AI Tools for Sales Pros

Sean O'Shaughnessey
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AI Tools for Sales Pros helps B2B sales professionals put artificial intelligence and automation to work in practical, real-world ways. Each episode explores use cases across prospecting, deal management, account growth, and revenue operations. Listeners gain actionable insights on how to streamline workflows, improve efficiency, and scale revenue by combining the power of AI with smart automation.

  1. 6D AGO

    The Last Mile in Sales AI: How to Scale Revenue Without Losing Trust

    Episode Summary In this episode of AI Tools for Sales Pros, Sean O’Shaughnessey breaks down the “Last Mile” problem in modern selling: AI can assemble the first 80% of the work, but only a human expert can deliver the final 20% that protects trust, margin, and outcomes. He argues that the real productivity crisis in B2B sales is not effort, but misallocation—top sales talent is buried in administrative work instead of revenue generation. The episode introduces a practical operating model where deterministic automation handles fixed truths and process control, while AI accelerates messaging and drafting. The result is faster execution, better sales management discipline, and more time for the trust-building conversations that drive sales success. Major Highlights The “Last Mile” principle: artificial intelligence is an accelerator, not an autopilot. Human judgment is still required to validate context, edge cases, and risk.Why productivity is stuck: many B2B teams still spend roughly one-third of time on revenue generation and two-thirds on internal sales processes and admin overhead.The “Artisan Trap” vs. the “New Way”: handcrafted work from scratch is being replaced by cognitive prospecting, listening posts, and autonomous workflows.Deterministic vs. Non-Deterministic outputs: high-risk outputs (pricing, contracts, compliance) require deterministic controls; AI should support formatting, messaging, and personalization.Automation + AI hybrid model: rules-based automation supplies verified data, AI shapes language, and final checks enforce consistency and accuracy.Revenue management implication: the objective is not more content—it is more high-quality customer conversations and better conversion velocity.Trust and value selling: relationship depth, multi-threading, and repeated high-value interactions are still core drivers of win rates and profitable growth.Real-world lesson: AI can flag opportunities, but business acumen determines timing, sequencing, and whether an account is ready for expansion.The “5-Minute Value-Add” mindset: AI removes blank-page work so reps can focus on strategy, messaging quality, and customer-specific relevance.Leadership call to action: evaluate current AI deployments as systems for revenue generation, not isolated tools for novelty or speed alone.Action Items for This Month Run a Last Mile audit: identify where your team is accepting AI output without deterministic checks, then define human approval points by workflow stage.Classify outputs by risk: separate “must-be-perfect” assets (quotes, pricing, legal language) from “can-be-variable” assets (outreach drafts, summaries, internal notes).Build one production workflow: trigger a stage-based sequence in your CRM that pulls fixed data, drafts AI messaging, and validates critical fields before send.Reclaim selling time: track how many hours are shifted from admin work to live customer conversations and tie that shift to pipeline movement and win rates.Create a manager review cadence: compare AI recommendations vs. manager judgment weekly to sharpen forecast quality and coaching priorities.Pilot one-account scaling: prove the workflow on a single target account, then expand to 25 and 100 accounts only after accuracy and consistency thresholds are met.Resources: Kendra Ramirez article, "Why Last Mile Knowledge Still Matters in the Age of AI"Whiskey is for Closers podcastJoin the B2B Sales Lab B2B Sales Lab is a private, member-led community for sales professionals who want actionable insights, not theory. It’s a space to ask real questions, share proven practices, and connect with others who are serious about improving revenue performance. Designed and led by veteran sales leaders, the Lab is where strategy meets execution. Join us at b2b-sales-lab.com. Custom theme music for AI Tools for Sales Pros created by Casey Murdock

    22 min

  2. FEB 2

    Sixty-Second Slide Review: Use AI to Build Better Slide Decks and Win Back Selling Time

    Episode Summary It’s late Thursday, and you’re stuck building a “pivotal” executive deck with no marketing support, no design help, and no extra hours—so you pay the hidden sales tax: administrative drag that steals selling time and dulls your edge. In today’s B2B environment, the problem isn’t effort; it’s the Tollbooth Effect—manual CRM updates, document hunting, and slide formatting that cools deals and slows revenue generation. This episode lays out a practical AI-augmented productivity suite approach that turns you into an editor-in-chief: AI handles structure and mechanics, you handle judgment, tone, and human impact. The result is faster, cleaner messaging, stronger sales processes, and more time for real revenue management work. Major Highlights The “sales tax” is real: administrative drag and internal processes consume the majority of a seller’s week, starving revenue-generating activity and limiting Sales success.The Tollbooth Effect: momentum from discovery dies when the system forces manual labor—CRM hygiene, notes cleanup, and deck formatting—right when you should be advancing the deal.The Producer Mindset shift: your value is strategy, business acumen, and human connection; technology executes content creation and formatting at machine speed.The workflow: use tools like Microsoft Copilot or Gemini for Workspace to turn transcripts and notes into structured inputs; then generate a slide-by-slide narrative from a strategic brief.The human-in-the-loop protocol: you are not the author, you are the editor—review each slide for accuracy, tone, and the emotional reality behind the buyer’s problem.The Sixty-Second Slide Review: compress a four-hour deck build into a ten-minute strategic review, improving responsiveness and increasing pipeline velocity.Tool paths across ecosystems: PowerPoint automation via VBA generation, Google Slides creation via Gemini Canvas with export, and Keynote creation via AppleScript—same outcome, different environment.Why it matters: reclaiming selling time compounds into higher output, better value selling conversations, and a visible “halo effect” from professional, fast follow-up.Clean data is the multiplier: “always-on hygiene” turns your CRM into a trustworthy source of truth, improving the accuracy of AI-generated outputs and strengthening customer confidence.AI fluency is not coding: it’s orchestrating tools to produce insight and execution—practical sales strategies that let you move faster without losing the human center.Action Items for This Month Adopt the Sixty-Second Slide Review: generate a first draft deck with AI, then spend one minute per slide fixing truth, tone, and buyer-specific messaging.Replace blank-screen deck creation with a Strategic Brief: prospect context, three outcomes for the meeting, and the proof points you want to land—then have AI produce the slide outline.Standardize your “post-call pipeline”: transcript or recap first, AI extraction second, deck generation third. Protect momentum by eliminating the Tollbooth Effect.Clean one critical CRM field set (next step, primary pain, decision criteria): your AI outputs are only as credible as your data foundation.Build one reusable deck skeleton: problem framing, impact, approach, proof, next steps. Let AI customize the middle based on the meeting transcript and industry.Join the B2B Sales Lab If you’re trying to keep up with AI-driven workflows without getting lost in hype, join the B2B Sales Lab. B2B Sales Lab is a private, member-led community for sales professionals who want actionable insights, not theory. It’s a space to ask real questions, share proven practices, and connect with others who are serious about improving revenue performance. Designed and led by veteran sales leaders, the Lab is where strategy meets execution. Join us at b2b-sales-lab.com Custom theme music for AI Tools for Sales Pros created by Casey Murdock

    16 min

  3. JAN 26

    From Gut Feel to Evidence: AI Pipeline Management That Cleans Up Commit and Closes Faster

    Episode Summary Zombie deals are the quiet killer of forecast accuracy and sales capacity. When stalled opportunities sit in the pipeline, they distort revenue management, waste coaching time, and create false confidence with executives. This episode argues for a shift from intuition-driven pipeline reviews to evidence-based sales management using AI signals from real buyer activity. The outcome is cleaner forecasting, sharper coaching, and more revenue generation by reallocating time away from dead deals and toward real opportunities. Major Highlights Why “busy” is often a polite version of “dead,” and how zombie deals poison forecasting long before they get marked Closed-Lost.The paradox of pipeline discipline: more fields, more interrogation, and more admin drag can reduce selling time and hurt Sales success.Moving from the Intuition Era to the Evidence Era: treating revenue as a measurable business process, not a vibes-based debate.How AI-powered revenue intelligence tools (examples include Clari and Gong) create an objective view of pipeline health by monitoring digital activity, engagement velocity, and deal risk patterns.The sales leader’s role shift: stop being a pipeline inspector and become a performance coach using evidence, not rep narratives.Risk dashboards and deal hygiene scoring: coaching off signals like economic buyer silence, stakeholder drop-off, and next-step absence.The Tollbooth Effect: small administrative steps that compound into massive drag across sales processes, and how AI helps remove friction.Why data quality is non-negotiable: high-performing AI depends on clean CRM data, supported by always-on hygiene approaches and tools like Cloudingo or Dedupely.Emotional forecasting with conversation intelligence: using Natural Language Processing to detect sentiment trajectory, stakeholder flags, and “paper process” risk.The strategic point: AI is not a replacement for leadership judgment; it is judgment amplification that improves business acumen by surfacing truth earlier.Action Items for This Month Audit five deals that have been in the same stage for more than 60 days. Identify which ones are zombie deals using evidence, not opinions.For each deal, answer three questions: When was the last inbound email from the prospect? How many unique stakeholders have met with you in the last 30 days? Is there a confirmed next step on the calendar?Rewrite your coaching questions from “Is it still alive?” to “What evidence says this is progressing, and what is our plan to re-engage the missing stakeholder?”Create a simple deal hygiene scorecard your team can follow weekly: engagement frequency, economic buyer involvement, next-step date, and stakeholder coverage.Start a data hygiene initiative. If duplicates and missing fields are normal in your CRM, prioritize cleanup so AI signals can work reliably.Pick one workflow to modernize with AI this month: risk dashboards for commit deals, call sentiment review for late-stage opportunities, or adaptive re-engagement sequences for stalled deals.Join the B2B Sales Lab If you are working to modernize forecasting, tighten sales processes, and improve sales management without drowning your team in admin work, you do not need to solve it alone. B2B Sales Lab is a private, member-led community for sales professionals who want actionable insights, not theory. It’s a space to ask real questions, share proven practices, and connect with others who are serious about improving revenue performance. Designed and led by veteran sales leaders, the Lab is where strategy meets execution. Join us at b2b-sales-lab.com Custom theme music for AI Tools for Sales Pros created by Casey Murdock

    18 min

  4. JAN 20

    Generate Custom Proposals in Seconds from CRM Data

    Episode Summary Most B2B teams are still paying a hidden “sales tax” every time a proposal gets requested: hours of document assembly, copy-paste errors, and slow internal processes that kill deal momentum. This episode reframes proposal creation from an artisan craft into Strategic Response Management (SRM), where proposals become a dynamic asset and the rep becomes the producer, not the typist. Using AI and automation as the nervous system of your sales stack, you can move from “Friday afternoon panic” to a 60-second executive review. The outcome is simple: faster response, cleaner Messaging, stronger Value selling, and more consistent Revenue generation. Major Highlights The real problem isn’t proposals. It’s the momentum gap created when internal processes delay a buyer-ready moment.Why “The Artisan Trap” is outdated: 80% of most proposals are recycled boilerplate masquerading as personalization.Strategic Response Management (SRM): proposals as a continuously improved system, not a static Word document.How the modern sales stack works as a “nervous system”: CRM status change triggers automated assembly, data pulls, pricing, and version control.Where artificial intelligence actually belongs: rewriting the executive summary using the prospect’s own words and tailoring proof points, without breaking brand standards.The “60-Second Review” operating model: reps edit and approve instead of starting from a blank page.Context-rich alerting: interactive proposals that show engagement data so sales management can coach deal strategy instead of proofreading.Standards before Automation: AI amplifies what you already do, so sloppy Sales processes just get faster.Impact examples: faster proposal creation, improved win rates, and better Revenue management through speed and relevance.The Document Friction Audit: a simple way to quantify the hours lost per deal and identify what to automate first.Action Items for This Month Run a Document Friction Audit on your last three proposals. Time the work from “call ends” to “proposal sent,” including file hunting and formatting.Identify the reusable 80%. List the recurring blocks you copy-paste (pricing tables, security language, implementation plan, case studies).Standardize one block before you automate it. Pick a single high-usage section (pricing or case studies) and define the “best-in-class” version your team will reuse.Create a simple trigger in your CRM: when a deal moves to “Proposal Requested,” confirm what data must be present (pain points, timeline, stakeholders, next step).Define your 60-second review checklist: accuracy of names, scope, pricing, proof points, and the executive summary narrative.Coach from engagement data: if a buyer spends time on pricing but skips implementation, address that concern directly on the next call.Join the B2B Sales Lab This document problem is bigger than admin work. It’s a sales capacity issue, a Sales success issue, and a Business acumen issue. B2B Sales Lab is a private, member-led community for sales professionals who want actionable insights, not theory. It’s a space to ask real questions, share proven practices, and connect with others who are serious about improving revenue performance. Designed and led by veteran sales leaders, the Lab is where strategy meets execution. Join us at b2b-sales-lab.com.

    14 min

  5. JAN 12

    Call Analysis and Coaching with AI (Part 2: Building a Feedback Loop)

    Episode Summary You can buy the best conversation intelligence platform on the market and still get zero behavior change. That’s the Coaching Chasm: data exists, but the field doesn’t improve because managers don’t have time, feedback arrives too late, and reps experience AI as surveillance instead of development. This episode lays out a new coaching philosophy: move from manual inspection to automated orchestration using AI-driven skill scorecards, best-in-class “golden moments,” and focused training sprints. The outcome is a measurable feedback loop that improves sales processes, accelerates ramp time, and connects skill improvement directly to revenue generation. Major Highlights The Coaching Chasm: why “insights” die in dashboards and never translate into sales success or behavior change. The cultural failure mode: when AI feels like a “gotcha,” reps get defensive and sales management loses trust and momentum. The shift from manager-as-detective to manager-as-performance-architect: automated orchestration beats manual inspection every time. How AI changes coaching dynamics: objective data reduces opinion battles, faster feedback increases relevance, and trend analysis supports development conversations. Case example (Andela): using AI scorecards to drive agenda-setting adoption from 17% to 49% in two weeks and compress cycle time through better process adherence. Case example (Appen): using curated call snippets to cut onboarding time in half and transfer technical and renewal Messaging quickly. Action Items for This Month Pick 3–5 skills that correlate with wins and define them as measurable scorecard metrics (not vague competency labels). Establish a baseline for each skill and set automated weekly reporting to track trends, not one-off call critiques. Build your first Best-in-Class Library: curate 10–15 “golden moments” as short clips organized by skill (discovery, objection handling, Value selling, pricing pushback, competitor mention). Run one training sprint (2–4 weeks) focused on a single skill, supported by daily micro-learning and scorecard-based monitoring for adoption. Rewrite your coaching framing: replace “you’re below average” with “your metric improved X% month-over-month” to reduce defensiveness and increase ownership. Create an ROI narrative: connect skill lift to conversion rate improvement, cycle time compression, and ramp time reduction to justify ongoing investment in AI-enabled sales processes. This week, pilot the Golden Moment: pull one 60-second clip from a top rep that demonstrates elite Messaging or execution, share it with the team, and explain why it worked. Join the B2B Sales Lab If you’re trying to turn conversation intelligence into real performance improvement, you don’t need more dashboards. You need a repeatable coaching system and peers who’ve already pressure-tested it. B2B Sales Lab is a private, member-led community for sales professionals who want actionable insights, not theory. It’s a space to ask real questions, share proven practices, and connect with others who are serious about improving revenue performance. Designed and led by veteran sales leaders, the Lab is where strategy meets execution. Join us at b2b-sales-lab.com

    15 min

  6. JAN 5

    Call Analysis and Coaching with AI (Part 1: Core Coaching Skills)

    Episode Summary You can’t coach what you don’t see, and most sales managers only hear a tiny fraction of their team’s calls. This episode introduces Augmented Coaching: using artificial intelligence and conversation intelligence to analyze every customer conversation and surface specific, teachable moments without adding hours to your week. You’ll learn how AI-driven insights like talk-to-listen ratio, question quality, and sentiment shifts turn coaching from gut feel into repeatable sales management. The outcome is simple: tighter sales processes, faster ramp, stronger messaging consistency, and more reliable revenue generation. Major Highlights The “coaching gap” problem: when managers review only a small percentage of calls, most rep behavior lives in a black box, and bad habits compound.Why this is a capacity issue, not a willpower issue: managers get buried in forecasts, deal support, admin work, and internal meetings.The shift from intuition-era coaching to Augmented Coaching: AI monitors and analyzes; the manager coaches the moments that matter.What conversation intelligence platforms do (examples include Gong and Chorus.ai): record, transcribe, and analyze calls to produce objective coaching data.Creating a “collective sales brain”: capture what top performers do (phrasing, objection handling, discovery patterns) and scale it across the team. The “Game Tape” approach: use short clips (often 2 minutes or less) to coach discovery, agenda-setting, objection handling, and value selling.Business impact examples discussed: improved win rates, reduced ramp time, and reclaiming manager hours through automation and targeted coaching.Tool selection and architecture: conversation intelligence belongs in the Optimization and Learning layer, supported by a solid data foundation and intelligence layer.Budget-friendly options: lighter-weight tools like Fireflies.ai, Otter.ai, or Fathom can still provide transcription, recaps, and action-item capture.Call Libraries as a force multiplier: curated playlists of best-in-class calls accelerate onboarding and standardize sales strategies across the team.Change management guidance: position AI as coaching support, share team trends before individual call-outs, and celebrate improvement publicly to build trust.The leadership upgrade: stop being a pipeline inspector and become a performance coach focused on the skills that drive sales success and revenue management.Action Items for This Month Audit your coaching coverage: calculate total team calls last month and the percentage you actually reviewed. Treat that percentage as a leading indicator for performance risk.Pick one skill to improve: agenda setting, discovery quality, objection handling, or messaging consistency. Avoid trying to “fix everything” at once.Run a small proof-of-concept: choose one rep and use a free trial tool to record five calls. Review talk-to-listen ratio and question quality before you listen to any recordings.Start a Call Library: save 3 examples of “great discovery,” 3 examples of “clean agenda-setting,” and 3 examples of “strong value selling.” Use them in onboarding and team huddles.Adopt the Game Tape Review cadence: schedule two five-minute reviews per rep per week using clips and metrics, not full-call listening sessions.Set expectations with the team: frame AI as a coaching accelerator, not surveillance. Share team-level trends weekly and recognize measurable improvement.Join the B2B Sales Lab B2B Sales Lab is a private, member-led community for sales professionals who want actionable insights, not theory. It’s a space to ask real questions, share proven practices, and connect with others who are serious about improving revenue performance. Designed and led by veteran sales leaders, the Lab is where strategy meets execution. Join us at b2b-sales-lab.com

    11 min

  7. 2025-12-29

    Admin Drag Is Killing Your Sales Capacity: Reclaim Selling Time Without Hiring

    Episode Summary Buying AI alone does not increase revenue. The real constraint in most B2B organizations is salesperson productivity, not tool availability, because reps spend too little time on revenue-producing work and too much time on administrative drag. This episode introduces the “Tollbooth Effect,” the buildup of small approvals, handoffs, and system tasks that quietly tax every deal and slow revenue generation. You’ll learn how to treat artificial intelligence as an architectural teammate, automate the input work, humanize the output, and prove impact through cycle time, win rate, and pipeline quality improvements. Major Highlights • Why executives are done funding “transformation” and are now asking the only question that matters: where is the revenue impact from AI? • The real productivity problem: most salespeople spend roughly a third of their week on revenue-producing work, while administrative drag consumes the rest. • The Tollbooth Effect explained: small, reasonable steps in isolation that become a system-wide tax on execution, deal momentum, and messaging quality. • Why adding headcount breaks in 2026: rising cost, fragile retention, and top performers resenting being turned into well-paid administrators. • The core operating principle: automate the input and humanize the output. Use AI to remove research, data entry, record hygiene, routing, and documentation burdens so humans can focus on judgment. • A strategy-first approach to artificial intelligence: treat AI as an operating layer that keeps your revenue engine consistent, not a content factory that produces more noise. • The “sales nervous system” model: an autonomic layer handles repetitive functions reliably, while reps stay focused on decisions, stakeholder navigation, value selling, and next-step commitments. • The deal-decay moment most teams ignore: the gap after a call. Speed and structure in follow-up protect urgency, improves conversion, and strengthens revenue management. • The discipline prerequisite: AI amplifies your system. If your sales processes are fuzzy, your discovery is weak, and your stage criteria are unclear, AI will accelerate inconsistency. • Data hygiene as a revenue lever: always-on hygiene builds trust in the CRM, reduces double-checking, improves forecasting integrity, and restores selling speed. Action Items for This Month • Run an admin audit: identify the three repetitive weekly tasks that require zero creativity, zero empathy, and zero strategic thinking. Pick one to eliminate first. • Define standards before automation: tighten stage exit criteria, discovery requirements, and follow-up rules so sales management and coaching are consistent. • Fix the post-call gap: create a structured workflow that captures commitments, unresolved issues, stakeholders mentioned, and next steps immediately after meetings. • Simplify CRM requirements: capture only what drives revenue generation and decision-making, then automate the capture and routing of those fields. • Commit to always-on data hygiene: implement rules and tools that flag duplicates, enforce formatting, and detect record conflicts so the system stays trustworthy without “data days.” • Prove impact with outcomes: track selling time recovered, follow-up speed, cycle time changes, win rate movement, and pipeline quality rather than tool adoption metrics. Join the B2B Sales Lab If you are working through AI adoption and want practical help that improves sales productivity, you do not need more theory. You need peers, standards, and real operating examples you can put to work. B2B Sales Lab is a private, member-led community for sales professionals who want actionable insights, not theory. It’s a space to ask real questions, share proven practices, and connect with others who are serious about improving revenue performance. Designed and led by veteran sales leaders, the Lab is where strategy meets execution. Join us at b2b-sales-lab.com

    16 min

  8. 2025-12-22

    Instant Follow-Up: AI Meeting Recaps That Speed Up Deals and Clean Up Your CRM

    Episode Summary Most sales teams underestimate the hidden “sales tax” that hits after every good meeting: recaps, CRM updates, follow-up emails, and task creation that quietly kill momentum. In this episode of AI Tools for Sales Pros, we break down how artificial intelligence and AI meeting assistants can eliminate that post-call drag while improving accuracy, consistency, and professionalism. You’ll learn how to move from manual note-taking to an orchestrated workflow that produces a structured recap, action plan, and CRM updates in minutes. The result is better sales processes, faster follow-up, and a practical path to sales success without adding headcount. Major Highlights The real cost of post-meeting admin work: why most teams lose deal velocity after a “great call” and how that impacts revenue generation. The “sales tax” concept: how small frictions compound into hours of lost selling time and weaken revenue management. The shift in operating philosophy: stop treating reps like court reporters and move them into a Producer / Editor role focused on value selling and human connection. AI meeting assistants (examples: Fireflies.ai, Otter.ai, Fathom): transcription is the baseline, but structured extraction is where the leverage appears. Orchestration beats transcription: connecting transcripts to an automation platform (Make.com or Zapier) to produce structured outputs aligned to your sales strategies and sales management system. Prompting as a sales process tool: how to instruct an LLM to extract pain points, budget signals, stakeholders, competitive mentions, objections, and next steps with owners and dates. Human-in-the-loop protocol: why the system should draft the follow-up email but never auto-send, protecting trust and improving messaging quality. Self-healing CRM behavior: how structured AI outputs reduce missing data, improve forecast hygiene, and strengthen revenue management discipline. Ethics and consent: a practical, value-forward disclosure script that protects the relationship while using artificial intelligence responsibly. The “Post-Call Lag Check” audit: a simple way to measure your current performance baseline before investing in any tooling. Action Items for This Month Run a Post-Call Lag Check: time how long it takes (end of call to done) to send the follow-up email and fully update the CRM for three meetings. Record five calls using a meeting assistant trial: review transcript quality, speaker identification, and how well the tool captures action items. Use a methodology-based prompt: paste one transcript into ChatGPT or Gemini and extract pain points, budget details, stakeholders, objections, competitors, and next steps into a structured format. Adopt the Editor workflow: generate the follow-up email as a draft, spend 60 seconds editing for accuracy and tone, add one personalization detail, then send. Standardize your recap format: define a single executive-summary structure your team uses so customers receive consistent messaging and your sales processes become repeatable. Create CRM task automation rules: ensure every next step gets a due date, owner, and description so commitments don’t drift and sales success becomes predictable. Join the B2B Sales Lab If you want to implement these workflows without starting from scratch, join the B2B Sales Lab. B2B Sales Lab is a private, member-led community for sales professionals who want actionable insights, not theory. It’s a space to ask real questions, share proven practices, and connect with others who are serious about improving revenue performance. Designed and led by veteran sales leaders, the Lab is where strategy meets execution. Join us at b2b-sales-lab.com

    17 min
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About

AI Tools for Sales Pros helps B2B sales professionals put artificial intelligence and automation to work in practical, real-world ways. Each episode explores use cases across prospecting, deal management, account growth, and revenue operations. Listeners gain actionable insights on how to streamline workflows, improve efficiency, and scale revenue by combining the power of AI with smart automation.

Information

  • Creator
    Sean O'Shaughnessey
  • Years Active
    2025 - 2026
  • Episodes
    29
  • Rating
    Clean
  • Copyright
    © Sean O'Shaughnessey
  • Show Website
    AI Tools for Sales Pros