This episode shows tech advisors how to build a compact, actionable AI-driven partner-matching system that solves vendor overwhelm, uncovers higher-margin opportunities, and creates a compelling, sellable differentiation. In a focused interview, Bob walks a practitioner through the end-to-end approach: selecting the right signals (contracts, usage, vertical fit), assembling reliable public and CRM data sources, designing a simple scoring model, and wiring outcome-driven automations (targeted outreach, proposal snippets, and commission tracking). Listeners will get a clear step-by-step blueprint they can pilot in a single week, concrete KPIs to measure success, and sample scripts that convert recommendations into signed deals. This is practical, no-fluff guidance for advisors who want to stop guessing about vendors and start recommending—and monetizing—the best options for each client.

Bob interviews a practitioner who built an "AI Win/Loss Decoder" — a lightweight, revenue-focused pipeline that ingests call transcripts, proposals, emails, and CRM notes to reveal why deals won or lost and then auto-generates repeatable playbooks, objection responses, and next-step sequences. This episode walks through exact data sources, simple labeling approaches, prompt patterns, and human-in-the-loop checks so listeners can start with 50–200 historical deals and get meaningful insights fast. You’ll hear concrete examples of playbooks one advisor deployed, the validation metrics they used, and a pragmatic rollout plan that fits a solo operator or small team. The conversation teaches a replicable method, solves the mystery of inconsistent sales outcomes, and gives a clear, actionable path to turn existing deal history into predictable revenue.

This episode teaches a concrete, step-by-step playbook for building a voice-first AI SDR that converts cold outreach into booked meetings for technology advisors, IT providers, and telecom agents. Bob interviews a practitioner who built a simple stack—AI script generator, TTS voicemail drops, short personalized follow-up SMS, and booking automation—and reduced outbound friction while lifting callback rates. Listeners will hear exact prompts, cadence, and quality controls that work without heavy engineering. You’ll get a 30/60/90 day pilot plan, measurable benchmarks to track, and a ready-to-run template you can test in a week. The episode solves the top pain point—lead generation—by showing how to scale outreach with fewer hours and predictable outcomes, and it moves you to action with clear next steps and a pilot checklist. Visit acquasition.ai/edge to download the templates and pilot guide.

Most technology advisors live and die by meetings — but getting a prospect to say yes to a meeting is the hardest step. In this episode Bob interviews a practitioner who built a repeatable ‘7‑Minute Prospect Audit’ that turns public signals into a concise, defensible one‑page audit you can deliver before a call. Listeners will get a step‑by‑step framework for sources to check (public job posts, vendor footprints, recent outages, LinkedIn signals, tech stack hints), the exact AI prompts and templates to synthesize findings into a persuasive pocket pitch, and the short email/LinkedIn sequences that reliably book meetings. This episode teaches a practical, low-cost pilot you can run this week, solves the top lead-generation bottleneck by creating conversation-ready deliverables, and moves you to action with a 30-day testing plan that fits solo operators and small teams.

Many technology advisors know AI can accelerate their business but worry about legal, privacy, and ethical landmines. In this episode Bob Bevilacqua interviews a practical AI governance expert to deliver a lightweight, sellable governance playbook built specifically for tech advisors. Listeners will get a five-step framework they can implement without hiring a legal team, a 2-week pilot they can bill, and word-for-word scripts that turn compliance into a competitive advantage. The episode teaches how to inventory AI use, capture client consent, enforce data hygiene, create transparent client-facing disclosures, and set escalation rules for sensitive decisions. It solves the real problem of paralysis-by-uncertainty by offering templates, low-effort controls, and measurable outcomes advisors can put into practice Monday morning. By the end listeners will have three immediate actions and a checklist to start packaging governance as a revenue-generating service.

In this interview Bob talks with a founder of an AI demo automation tool and a veteran technology advisor who used it to convert cold outreach into booked meetings. The episode teaches a step-by-step workflow for creating ‘zero-prep’ demos: supply minimal client context, product highlights, and environment cues to an AI that returns a 5–7 minute demo script, talking points, a short live walkthrough plan, and a two-slide follow-up one-pager. We cover concrete prompts, the minimal data sources you need, simple integrations with calendar and meeting platforms, common objections and guardrails to preserve credibility, and a 30-day pilot any advisor can run without hiring designers or engineers. Listeners walk away with templates, a checklist, and a safe rollout plan that produces immediate lift in show-rates and demo-to-close velocity.

This episode teaches a compact, repeatable system: use lightweight AI tools as a daily sales coach to rehearse discovery calls, generate tailored rebuttals, score your talk tracks, and create ready-to-send follow-ups. Bob interviews a practitioner who built a simple AI-driven routine that transformed cold outreach and follow-up for a small MSP. Listeners will get an exact 15-minute workflow, templates for discovery openers and objection responses, and a checklist to integrate AI coaching into an advisor’s calendar and CRM. The focus is practical: minimal setup, measurable lift in show rates and conversion, and safeguards to keep conversations authentic and compliant. If you’re time-starved but need better sales execution, this episode turns practice into consistent performance — one short, high-impact routine you can deploy this week.

Most tech advisors write proposals the same way they’ve always done — manual, generic, and easy to ignore. In this episode Bob interviews a guest who built an AI-driven proposal and close-prediction system specifically for technology sellers. We teach an actionable, step-by-step approach: collect the minimum viable inputs that power personalization, embed pricing rules and margin guardrails, add a lightweight predictive model that scores close probability, and automate follow-up sequences based on score and buyer behavior. Listeners will get a feasible 30-day pilot plan they can run with existing CRM and document tools, scripts for higher-converting executive summaries, and a repeatable rollout checklist that preserves margins and compliance. This episode solves a real problem — too many proposals, too few closes — and moves advisors one concrete step closer to measurable revenue.

Many technology advisors leave real money on the table because vendor portals, billing systems, and contract footnotes are noisy, inconsistent, and time-consuming to reconcile. In this practical interview, Bob Bevilacqua and a guest who runs commission-recovery projects walk through a repeatable, low-tech + AI approach you can run in 30 days. You’ll learn which data sources to prioritize (vendor portals, invoices, CRM, contracts), simple NLP and RPA patterns that surface mismatches, a lightweight human-in-the-loop review workflow, and outreach language that turns findings into recovered commissions or credits. This episode teaches a concrete playbook, solves the immediate problem of unseen revenue leakage, and moves listeners to a clear next step they can implement without hiring a data scientist. Expect real templates, measurable KPIs to track, and a pilot plan built for solo operators and small teams.

Most technology advisors know Quarterly Business Reviews should be revenue moments — yet they rarely run them consistently or well. In this episode Bob interviews a practitioner who built an AI-assisted QBR workflow that automates data collection, crafts concise, client-specific insights, schedules the meeting, and produces prioritized upsell plays. Listeners get a practical, low-tech blueprint they can pilot in weeks: what data to pull (billing, tickets, usage, renewals), how to prompt AI to write persuasive talking points and one-page executive summaries, rules for human-in-the-loop checks, and an automated follow-up sequence that converts QBRs into proposals. The conversation focuses on simple integrations, measurable KPIs (show rate, expansion rate, churn reduction), templates Bob uses with advisors, and a 5-client pilot plan. By the end you’ll have an actionable roadmap to stop leaving revenue on the table and run QBRs that scale without losing the human touch.