How I Build a Qualified Target List Using AI + Real Data Most people let AI do all the targeting work. That's the problem. In this week's video I walk through the exact two-layer targeting system I use to go from "I need more clients" to a short list of companies I'm actually confident reaching out to. Here's what's covered: - The 4 alignment filters every qualified target has to pass - How to use ChatGPT + Sales Navigator together (neither one alone gets you there) - How to confirm your list so you're not wasting outreach on the wrong companies I also mention the Targeting Radar GPT — grab it from the link below, it'll walk you through the first layer automatically. Targeting Radar GPT

If you missed today's live session (or want to rewatch it), here's everything you need. Most people don't have a lead problem. They have a targeting problem. You build a list of hundreds or thousands of companies, send outreach, and wonder why nobody responds. The issue isn't volume — it's that you're targeting companies that were never going to buy from you in the first place. In this session, I walked through my entire B2B targeting process step by step — live, with real tools, real results, and real mistakes along the way. Here's what we covered: - How to define the "splinter" — the small, specific pain your buyer already feels (not the whole business problem) - The 3-part targeting method: Define the Splinter → Write the Prompt → Validate in Sales Navigator - A live demo of the targeting prompt inside ChatGPT, including how I pressure-tested the results and threw out companies that didn't actually fit - Why category fit isn't enough — a company can look perfect on paper but already be too digitally mature to need what you sell - How to use Sales Navigator account filters and lead filters to build a tight, validated list (not a giant ocean of names) - How to cross-reference AI output with Sales Navigator to confirm whether the targeting actually holds up - The difference between DIY targeting, community-supported targeting, and done-for-you targeting — and when each one makes sense Key takeaways if you're short on time: 1. Start with the pain, not the list. If you can't describe the specific pain that would drive someone to buy your solution, your targeting will always be too broad. 2. AI gives you a hypothesis, not a final answer. Every named account that comes back needs to be validated before you spend time on outreach. 3. Check digital maturity before you reach out. The right category + the wrong maturity = wasted meetings. Look for companies where the expertise is real but the digital presence hasn't caught up yet. 4. Exclusions are just as important as inclusions. Knowing who NOT to target will save you more time than a longer list ever will. 5. Tighten the list until it's small enough to actually work. You don't need thousands of companies. You need a short list of the right ones you can call this week.

Today we’re continuing the most important part of lead magnets: stopping the leak after someone opts in. A lead magnet doesn’t fail because it wasn’t good. It fails because nothing happens next. Here’s what we’re covering live: - What your follow-up should look like (without sounding salesy) - What to do when there’s no response - How to keep showing up and build trust until they’re ready Join me live here: https://www.skool.com/live/RgXZZdbZ4vZ

Summary In this video, I walk through a practical 2025 year-in-review—what changed inside D3 Digital Media Marketing, what worked, and what I’m building to help business owners create a content system that consistently attracts attention, moves people into a funnel, and converts into real conversations and clients. Here are the key takeaways: 1) Our “platform of choice” became Go High Level (GHL)We made a deliberate shift away from scattered embedded website forms and moved lead capture, tracking, scheduling, and automation into GHL (our white-label: CxNector). The goal was simple: one system clients can actually run their growth from—without duct-taping tools together. 2) Why GHL matters (even if you’re not “technical”)I break down the parts of the platform that matter most for scaling: - Dashboards and pipelines (visibility into lead flow + conversion) - Calendars (the starting point for attribution and automation) - Contacts + smart lists (segmentation without chaos) - Payments, invoices, subscriptions, and documents (operational maturity) - Social planner + email campaigns (distribution without multiple subscriptions) - QR codes tied to tags + automations (events, networking, digital business cards) 3) A “white glove” onboarding mindsetTools don’t solve the problem—adoption does. I explain how we guide clients through setup and usage so that handoff is realistic, reporting is meaningful, and bottlenecks are solvable. 4) The operational upgrades that drove real leverage - Manual posting → 100% automated posting to eliminate inconsistency and reduce client risk - Zapier → Make.com to reduce cost and improve performance - Expanded automation workflows across calendars, tagging, follow-ups, and nurture - Consolidation of scheduling and analytics into GHL (replacing tools like Metricool) 5) Outcomes that matteredI share examples of what we’ve seen this year: stronger posting consistency, traffic lifts (2–3x in some cases), and tangible revenue outcomes tied to better visibility + follow-up systems.

I just published a long-form article breaking down a shift we’ve made that materially changed how our funnel performs. Short version:Lead scoring by itself is outdated. What’s working now is the combination of: - Lead Scoring → who someone is (fit, role, ICP alignment) - Engagement Scoring → what they consistently do over time When those two signals intersect, something important happens: 👉 Decision-makers surface without raising their hand 👉 Sales stops chasing activity and starts responding to intent 👉 The CRM becomes a prioritization engine, not a contact database Inside GHL, we’re seeing executives quietly engage across content, email, and social — and then rise to the top naturally because the system is designed to notice patterns, not spikes. In the article I break down: - Why most scoring models fail in practice - How we implemented this inside a real CRM - How engagement over time changes pipeline quality - What surprised us once the system was live This thinking is also what led me to build KontentPath — because most teams don’t struggle with tools, they struggle with structure. We’re still in beta, and community members are getting early visibility into how this all connects. Question for the group:How are you currently deciding who gets attention first in your CRM?Gut feel, rules, scores… or something else? Drop your approach below — I’m happy to compare notes or share specifics on how we’re weighting signals if it’s helpful. https://www.skool.com/content-conversion-system-9386/classroom/75564583?md=1de81895b2c3409fbfb87cc04b8f2c82 In my Digital Spotlight community we spent time as a group talking about implementing this process and at KontentPath.com we actually walk you through the process step by step.