Building A High-Value Lead Database

Years doing cold outreach taught me this: Bad segmentation will break your campaigns Look, I get it—spray and pray is easy. It’s low maintenance, and sometimes it even works. But here’s the problem ❌ Low reply rates ❌ Risk of burning your dream clients ❌ Wasted email volume on unqualified prospects The result? Fewer meetings booked per week. Here’s what to do instead: 𝟭. 𝗕𝘂𝗶𝗹𝗱 𝗮 𝗵𝗶𝗴𝗵-𝗾𝘂𝗮𝗹𝗶𝘁𝘆 𝗽𝗿𝗼𝘀𝗽𝗲𝗰𝘁 𝗹𝗶𝘀𝘁 Scrape your Total Addressable Market (TAM) using Apollo.io (or similar). Then, upload the data into Clay for deeper segmentation. 𝟮. 𝗦𝗲𝗴𝗺𝗲𝗻𝘁 𝗯𝘆 𝗳𝗶𝗿𝗺𝗼𝗴𝗿𝗮𝗽𝗵𝗶𝗰𝘀 Break your list down by: ✅ Industry ✅ Seniority ✅ Revenue* ✅ Company size ✅ Role/Department To get precise revenue data, use waterfall enrichment: 🔹 Clearbit 🔹 HG Insights 🔹 RocketReach 🔹 People Data Labs 🔹 Owler - A Meltwater Offering This helps you focus on high-probability prospects who are more likely to convert. 𝟯. 𝗚𝗼 𝗱𝗲𝗲𝗽𝗲𝗿 𝘄𝗶𝘁𝗵 𝗮𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝘀𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 Leverage Claygent to segment based on unique attributes: 🔍 Does the company offer Buy Now, Pay Later? 🔍 Are they SOC II, GDPR, or ISO 9001 compliant? 🔍 Do they have a podcast? Use yes/no questions or multiple-choice (max 3 options) to improve accuracy. The goal? Gather enough intelligence to anticipate their pain points, and solutions before even reaching out. 𝟰. 𝗨𝘀𝗲 𝗰𝗮𝘀𝗲 𝘀𝘁𝘂𝗱𝘆-𝗯𝗮𝘀𝗲𝗱 𝘀𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 Ocean.io helps you find hundreds of companies similar to your highest-paying clients, while a simpler (but still effective) approach is to segment by industry and refine it over time. 𝟱. 𝗦𝗲𝗴𝗺𝗲𝗻𝘁 𝗯𝘆 𝘃𝗲𝗻𝗱𝗼𝗿𝘀 & 𝘁𝗲𝗰𝗵 𝘀𝘁𝗮𝗰𝗸 Another powerful way to qualify leads is by the vendors they use: ⚡ BuiltWith – See what technologies are installed on a website. ⚡ ScrapeLi – Check if they follow a certain company on LinkedIn. ⚡ PredictLeads – Scrape employee certifications & job postings to understand what software they’re using. At the end of the day, better segmentation = better results. 𝗤𝘂𝗶𝗰𝗸 𝗿𝗲𝗰𝗮𝗽: Scrape a lead list Segment by firmographics Use Claygent for advanced segmentation Use case study-based segmentation Use vendor-based segmentation P.S. Are you implementing these methods?

I’ve talked with over 100 sales leaders in the past 3 months and I am covering all 5 of their top challenges in depth each week…. Today we are talking about Account Targeting. Everyone has an Ideal Customer Profile (ICP), but if you're only relying on that to target accounts, you are missing the mark. At HubSpot and Klaviyo, I learned that the ICP doesn't guarantee quick closes, high revenue, or long-term retention. It's just a starting point...each segment needs to dig deeper to find the best paths to quota attainment. So how do you target the right accounts? Here's the playbook that works: 1. Pick Deals You Can Actually Close 🎯 Chasing shiny accounts that are too complex or a poor fit wastes time. Identify accounts where you realistically have a strong chance to win. Tip: Look at your closed-won deals to find common factors like industry and company size. Stick to accounts matching your historical sweet spot. 2. Balance Size with Speed ⚖️⏳ Big deals are great, but if they take too long to close, you might miss your number and be on PIP by the time it comes in. Balance opportunity size with how quickly it can close. What to do: Prioritize accounts with high revenue potential that also move quickly through the pipeline. Look for patterns in your fast-closing, high-value deals. 3. Target the Stickiest Accounts 🤝 The best deals not only close but also stick around, expand, and refer others. Prioritize accounts that resemble your most loyal customers. Okay so how do we find the right target accounts? Build a TAP (Target Account Profile): Start with the Data: Pull up your CRM and create a dashboard of all your closed-won deals. Focus on key metrics like close rates, deal size, speed to close, and customer stickiness. These are the factors that tell you what types of accounts are the most valuable. Download the Report: Once your dashboard is set, download the report. And upload as a pdf into GPT (or another AI tool) and ask it to analyze your deals and find your top accounts. Make sure it weighs factors like likelihood to close, speed of close, deal size, and stickiness—with extra weight given close rates and deal size. Enrich Your Data: Next, take those top-performing accounts and upload them into a tool like Clay or another enrichment platform. The goal? To find every company that looks just like your best accounts in terms of size, industry, revenue, and buying patterns. Distribute to Your Team: Once you have this enriched data, distribute it to your sales team as Tier 1 accounts. These are the highest-priority accounts, the ones most likely to close quickly, at scale, and with high retention. Make sure your team knows these are the deals that will move the needle. That's how you solve the account targeting problem. Remember, the ICP isn't always what moves the needle for every sales segment. What did I miss? Leave your account targeting thoughts in the comments

Building hyper-targeted prospect lists used to be a major challenge for me. I sifted through endless data, tried generic filters, and spent hours on manual searches—all with mediocre results. Then I developed a lookalike audience strategy—and it changed everything. Here's exactly how I do it: 1. Identify My Best Customers I start with my most successful and best performing clients. These are the businesses I want to replicate. 2. Grab Their Website URL I visit a couple websites and copy their URLs. This becomes the foundation for creating my Ideal Customer Profile (ICP). 3. Open PandaMatch I open PandaMatch 🐼, a tool designed to build detailed customer profiles based on existing clients. 4. Build My ICP with PandaMatch I paste the URL into PandaMatch. It analyzes the site and generates a comprehensive ICP—covering industry specifics, company size, and other key attributes. 5. Export and Find Similar Leads in Apollo.io I click "Export" and select "Find Leads in Apollo." This moves my ICP data into Apollo, where I can search for companies that match my ideal criteria. 6. Refine the Search with ChatGPT To zero in on decision-makers, I open ChatGPT and input something like: "My ICP is Law Firms with 2 to 30 employees located in the US. I'm selling a bookkeeping service. Give me 25 job titles of the best buyers within a law firm, such as owner, CEO, partner, etc. Please separate each title with a comma." ChatGPT provides a list of job titles most likely to be interested in my service. 7. Target Specific Job Titles in Apollo I copy the list of titles from ChatGPT and paste them into the "Job Title" filter in Apollo. This ensures I'm not missing anyone. And that's how I use lookalike audience to build hyper-targeted prospect lists. ✌ Hope this helps

“211 SQLs → $7,500 x 9 deals → $67,500 for client Bobby in just 35 days with cold email” “Cody, where have you been in the last month?” → Dialing in hyper-scale cold email systems. Everyone need to become *the best* at One thing. My One thing = high volume cold email. P.S. This does NOT work if you have a small TAM (Total Addressable Market) / account-based-marketing. 🐊: This is, however, *the* best strategy for any B2B that has a product/offer where economics make sense at a large scale. You’ll know if you have a high TAM product & backend to deliver. before the LinkedIn up-bound/around-bound failed outbound agency owners say “outbound is dead, you shouldn’t make that much money from email!!” 🤡 These automated campaigns were a button push. There was little effort after the initial setup other than lead management. It’s absolutely not as easy as it was in 2021. Cold email is difficult. Mass market advice is.. “…buy inboxes from us, VAs to deliver lead lists, copy/paste templates to ICP then hundreds of SQLs appear out of thin air.” The success rate ^ is probably 10%, especially in the 1st month. If a “marketer” tells you otherwise, question them. Here’s what’s been working well: ✅ Weekly Domain blacklist checks ✅ Weekly Inbox Placement Tests + replace bad inboxes [see if you’re going to spam] ✅Open tracking off (Non-negotiable) Don’t send links or videos or images ✅ Apollo / Sales nav to build initial (top of funnel) lists ✅ Clay to qualify accounts at scale + remove non-ICP fits + add in gpt4o personalizations to qualified leads ✅ Findymail to enrich & double-validate email addresses [Findymail is the best email enrichment tool on the market, A/B test it vs every other provider and it will will] ✅After 3-4 months of list building, you’ve built a niched ICP database of your best ideal customers with enriched data/personalization columns. Recycle this list infinitely with new angles. 100% of the time, prospects forget your email the next day, after a few months or sooner reach back out. ✅ Cold outbound messaging based on customer interviews/sales calls, although you can spawn ideas from thin air. Here’s what has NOT been working well in the outbound space in the last 45 days: 👉 Don’t use ANY “private infrastructure” sellers. You will waste your money, 99.9% of the time. I know just about every high level outbound person in this space, we’ve all tried MailScale, Mailforge, InfraForge – they’re not good. They are marketers selling a bad product, they have fantastic marketing angles. Ultimately, make your own choice + question everyone. 👉 Google inboxes sending to other google inboxes. Microsoft is starting to become a foundation to solve this. 👉 Listening to mass market outbound advice. Cody

"We don't have enough people to call" is utter nonsense. Your TAM is likely not that small — you just don't know how to identify the contacts in your TAM. Here's exactly how I build my lists to capture my entire TAM: STEP 1: Figure out where your leads are and collect them. At PhoneBurner, we have to call businesses that have sales development managers, but simply looking up "Sales Development Directors" on SalesNav doesn't cut it. Instead, I: ➜ Scrape websites (using Bardeen) to collect customer reviews on competitor pages ➜ Search for companies hiring for SDRs ➜ Find accounts who attended events with public attendee lists If a website (Like LI or G2) prohibits scraping, you can copy/paste the contents of the page into ChatGPT and ask it to make a table. STEP 2: Upload account list to Sales Navigator. Once you've isolated your accounts and put them into Google Sheets, Excel, Airtable, etc., you'll need to enrich the data by using Clay or my Google Sheet formulas (which are free). Using one of these, you'll need to find: ➜ Account website ➜ Account LinkedIn URL Then, go to LinkedIn Sales Navigator ➜ Accounts ➜ Upload Accounts STEP 3: Find leads from account list and get data. It doesn't matter what data provider you use as long as it has a Sales Nav extension and a bunch of credits. Personally, I like Seamless & TryProspect. Start filling out the lead filter criteria and under the account workflow section, include the uploaded account list(s). Let all of your searched leads automatically save into a default folder from your data provider. STEP 4: Call leads and continue to retarget. Big mistake in outbound is that we'll call a list X amount of times and then forget about it. Instead, call your list, bucket your contacts, follow up with your leads, and work your buckets. This is done best with PhoneBurner. Some pro prospecting tips: ➜ Recent job changes is a great trigger ➜ Departments with a 30%+ growth is also a great trigger ➜ Waterfall/segment your leads > sequencing them ➜ Book demos with multiple departments instead of just 1 ➜ Expand your TAM by contacting your current customer's competitors ➜ Enrich contacts in a "bad #" folder to get their correct numbers ➜ Search posts about your competitors by including quotation marks ➜ Find your best customers and ask for referrals ➜ Cleanup formatting errors in CSVs using ChatGPT + enrich data using my Google Sheets prospecting guide

How a Clay-Powered GTM System Transforms 10,000 Weekly Leads Into 350 Qualified Opportunities Sales and GTM teams know this challenge: Too many potential leads with not enough signal to identify which ones actually matter, or an unstructured TAM wich little rich data on how to prioritize accounts. Let's look at an end-to-end system that changes how startups handle lead qualification at scale. This isn't about adding another tool to the stack – it's about re-thinking what's possible with go-to-market execution in 2025. From Signal Overload to Precision Targeting This system processes around 10,000 weekly leads triggered by marketing email interactions and automatically: 1. Filters out 95% of non-ICP leads using rigorous qualification criteria 2. Only enriches high-value contacts with validated work emails 3. Routes qualified leads directly into the CRM with proper field formatting 4. Triggers automated outreach from the appropriate rep's account What previously required teams to manually review thousands of leads now happens hands-off. What's the alternative Without a system like this, it's by and large one of these two: → Manual overload: SDRs spend hours reviewing thousands of low-quality leads → Missed opportunities: Arbitrary sampling means missing high-value prospects hiding in the data The real power isn't just automation – it's the sophisticated qualification engine using data points most companies can't efficiently access: → Director+ seniority filtering via title parsing → Funding stage and amount verification → Sales hiring detection using custom web scrapers → Multi-tier scoring logic with business-specific criteria Real-World Impact This isn't theoretical – the system currently: → Processes tens of thousands of weekly inbound leads → Identifies roughly 350 tier-one qualified opportunities → Triggers personalized outreach from the right rep → Maintains complete data integrity across all systems Everything runs through Clay with custom AI agents and intelligent workflows making decisions that were previously impossible to automate. Beyond Basic Enrichment → Custom AI agents gather data 40x cheaper than standard enrichments → Strategic qualification before enrichment means only paying for data on qualified leads → Proper CRM integration with field mapping → Auto-cleanup workflows maintain system efficiency It's one of the systems Brendan Short and I are building together. Hit us up if you're interested in seeing what's possible and sensible for your GTM. 🎥 Hands-on how this looks in the clip below, architecture and the actual system. 🗯️ I've got a detailed 45-minute walkthrough showing exactly how this system works column by column. Drop a comment for access to the full technical breakdown.