Many technology advisors sit on a goldmine of expansion revenue buried inside client systems — ticketing spikes, unused bandwidth, billing anomalies, or feature gaps — but they lack a repeatable way to find and act on those signals. In this episode Bob interviews a practitioner who built a lean, production AI ‘Opportunity Radar’ that connects CRM, helpdesk, billing and basic usage telemetry, scores signals with simple machine rules + a small LLM layer, writes tailored outreach, and auto-schedules 15‑minute discovery calls with human handoff. Listeners will get a step‑by‑step 30‑day pilot plan, the minimal data you need, sample outreach templates, realistic KPIs (meetings/week, conversion), and guardrails to protect margins and relationships. This is a tactical, implementable play for solo advisors and small MSPs who want to unlock predictable, low-effort expansion revenue without heavy engineering.

This episode teaches technology advisors a practical, low-effort way to convert cold prospects into qualified meetings by combining AI-driven outreach with human review. Bob interviews a practitioner who built a hybrid AI SDR for small tech firms: the episode breaks down the minimum data you need, the exact triggers and sequences that book meetings, prompt-and-script examples that sound authentic, and a measurable 30-day rollout you can copy. Listeners will walk away with a prioritized implementation checklist, simple KPIs to prove ROI, and a ready-to-run script set that requires about ten minutes of daily supervision. The focus is on actionable steps—no vendor hype—so solo advisors and small teams can automate repetitive outreach, reclaim lost time, and stop letting high-intent opportunities slip through. By the end, you’ll know what to build, what to test first, and how to scale without losing the human touch.

Most tech advisors treat partners as sporadic referrals instead of a predictable growth channel. In this episode Bob interviews a channel-ops leader who built an AI-driven co-sell engine that discovers complementary partners, scores fit and intent, automates outreach and follow-up, and handles deal handoffs and revenue-share workflows. You’ll get a concrete, step-by-step playbook you can implement in 30/60/90 days: how to identify high-opportunity partner types, lightweight datasets and signals to score fit, templates and automation flows that book joint meetings, and simple tracking to ensure commissions and referrals are captured. This episode teaches a real system, solves the common “partners go dark” problem, and gives actionable templates and a quick implementation checklist so solo advisors and small teams can start co-selling without new headcount.

Many tech advisors leave recurring revenue and easy wins on the table because manual audits are slow, inconsistent, and painful. In this episode Bob and a guest who has built a profitable audit-for-fee offering walk through how to use lightweight AI to analyze telecom bills, vendor contracts, and usage telemetry, surface guaranteed savings or reclamation opportunities, and package findings as a saleable service. You’ll get a step-by-step blueprint: which data sources to collect, how to automate anomaly detection and margin-safe recommendations, pricing and pilot structures that win trust, and exactly how to turn every audit into follow-up upsells and retained services. This is tactical, low-tech-to-start advice that a solo advisor or small MSP can implement in weeks to create a new predictable revenue stream and differentiate in a crowded channel.

Most tech advisors treat QBRs as administrative check-ins. This episode flips that script: Bob interviews a technology advisor who built an AI-driven QBR system that turns every client review into a predictable source of savings, upsells, and renewals. Listeners will get a step-by-step framework for extracting data from bills, tickets, monitoring tools and CRM notes; feeding lightweight prompts to generate a one-page executive summary, prioritized recommendations, and a 3-step action plan; and automating delivery and follow-up without losing the human touch. The conversation focuses on practical tools, simple templates, and measurable outcomes — showable ROI, time-saved, and predictable expansion revenue. By the end of the episode you’ll know exactly how to pilot AI QBRs with three clients, what metrics to track, and a low-risk rollout plan that preserves relationships while unlocking hidden revenue. Visit the show site for templates and starter prompts.

Many technology advisors leave money on the table because vendor programs, commission rules, and routing options are messy, manual, and time-consuming. In this episode Bob Bevilacqua interviews a channel revenue strategist to teach a practical, step-by-step approach for building an AI-powered 'Commission Compass'—a lightweight system that analyzes program rules, predicts net take-home per deal, and recommends the best vendor path to maximize margin and close probability. Listeners will walk away with a simple scorecard model, a three-step pilot plan they can run in a week, and scripts to present optimized options to clients. This episode solves the real problem of opaque partner economics and moves advisors toward immediate action: identify top 3 programs, run 10 deal simulations, and start routing smarter this month. Visit AcquasitionAI.com/commission-compass to download the scorecard template and pilot checklist.

Many tech advisors lose deals not from price but from predictable, fixable risks: missed follow-up, misaligned decision-makers, vendor hiccups, or silent churn signals. In this interview Bob Bevilacqua talks with a guest practitioner who built a pragmatic, low-cost Deal Risk Radar that analyzes CRM entries, email cadence, call notes, proposal status, and vendor alerts to surface high-risk opportunities. Listeners will get a step-by-step playbook for signals to track, a simple scoring model they can implement in days, automation triggers to rescue deals, and ready-to-use scripts for human follow-up. This episode teaches a concrete process, solves the problem of inconsistent follow-up and hidden deal leakage, and leaves advisors with three immediate actions to start protecting pipeline revenue this week.

Most technology advisors rely on sporadic referrals and wishful thinking. This episode reframes referrals as a repeatable, automation-first channel you can design, measure, and scale with lightweight AI. Bob interviews a guest who has built referral programs for channel partners and uses AI to automate outreach, incentives, tracking, and follow-up. Listeners will get a practical, vendor-agnostic playbook: identify referral-ready clients, craft automated micro-asks, trigger personalized outreach using AI templates, track referral health in a simple dashboard, and close the loop with automated thank-yous and commission flows. The episode teaches specific prompts, workflow patterns, and measurable KPIs you can implement in a day or two. By the end you'll have a seven-step starter checklist and one accessible automation to deploy this week — turning underused client goodwill into a predictable lead source that scales without hiring a team.

Small advisory teams often lose momentum in live conversations because the right line or proof snippet isn’t available at the moment it matters. In this focused episode Bob interviews a CRM integration engineer and a seller who ran a compact, low-risk Live Seller Assistant pilot that surfaced one-line prompts, objection counters, and next-step scripts in a CRM sidebar in suggest-only mode. Listeners will get a practical blueprint: pick one in-call scenario, build a low-code read-draft-approve flow, size a 30-day pilot for ~20 calls, and track conservative success gates like Qualified→Pilot lift and adoption rate. The episode balances technical architecture (webhooks, sidebar vs extension, audit logs) with seller change management, compliance guardrails, and a short internal checklist listeners can use to run a safe pilot. Episode resources are framed as show materials and a downloadable pilot pack for listeners who want implementation templates and prompt recipes.

Demos, pilots, and model tests all need realistic data — but using live client records risks privacy, vendor friction, and lost trust. In this interview episode Bob sits with a data-privacy engineer and a demo-product lead to deliver a step-by-step Demo Data Sandbox playbook tailored for small technology advisory teams. Listeners learn how to choose one demo use-case, build a lightweight synthetic-data pipeline (mapping, anonymize→synthesize→validate), host a minimal sandbox, and produce buyer-safe artifacts (screenflows, one-page evidence sheets) that speed approvals and close pilots. The episode focuses on practical, low-code patterns you can run without a data team: spreadsheet-based synthesis, template-driven record generators, and conservative validation checks. You’ll get a 30-day pilot plan, copyable consent language, and a downloadable Demo Data Sandbox kit (mapping template, synth prompts, validation checklist) so teams can safely start demos this week. Visit the show site to grab the kit — Your Edge Starts Here.