. No quote means no price pushback. Objection handling is a downstream skill that only activates once discovery and funnel progression are working. So if your bottom performers look “fine” on objection handling, it’s not because they’re good at it. It’s because they never get far enough into the conversation to be tested. Coach the funnel and discovery first. The objection scripts only matter once agents are actually reaching the close. 5. The metrics worth coaching first Pulling it together, here are the five benchmarks drawn from the top-performing tier, ordered by impact. These are the daily targets that move the needle. Metric Target Average now What to coach Funnel completion ≥ 8.5/10 5.87 Every conversation hits all four stages and ends with a close attempt Questions per call 7+ (2 open-ended) 5.08 Cover shopping reason, coverage needs, payment preference before quoting Talk ratio ≤ 4:1 6.7:1 Pause after every info block: “Does that make sense for you?” Carriers mentioned 2+ 1.04 Name at least two carriers checked; comparison builds trust Time to quote First third of call Varies Finish discovery early and start quoting; customers came for a quote Start with funnel completion. Fix that first, and the rest follows. Why this matters more in chat There’s a reason this is urgent now. Chat-based quoting converts at roughly half the rate of voice, and chat is becoming the dominant channel. Voice gives agents tone, pacing, and emotional cues. Chat strips all of that away. When a voice call stalls, the customer is still on the line. When a chat stalls, they’ve already opened the next tab. The performance levers in this report, funnel completion, discovery, turn balance, product presentation, are the only tools agents have left when tone and body language are gone. They’re also the levers most teams can’t see. Most QA teams manually review less than 2% of conversations. A 204% funnel gap and a 5x participation gap don’t show up in a 2% spot check. No human reviewer tracks those patterns across hundreds of conversations. The verdict The performance gap isn’t a talent problem. It’s a visibility problem. The conversations are already recorded. The behaviors are measurable and consistent. What’s been missing is a system to evaluate at scale and turn the findings into coaching. From 0% to 65% isn’t luck. It’s a system. Want the full breakdown? The complete High-Ticket Insurance Sales report covers all five dimensions with tier-by-tier benchmarks and the full coaching playbook. Book a demo to see how your team compares.
Turning Your Call Transcripts Into a Knowledge Base
Every time an experienced rep handles a difficult customer question, they produce something valuable. A correct answer, delivered in context, backed by real product knowledge. That answer is spoken once. Then it disappears. The next rep who gets the same question starts from zero and they figure it out on a live call with a real customer, which is the most expensive way to learn. This is happening on every team that has call recordings and no system for turning them into something accessible. The knowledge exists. It is just not in a form anyone can reach when they need it. What Recordings Without a Knowledge Base Look Like Thousands of transcripts covering every question your customers asked, every situation your reps have navigated, every edge case someone had figured out and handled well. None of it is in a knowledge base. New reps are onboarding into a situation where the answers already exist. They are spending their first weeks asking colleagues and learning on live calls with real customers because the institutional knowledge of the team is locked inside recordings nobody is systematically reading. The recordings are there and the answers are in them. The gap is purely structural. The Harder Problem Extracting knowledge from existing recordings is the first problem. Most teams stop there when they think about this. The harder problem is what comes after: keeping the knowledge base current as the product changes, as questions evolve and new situations emerge. A knowledge base that isn’t updated becomes inaccurate. And an inaccurate knowledge base is worse than no knowledge base, because reps trust it. Most knowledge bases go stale for one reason: the update is manual and it competes with everything else the team is doing. Someone has to notice the answer has changed, draft the update, get it approved, and publish it. That is exactly what Insight7 solves – an AI native system where every call your team has automatically contributes to the knowledge base, surfacing new questions as they emerge and updating answers as the product evolves. What Changes When You Actually Do This At Insight7, the teams we work with that implement a call sourced knowledge base consistently see new reps reaching baseline performance faster than those that onboarded without it. The knowledge that previously lived in the heads of the three most experienced people on the team becomes accessible to everyone. How Insight7 Approaches This At Insight7, our knowledge base solution is built around the assumption that the best source material for what your team needs to know is your own calls. The system takes your transcripts and structures them into searchable, editable articles.Answers drawn from the calls where the question came up, how your best reps answered it, and what the outcome was. Draft articles surface automatically from the call analysis. Designated reviewers see them in a queue. They approve, edit, or reject. What goes live has been through a human who knows the product and trusts the answer. The result is a knowledge base that updates from the work the team is already doing, rather than requiring a separate documentation effort that competes with everything else.
Insight7 Launches AI Coaching Mobile App for Communication Practice
GAINESVILLE, FL, April 15 ,2026 – Insight7, a leading developer of Call Intelligence and AI Coaching solutions, today announced the official launch of the Insight7 mobile app, bringing AI Coaching & Roleplay to iOS devices. Built for both individual professionals and customer facing teams, the app delivers on-demand access to skill building practice and performance feedback – wherever life and work happen. Whether you’re a job seeker preparing for your next interview, an early career professional building communication confidence, or a sales rep sharpening objection handling before a big call, the Insight7 mobile app puts personalized AI coaching in your pocket. You get realistic practice and instant feedback, on your own time. “Most people don’t get enough practice before the moments that matter most,” said Odun Odubanjo, CEO and Co-founder at Insight7. “The mobile app changes that. It gives every individual an always available coach that helps them show up prepared and confident.” Key Features and Capabilities Built for Every Stage of Your Career The Insight7 mobile app is available now on the App Store. Learn more at Insight7.io. ABOUT INSIGHT7 Insight7 is the developer of AI- powered Call Intelligence and AI Coaching built for modern workplace teams and individual professionals. From Call Analytics for extracting insights from customer conversations to AI Coaching & Roleplay for accelerating skill development, Insight7 helps organizations and individuals turn conversations into growth. Founded by former Shopify product leader Odun Odubanjo, Insight7 is based in Gainesville, Florida, with a globally distributed team. Learn more at www.insight7.io
High Ticket Sales: One Call Close Revenue Intelligence Buyer Guide
In high-ticket, one call close sales, every call is the only call. There is no follow-up sequence. No second meeting. No recovery email. You either close on that call or the opportunity is gone. This reality changes everything about how performance must be measured, coached, and optimized. This buyer guide is written for high-ticket sales leaders evaluating revenue intelligence platforms built specifically for one-call-close environments. It covers: What revenue intelligence means in a one-call-close model Whether your team is ready What to look for in a platform What it actually costs How to evaluate vendors How to implement successfully How to measure ROI So you can make a confident, informed decision before signing a contract. Why One Call Close High-Ticket Sales Is Structurally Different In traditional sales teams, deals unfold over weeks or months. There are multiple touchpoints, pipeline stages, and opportunities to recover from mistakes. In one-call-close sales, the margin for error is effectively zero. The moment a rep hangs up without a commitment, the lead goes cold.There is no nurture sequence. No second shot. This model is common in high-ticket industries such as: Insurance Healthcare services Financial services Manufacturing and equipment sales Because revenue is won or lost inside a single conversation, performance visibility must operate at the call level – and it must be fast. Most revenue intelligence platforms were built for multi-touch B2B environments. They focus on pipeline tracking, deal stages, and long sales cycles. One-call-close teams operate under completely different constraints: Same-day coaching matters Script execution precision matters Objection handling quality matters First-call conversion rate is the core KPI This guide helps you evaluate platforms designed for that reality What Is Revenue Intelligence for One Call Close Sales? Revenue intelligence for high-ticket, one-call-close sales is the use of AI to analyze 100% of sales conversations, identify the exact moments where revenue is won or lost, and turn those insights into actionable coaching before the next live call. In high-ticket environments, a single lost call can represent thousands – sometimes tens of thousands – in revenue. There is no second meeting to recover it. Because the entire sales cycle happens inside one conversation, performance visibility must operate at the call level – and it must move fast. Revenue intelligence in this context must answer operationally critical questions like: What do top closers do in the first 60 seconds that average reps don’t? Which objections are consistently ending high-ticket calls before the close? At what exact point in the conversation are deals being lost? What behaviors correlate with post-sale cancellations? How do we replicate our best rep’s performance across the entire team? Traditional QA processes review 1–3% of calls manually. Revenue intelligence analyzes 100% of conversations using AI. Instead of anecdotal feedback, you get: Pattern recognition across thousands of high-ticket calls Call-level conversion diagnostics Behavior-level performance data Structured practice environments that improve reps before they are live again For high-ticket, one-call-close teams, delayed coaching equals lost revenue. Insights must translate into same-day improvement. Why Most Revenue Intelligence Platforms Aren’t Built for One Call Close Sales Most dominant revenue intelligence tools – including Gong, Chorus.ai, and Clari – were designed for multi-touch B2B sales cycles and long pipeline management. Their architecture prioritizes: Deal progression tracking Forecasting accuracy Pipeline visibility across weeks or months Executive reporting at the opportunity level High-ticket, one-call-close sales operate under different economic constraints: The entire revenue opportunity lives inside a single call First-call conversion rate is the primary KPI Objection handling precision directly impacts revenue Coaching must be immediate to prevent repeat losses When revenue is decided in 30–60 minutes, the platform must treat that call as the complete sales cycle – not as one stage in a longer journey. Is Your High-Ticket Sales Team Ready? Revenue intelligence creates the greatest impact when sufficient call volume and coaching discipline exist. Strong Fit 25+ reps and 1,000+ calls per week High-ticket, close-or-lose model on the first call Top reps outperform average reps by 2x or more Scaling faster than new hires can be trained Post-sale cancellations are eroding booked revenue Call recordings, CRM data, and dialer API access available These conditions generate enough data for AI to identify meaningful patterns in high-ticket conversion performance. Not Ready Yet Fewer than 25 reps or under 500 calls per week No call recordings Managers do not currently coach Leadership expects a “set it and forget it” solution Revenue intelligence amplifies a coaching culture — it does not replace one. What Does Revenue Intelligence for High-Ticket Sales Actually Cost? Most vendors quote per-seat pricing. For a high-ticket sales team with ~100 users, the fully loaded Year 1 cost typically looks like this: Cost Category Typical Range Platform fees $80K–$150K / year Implementation & integration $10K–$50K IT and RevOps time $20K–$40K Manager time $20K–$40K Change management $15K–$40K Year 1 Total $150K–$320K A practical budgeting rule:Plan for 2–2.5x the quoted platform fee in Year 1. This reflects internal time, rollout effort, and change management — not just software. The Hidden Cost: Failed Implementation The largest financial risk is not the platform fee. It is a stalled rollout. Low adoption, minimal behavior change, no measurable ROI — followed by migration to another platform 12–18 months later — can easily double the original investment when you factor: Lost optimization gains Internal rework Management distraction Contract overlap Getting vendor selection and rollout right matters more than negotiating a 10% discount. Benefits and Drawbacks Benefits 1. More Closed Deals at the Same Call Volume In high-ticket, one-call-close sales, a 1–2% lift in first-call conversion rate generates incremental revenue without: More leads More headcount More marketing spend It compounds across thousands of calls. 2. Precision Diagnosis of Call Breakdown AI identifies where deals fall apart: Weak opening Poor objection handling Missed buying signals Mistimed close Coaching becomes targeted instead of anecdotal. 3. 100% Call Coverage Traditional QA reviews 1–3% of calls.Revenue intelligence analyzes all of them. Managers move from sample-based coaching to pattern-based coaching. 4. Faster Ramp Time New hires practice real objections before facing
Insight7 Launches AI Coaching & Roleplay: On-Demand Practice for Workplace Communication
GAINESVILLE, FLA, January 14, 2026 — Insight7, a leading developer of conversational intelligence solutions, today announced the official launch of AI Coaching & Roleplay, an AI-powered practice platform that helps sales professionals, customer support representatives, managers, and leaders develop critical communication skills through realistic conversation simulations and instant, data-driven feedback. Whether the objective is mastering discovery calls, handling difficult customer situations, delivering performance reviews, or practicing executive presence, AI Coaching & Roleplay supports a wide range of use cases and adapts to the unique development needs of each role. Unlike traditional coaching models that rely on manager availability and subjective feedback, or expensive simulation tools designed for enterprise-scale training programs, AI Coaching & Roleplay is an accessible, template-driven solution built for growing teams. The platform uses dynamic AI personas that engage in realistic, unscripted conversations, automatically evaluating communication effectiveness and providing instant coaching tied to specific conversation moments. It delivers value across roles by providing unlimited, on-demand practice environments where skill development happens on each individual’s schedule, not their manager’s calendar. “There’s a fundamental disconnect between how organizations want to develop their people and the limitations of traditional coaching,” said Odun Odubanjo, CEO and Co-founder at Insight7. “Teams don’t need another tool that replaces human judgment with black-box AI. They need accessible practice environments that build real skills through repetition and objective feedback. Our platform delivers exactly that – AI that accelerates human skill development rather than attempting to replace human coaches.” Key Features and Capabilities AI-Powered Roleplay Simulations: Engage in realistic, unscripted conversations with dynamic AI personas that adapt in real time based on communication style and responses. Automated Coaching & Skill Evaluation: Receive instant, objective feedback on empathy, active listening, questioning, tone, clarity, and goal achievement tied to specific conversation moments. Scenario Libraries: Access prebuilt templates for common situations including objection handling, complaint resolution, discovery calls, negotiation, and feedback delivery. Performance Dashboards: Visualize individual and team-level skill progression over time with objective behavioral data and improvement tracking. Multilingual Support: Practice and evaluate conversations in multiple languages to support global teams and diverse customer bases. Transforming Skill Development Across Critical Use Cases Insight7’s AI Coaching platform serves a wide range of applications for customer-facing teams and organizational leaders: Sales Teams practice discovery calls, objection handling, and closing conversations in risk-free environments, accelerating ramp time and building confidence before live prospect interactions. Customer Support and Success Teams rehearse difficult scenarios including complaint resolution, de-escalation, relationship-building, and renewal conversations, improving customer satisfaction and retention without risking customer relationships. Leaders and Managers practice delivering difficult feedback, conducting performance conversations, navigating conflict resolution, and building executive presence for high-stakes communication situations. Enablement and L&D Teams scale consistent, high-quality coaching across distributed teams, standardize training programs, and measure skill development with objective performance data rather than subjective manager assessments. AI Coaching & Roleplay is available immediately for organizations of all sizes. Teams interested in learning more can visit Insight7. ABOUT INSIGHT7 Insight7 is the developer of AI-powered conversation intelligence and coaching platforms built for modern workplace teams. From Call Analytics for extracting insights from customer conversations to AI Coaching & Roleplay for accelerating skill development, Insight7 helps organizations turn conversations into revenue and people growth. Built for everyday business users, the platform empowers teams to standardize training, scale coaching, and drive measurable performance improvement. Founded by former Shopify product leader Odun Odubanjo, Insight7 is based in Gainesville, Florida, with a globally distributed team. Learn more at www.insight7.io
AI Coaching Use Cases: How Teams Improve Performance
Training teams today is harder than ever and AI coaching solves that. Customers expect faster responses, sales cycles are more complex, and leaders juggle distributed teams with shrinking attention spans. Traditional workshops aren’t enough — people forget up to 70% of what they learn within a week. The solution: AI coaching. Not a replacement for trainers or managers, but a force multiplier. AI lets teams practice real scenarios, build muscle memory, and get instant feedback, helping them perform at their best every day — not just after training. Across Sales, Customer Service, and Leadership, Coaching with AI tackles real challenges teams face every day. Here’s how. AI Coaching In Sales Sales is unpredictable. One missed discovery question, a weak objection response, or a poor pricing explanation can cost a deal. AI gives sales reps the opportunity to practice these moments repeatedly until they become instinctive. Objection Handling Sales reps frequently encounter tough objections — pricing pushback, timing concerns, or competitors. Many freeze or respond defensively under pressure.AI coaching enables realistic objection roleplays and provides targeted feedback, helping reps stay calm, persuasive, and confident. Discovery Calls Reps often miss critical qualification questions or fail to uncover customer needs, leading to lost opportunities. AI coaching guides reps through discovery conversations, ensuring they consistently uncover valuable insights, improving lead quality and deal potential. Prospecting & Cold Calls Initiating conversations with new prospects is challenging and often inconsistent. AI coaching provides scenario-based practice for openings, transitions, and rapport-building, helping reps start strong and build confidence before they even pick up the phone. Product Pitching Inconsistent or unclear presentations reduce effectiveness. AI coaching lets reps practice tailored product pitches, ensuring clarity, relevance, and alignment with customer needs. Negotiation & Pricing Negotiating value and pricing under pressure is a high-stakes skill. AI allows safe negotiation simulations, helping reps build confidence, navigate difficult conversations, and improve win rates. Renewal & Upsell Many reps miss upsell opportunities or fail to communicate value effectively. AI simulates renewal and upsell conversations, increasing retention and account growth. Product & Process Knowledge Testing A deep understanding of products and internal processes is essential. AI reinforces knowledge through scenario-based testing, ensuring reps communicate confidently and accurately. Tool-Specific Knowledge Testing CRM and sales tools are only as effective as the reps using them. AI simulates tool-based tasks to improve proficiency and reduce errors. Post-Training Reinforcement Without follow-up, workshop skills fade quickly. AI provides exercises and roleplays after formal training, reinforcing learning and helping knowledge stick. Customer Service AI Coaching Customer service teams deal with high-pressure interactions every day. Frustrated or angry customers, inconsistent processes, and complex tools can all reduce efficiency and satisfaction. AI helps reps practice empathy, consistency, and proactive support. Customer Complaint Handling Reps often struggle to manage frustrated or angry customers. AI simulates complaint scenarios, providing real-time feedback to improve empathy, de-escalation, and resolution skills. Support Ticket Resolution Following inconsistent processes can cause errors and delays. Coaching wth AI reinforces correct procedures, improving efficiency and service consistency. Proactive Customer Success CS teams often react rather than anticipate customer needs. AI tools offer simulations for proactive engagement, helping reps identify churn signals and increase customer satisfaction. Product & Process Knowledge Testing Reps need accurate knowledge at their fingertips. AI tests understanding through simulated interactions, ensuring correct guidance and reducing errors. Tool-Specific Knowledge Testing Ticketing platforms and internal dashboards can be complex. AI coaching provides hands-on practice, improving tool usage and accuracy. Post-Training Reinforcement Workshops alone are not enough. AI delivers follow-up exercises and roleplays to reinforce skills over time, keeping service quality high. AI Coaching In Leadership Leaders face uniquely challenging conversations — giving feedback, coaching employees, handling conflicts, and motivating teams. AI coaching gives them a safe environment to practice and refine their skills, improving outcomes for the entire organization. Performance Feedback Coaching Conversations Guiding employee performance and development requires skill. Coaching with AI enables realistic coaching roleplays, fostering team growth and engagement. Difficult Conversations Sensitive issues often get avoided. AI simulations allow leaders to practice conflict resolution, improving outcomes while reducing stress. Delegation & Empowerment Poor delegation creates bottlenecks and lowers accountability. coaching with AI guides leaders in assigning tasks and empowering teams, boosting overall performance. Team Conflict Mediation Leaders aren’t trained therapists but must resolve interpersonal disputes. AI simulates conflict scenarios, helping leaders mediate effectively and maintain cohesion. Recognition & Motivation Many leaders under-recognize achievements or fail to motivate. AI provides practice in recognition conversations, enhancing engagement and morale. Post-Training Reinforcement Leadership skills degrade without consistent practice. AI delivers exercises, reflection prompts, and reinforcement to ensure long-term development. Why AI Coaching Matters Now Teams don’t just need more training. They need continuous practice, personalized reinforcement, and actionable feedback that adapts to real-world challenges. AI coaching provides: Safe, realistic practice for high-pressure situations Instant feedback and improvement guidance Reinforcement that turns learning into habit Scalable training across entire organizations When teams practice more, they perform better — faster ramp times, higher productivity, improved customer experiences, and stronger leadership. How Insight7 Makes AI Coaching Actionable At Insight7, we make AI coaching practical and measurable. Our platform: Evaluates calls and interactions across Sales, Customer Service, and Leadership Identifies skill gaps and provides targeted improvement suggestions Delivers scenario-based simulations and roleplays Reinforces skills continuously to ensure long-term retention Insight7 helps you move from theory to real-world impact, helping organizations train smarter, retain knowledge longer, and improve performance faster.
Insight7 Becomes Official Zoom Partner to Deliver Instant AI Powered Call Analytics
GAINESVILLE, FLA., October 27, 2025 – Insight7, an AI powered conversation intelligence platform, announced it has achieved official Zoom Partner status, marking an elevated relationship that expands the reach and capabilities of its call analytics solution for Zoom users worldwide. This strategic partnership enables organizations using Zoom to seamlessly access Insight7’s advanced call analytics platform, which transforms customer conversations into instant scorecards, targeted coaching insights, and actionable business intelligence, without manual review effort. “Becoming an official Zoom partner represents a significant milestone in our mission to help teams extract maximum value from every customer conversation,” said Odun Odubanjo, CEO and Co-founder at Insight7. “Zoom users can now leverage our AI powered platform to scale quality assurance, accelerate coaching, and drive measurable improvements in customer satisfaction and revenue, all while maintaining the seamless workflows they rely on.” Automated Intelligence for Customer Teams Insight7 automates call analytics for rep performance evaluation, customer insights, and team effectiveness at scale, scoring them for quality, surfacing coaching opportunities, and highlighting patterns tied to revenue, satisfaction, and retention. Dashboards make it easy to track team performance, spot compliance risks early, and pinpoint where training is needed. With Insight7, Zoom users can: Improve Quality Assurance: Replace random QA samples with full call evaluation. Automatically flag risky behavior, silence, sentiment shifts, and resolution gaps. Improve Coaching & Training: Detect underperformance early and deliver targeted coaching based on real interactions. Scale Sales & CX: See what top performers do differently and replicate it across the team. Track Trends Over Time: Use dashboards to monitor performance, sentiment, silence, and compliance signals, at a glance. Insight7 integrates with Zoom, Google Meet, and other major platforms, so insights flow seamlessly into existing workflows. Insight7’s partnership status with Zoom is now active, and organizations can learn more by visiting https://partner.zoom.com/solutions/insight7/. ABOUT INSIGHT7 Insight7 is the developer of an AI-powered conversation intelligence platform built for customer-facing teams. Designed to support quality assurance, performance evaluation, coaching, and compliance use cases, Insight7 helps organizations turn thousands of customer calls into actionable insights. Built for everyday business users, it empowers cross functional teams to evaluate conversations at scale, drive continuous improvement, and make faster, smarter decisions. Founded by former Shopify product leader Odun Odubanjo, Insight7 is based in Gainesville, Florida, with a globally distributed team. Learn more at www.insight7.io.
Insight7 Launches Call Analytics 2.0: AI Powered Analytics For Modern Customer Teams
GAINESVILLE, FLA, Oct 22, 2025, Insight7 a leading provider of call analytics solutions, today announced the launch of Call Analytics 2.0, an AI-powered coaching platform designed to help customer success, support, and sales teams extract actionable insights from every customer conversation without adding manual review time. For years, customer facing teams have struggled with an avalanche of call data but minimal insight. Call recordings accumulate in systems, critical moments are forgotten, and managers spend countless hours reviewing calls without systematic improvement in team performance. Call Analytics 2.0 addresses this challenge by transforming every customer interaction into a live feedback loop that reveals performance patterns, coaching opportunities, and skill gaps in seconds. “Traditional call analytics tools tell you what happened, but they don’t tell you what to do about it,” said Odun Odubanjo, CEO and Co-founder at Insight7. “Call Analytics 2.0 is fundamentally different, it’s an AI coach built directly into your call stack that provides personalized, actionable guidance for every team member while giving managers complete visibility into team performance and trends.” Key Features and Capabilities AI-Powered Coaching Tips: Receive personalized, AI-generated feedback tailored to individual coaching styles and each representative’s specific development areas. Review & Coaching Assessments: Evaluate calls side by side with comprehensive performance tracking that identifies skill gaps and measures improvement over time. Collaborative Workflows: Enable team collaboration with integrated notes, comments, and follow-up tracking directly within call recordings. Dedicated Rep Logins: Provide every team member with personalized dashboards and self-directed training resources. Global Dashboards: Deliver enterprise-wide visibility into insights, trends, and performance metrics across entire organizations. Intelligent Alerts: Automatically detect and notify managers of key moments, compliance issues, or critical situations requiring immediate attention. Automated Team Workflows: Seamlessly integrate with existing tech stacks to trigger CRM updates, create support tickets, and distribute insights across platforms. HIPAA Compliance: Ensure secure handling of healthcare and other sensitive data with enterprise-grade security and compliance features.Call Analytics 2.0 is available immediately for customer success, support, and sales teams. Organizations interested in learning more can visit Insight7 ABOUT INSIGHT7 Insight7 is the developer of Call Analytics 2.0, an AI powered conversation intelligence platform built for customer teams. Designed to support a wide range of use cases, including quality assurance, performance evaluation, coaching, and compliance, Insight7 helps organizations turn thousands of customer calls into actionable insights. Built for everyday business users, the platform empowers cross functional teams to evaluate conversations at scale, drive continuous improvement, and make faster, smarter decisions. Founded by former Shopify product leader Odun Odubanjo, Insight7 is based in Gainesville, Florida, with a globally distributed team. Learn more at www.insight7.io.
How To Scale Interview Quality with AI Call Evaluation: Fresh Prints’ Success Story
Running hundreds of interviews every month is a challenge for any fast-growing company — especially when hiring at scale. For Fresh Prints, a custom apparel startup that recruits and trains student entrepreneurs to run campus-based businesses, the challenge was massive. Their growth team reviews over 700 recorded Loom interviews every month, evaluating each candidate’s engagement, clarity, and cultural fit. Keeping these evaluations consistent — and spotting red flags across such a high volume of calls — was nearly impossible. That’s when they turned to Insight7’s AI-powered call evaluation to streamline and scale their QA process. The Challenge: Scaling Interview Evaluation Across Hundreds of Calls Fresh Prints’ talent model depends on selecting the right student entrepreneurs, people who can sell, lead, and represent the brand on their campuses. Before Insight7, the growth team had to manually review hundreds of interview recordings, taking notes and scoring candidates by hand. With over 700 interviews each month, the workload quickly became unsustainable. “Running hundreds of interviews every month used to be a huge challenge for us,” Santiago Villaronga shared. “Keeping evaluations consistent and spotting red flags across many interviews was nearly impossible.” The process slowed down hiring decisions, made feedback inconsistent across evaluators, and introduced risk, good candidates could slip through the cracks simply because there wasn’t enough time to review every call thoroughly. The Solution: AI-Powered Interview Evaluation with Insight7 To solve the problem, Fresh Prints adopted Insight7, integrating it directly with Loom, their existing call recording tool. “Since adopting Insight7, our QA process has completely changed. It integrates seamlessly with Loom, automatically pulling in recordings and applying our customer evaluation criteria.” Instead of relying on manual reviews, Insight7 now automatically analyzes every interview using Fresh Prints’ evaluation rubrics. It assesses factors like candidate engagement, clarity, and cultural fit, surfacing patterns and potential concerns without requiring the team to listen to full calls. “We can now analyze interview quality at scale without listening to every minute of our call. Insight7 surfaces trends, flags red flags, and delivers actionable coaching insights in a fraction of the time.” The Impact: Quality, Fairness, and Scale The results have been transformative. Fresh Prints’ growth team now evaluates hundreds of interviews with speed, accuracy, and consistency, all while maintaining fairness across candidates. With Insight7: QA reviews are automated, ensuring every interview is evaluated with the same criteria. Red flags are identified instantly, enabling faster hiring decisions. Actionable insights are delivered automatically, helping improve interviewer performance. The team saves hundreds of hours every week, freeing them to focus on scaling recruitment instead of manual analysis. “It’s fast, accurate, and saves our team hundreds of hours every week, giving us confidence to keep scaling hiring without sacrificing quality or fairness.” Why This Matters for Talent and Growth Teams For any organization running high-volume interviews, AI-powered call evaluation offers a way to scale quality and fairness simultaneously. With tools like Insight7, hiring and QA teams can:Analyze hundreds of calls instantly without manual effortMaintain consistent evaluation standards across all interviewersIdentify trends and red flags early in the processFree up time for strategy, training, and candidate engagement Conclusion Fresh Prints’ journey shows how AI call evaluation doesn’t just make interview analysis faster, it makes it smarter. By integrating Insight7 into their QA process, they’ve transformed hiring from a manual, time intensive bottleneck into a data-driven, scalable, and fair system. The result? A growth team that’s confident, consistent, and ready to scale, without ever compromising on quality. ” Frequently Asked Questions How does AI call analytics help recruitment teams?It automates call reviews, applying consistent evaluation rubrics across interviews while highlighting red flags and improvement areas. Does Insight7 work with Loom?Yes. Insight7 integrates seamlessly with Loom to pull recordings automatically for analytics and insight generation. Why is automation important in hiring QA?It ensures fairness, speeds up evaluation, and enables recruiters to make data-driven hiring decisions without wasting hours on manual review.
How To Scale Research Evaluation with AI Call Analytics: Riggs Partners’ Success Story
Scaling research evaluation across multiple projects and clients can quickly become overwhelming.Riggs Partners, a purpose-driven brand and communications agency, runs dozens of interviews, focus groups, and stakeholder calls each month, each packed with insights that guide strategic decisions. But their process for extracting insights from these calls was slow, manual, and time-consuming. Before adopting AI, researchers spent days transcribing, printing, and manually highlighting interviews to identify key quotes and themes. Traditional methods simply couldn’t keep up with the growing volume of conversations and deadlines. That’s when Riggs Partners turned to Insight7’s AI-powered call analytics to transform how they evaluate research conversations. The Challenge: Turning Hours of Calls into Actionable Research Insights Before using Insight7, the Riggs team faced a familiar bottleneck: manually turning qualitative data into usable insights. Kevin Smith, Partner at Riggs Partners explains: “Before we got Insight7, I would spend days getting recordings transcribed, printing out transcripts, reading them, highlighting interesting quotes, aggregating those quotes into insights, and putting all of that into a PowerPoint.” This manual approach wasn’t just slow, it limited how quickly insights could be shared internally or presented to clients. For a firm built on collaboration and strategy, this process made it hard to stay agile and responsive. And with multiple team members often contributing to the same project, organizing and updating research findings became even harder. The Solution: AI Powered Research Evaluation with Insight7 Everything changed once Riggs Partners adopted Insight7. “Now, I just upload the recordings into Insight7 and all of that work is done for me in a matter of minutes,” Kevin shared. “It’s a great tool.” With Insight7, Riggs Partners could instantly upload recorded interviews and get structured insights, highlights, and themes — without spending days manually reviewing each transcript. Insight7’s flexibility also proved valuable: “Being able to add to and take away and change some of the inquiries on the data because I’ll have different co-workers that have different questions, it’s nice to be able to go back in. It’s not a one-shot and you’re done scenario.” This meant the team could adapt their research evaluation dynamically, exploring new angles, refining insights, and collaborating seamlessly across projects. The Impact: From Days of Work to Minutes With Insight7, Riggs Partners reduced a process that used to take several days down to minutes. What once required manual transcription, highlighting, and synthesis is now automated, letting researchers focus on strategic storytelling rather than administrative work. Key benefits achieved: Faster turnaround: Insight generation in minutes instead of days. Collaborative flexibility: Multiple team members can revisit and refine data. Consistent quality: No more variation in how insights are captured or presented. Why This Matters for Research and Strategy Teams For any organization handling large volumes of qualitative data, from agencies to in house research teams, the Riggs Partners story highlights how AI powered evaluation changes the game: Eliminate manual transcription and note-takingGenerate structured insights instantlyCollaborate dynamically across research projectsScale analysis without sacrificing depth or accuracy By automating the grunt work, teams can focus on what really matters, telling better stories, faster. Conclusion Riggs Partners’ journey shows that AI call analytics isn’t just for sales or support teams, it’s a powerful ally for research and strategy professionals, too.With Insight7, they’ve transformed tedious, manual analysis into a fast, flexible, and collaborative process — all while maintaining the depth and nuance their work demands. ” Frequently Asked Questions Do researchers still need to transcribe calls manually?No. Insight7 automatically transcribes and evaluates calls, surfacing key quotes and insights within minutes. Can multiple team members collaborate on the same project?Yes. Teams can update data and explore different research angles without starting over. Why is AI powered call analytics valuable for research teams?It enables teams to evaluate qualitative data faster, extract richer insights, and collaborate seamlessly, all without the manual burden of traditional analysis.
