5,497 Reachable Leads
14-Step Pipeline

Go to linkedin.com/sales/search/people (Sales Navigator Lead Search)

You will see a search bar at the top and filter panels on the left sidebar. DO NOT type anything into the top search bar -- leave it blank always.

On the left sidebar, click "Company headcount". Check the box for the headcount range listed in the sub-search table (e.g., 11-50). Click "Show results".

Click "Current job title" in the sidebar. A text box appears. Type or paste the INCLUDE titles: CEO OR Founder OR Co-Founder OR Chief Executive. Press Enter. They will appear as green pills (green = included). Confirm the toggle at the top of the title filter says "Include."

Now add the EXCLUDE titles. There are two ways to do this. Method A: Click the "Include" dropdown at the top of the title filter and switch it to "Exclude". Now type or paste: GTM OR Growth OR Advisor OR Board OR Consultant OR Coach OR Fractional OR Intern OR Associate. Press Enter. They will appear as red pills (excluded). Switch the dropdown back to "Include" when done. Method B: Type the values while still on "Include." They appear as green pills. Then for EACH one, click the circle-with-line-through-it icon (looks like a stop sign, next to the X on the green pill). The pill turns red = excluded. Either method works. You will know it is correct when all exclude titles are red and all include titles are green.

Click "Geography" in the sidebar. Type United States and select it from the dropdown. (Add Canada as a second geography run later if needed.)

PAUSE. Scroll down to the segment tables below. Find the segment you are currently building (Segment 1, 2, or 3). Each segment has a bold line that says "Industry filter for all Segment X sub-searches" with the exact industries to input. Read that line, then come back here and continue.

Click "Industry" in the sidebar. Type and select the industries from the segment table you just read. For example, Segments 1-2 use: Software Development and Technology, Information and Internet. They will appear as green pills (included). Now add the exclude: type Financial Services and press Enter. It will appear as a green pill. Click the circle-with-line-through-it icon (stop sign icon, next to the X) on the green pill. It turns red, confirming it is excluded. Alternatively, switch the dropdown to "Exclude" first, then type the industry.

Click "Posted on LinkedIn" in the sidebar. If the sub-search says "ON," toggle this to Yes. If "OFF," leave it untouched (default = all).

Click "Seniority level" in the sidebar. Check only the boxes listed in the sub-search table. For Jamie, this is Owner only. Do NOT check CXO -- Jamie only works with founders, not C-suite executives like COOs or CFOs. CXO inflates results by 5-6x with wrong-fit leads.

CHECK THE RESULT COUNT in the top-right area of the results. If it says "2,500+ results", you must split further -- go back and narrow headcount or add the "Posted on LinkedIn" filter. If it shows a number under 2,500, you are good.

Copy the full URL from your browser's address bar. The URL contains all your filter selections. Open the Lead Source URL Tracker (Jamie tab), find the matching sub-search row, and paste the URL into the "Sales Nav URL" column. Also enter the actual result count in the "Actual Count" column.

Repeat steps 1-11 for each sub-search in the segment tables below.

Log in to app.heyreach.io. Make sure you are in the correct workspace (check the workspace name in the top-left corner).

In the left sidebar, click "Lead Lists"

Click the "+ Create New List" button (top right)

Give the list a name that matches the sub-search. Example: Jamie - SaaS Series A - Posted 11-50 (1a). Use the sub-search ID from the tables above so you can track it later.

Select "Import from Sales Navigator URL" (NOT "Upload CSV" -- that's a different option)

Paste the full Sales Nav URL you copied in Step 1. Click "Import".

HeyReach will show a progress bar. Scraping takes 5-15 minutes depending on list size. You can start another sub-search while this one runs -- HeyReach allows multiple imports at once.

When status changes to "Completed", click on the list name to open it.

Click the "Export" button (top right of the list view). Select "Download as CSV".

The CSV will contain: First Name, Last Name, Company Name, Job Title, LinkedIn Profile URL. Save the file as Jamie_Raw_1a.csv (matching the sub-search ID).

Repeat steps 3-10 for all remaining sub-searches (1b, 2a, 2b, 3a, 3b, 3c).

Open your terminal and type claude to start Claude Code

Drag all your raw CSVs from Step 2 into the Claude Code window (one per sub-search segment). You can drag them all at once.

Copy the prompt below and paste it into Claude Code. Hit Enter.

Open Google Chrome. Go to Instant Data Scraper on Chrome Web Store

Click "Add to Chrome" > "Add Extension". This is Instant Data Scraper (free, no credit limits, no account needed).

You will see a small Instant Data Scraper icon in your Chrome toolbar (top right). If you don't see it, click the puzzle piece icon and pin it.

Go to crunchbase.com/discover/organization.companies. Log in if prompted. You will see the Companies tab selected at the top left (next to Contacts and Investors). Below it is a row of filter category cards: Overview, Contacts, Predictions, Insights, Competitors, Financials, Company Status, Deals, Notes, Lists, Tags, Partner Filters. Each card has a small ⊕ icon on the right side.

Open the Overview card: Click the ⊕ icon on the "Overview" card. A panel opens showing: Description Keywords, Headquarters Location, Industry, Number of Employees, Founded, Actively Hiring, and more.

Set Industry: In the Overview panel, find the "Industry" search box. Type Software and select it from the dropdown. It appears as a blue pill with an X. (For Jamie, "Software" alone is sufficient -- it captures SaaS, software dev, and tech companies without pulling in irrelevant results.)

Set Headquarters Location: In the same Overview panel, find the "Headquarters Location" search box. Type Canada and select it (blue pill). Then type United States and select it (blue pill). Both should appear as removable pills.

Set Number of Employees: In the same Overview panel, find "Number of Employees". This is a slider with two drag handles (NOT checkboxes). Drag the left handle to 11 and the right handle to 100. The numbers display above the slider as you drag. This targets companies with 11-100 employees.

Close the Overview panel by clicking the X in the top right of the panel. Your Overview card should now show "Overview: Canada, United States, +3" (indicating 3 additional filters active).

Open the Financials card: Click the ⊕ icon on the "Financials" card. A panel opens showing: Last Funding Date, Last Funding Type, Last Funding Amount, Total Funding Raised, Valuation, Investors.

Set Last Funding Type: In the Financials panel, find "Last Funding Type" on the right side. You will see checkboxes: Pre-Seed, Seed, Series A, Series B, and a "+ More Options" link. Check Series B. (For a separate search, you can also check Series A -- run them as separate saved searches to stay under the 1,000 export limit.)

Set Last Funding Date (optional): In the same Financials panel, find "Last Funding Date" on the left side. You will see radio buttons: Past 30 Days, Past 60 Days, Past 90 Days, Past Year, Custom Date Range. Select "Past Year" to target companies that raised within the last 12 months. Or leave it unset to capture all recently-funded companies regardless of when they raised.

Close the Financials panel. Your Financials card should now show "Financials: Series B".

Open the Company Status card: Click the ⊕ icon on the "Company Status" card. A panel opens showing: Type, Operating Status, M&A Status, and IPO Status.

Set Type: Check For Profit (uncheck Non-profit).

Set Operating Status: Check Active (uncheck Closed).

Set IPO Status: Check Private (uncheck Public and Delisted -- you want pre-IPO companies only).

Close the Company Status panel. Your card should show "Company Status: For Profit, Active, +1".

Save the search: Click "Save Changes" (top right, next to the green "Sync" button) or click the 🔖 pin icon next to the search title to save it to My Dashboard > Saved Searches. Name it descriptively, e.g., Jamie software, 11 to 100 employees, Series B, for-profit, Canada/USA.

Make sure you are on the Crunchbase search results page and the results table is visible (showing Organization Name, employee count, etc.).

Click the Instant Data Scraper icon in your Chrome toolbar. A popup window opens showing a preview of the scraped data from the current page. It auto-detects the table columns (Organization Name, Headquarters Location, Description, Website, LinkedIn, Contact Email, etc.).

If Instant Data Scraper does not detect the table, scroll down the Crunchbase page first so the table fully loads, then click the icon again.

Click "Locate 'Next' button" (blue button, top left of the popup). Instant Data Scraper will highlight the Crunchbase "Next >" pagination link. If it highlights the correct button, you are ready. If it highlights the wrong element, click "Locate 'Next' button" again until it finds the right one.

Set the delay between pages: Min delay: 2 sec, Max delay: 20 sec. This prevents Crunchbase from rate-limiting you. Leave the "Infinite scroll" checkbox unchecked (Crunchbase uses pagination, not infinite scroll).

Click "Start crawling". Instant Data Scraper will automatically: scrape the current page (50 rows), click "Next", wait 2-20 seconds, scrape the next page, and repeat through all pages. The status shows: Pages scraped, Rows collected, and Working time. Let it run until it reaches the last page.

When it finishes (or you click "Stop crawling"), click the "CSV" button (green, top right of popup) to download all collected data as a CSV. Save as Jamie_Crunchbase_Companies.csv. You can also click "XLSX" for Excel format or "COPY ALL" to paste into Google Sheets.

1. Open your terminal and type claude to start Claude Code

2. Drag in your clean Crunchbase CSV from Step 3B (the one with proper column names)

3. Copy the prompt below and paste it into Claude Code. Hit Enter.

4. Claude extracts the company domains, calls the Prospeo API in batches, filters results to only CEOs/Founders/Co-Founders, and outputs a clean CSV with personal LinkedIn URLs.

5. This takes 20-40 minutes depending on how many companies (rate limits). Claude handles the waiting automatically.

Log in to app.expandi.io

In the left sidebar, click "People" > "Import" > "Upload CSV"

Select your first file. For Track A, upload Jamie_Deduped_Clean_Updated_Part1.csv first.

Map columns CAREFULLY -- this is the most important step:

Name the list clearly so you can tell lists apart later. Examples: Jamie - SaaS Growth Founders Part 1 - Mar 2026, Jamie - CB Founders Series A/B - Mar 2026

Leave "Auto-refresh" and "Auto-assign to campaign" unchecked. Click "Confirm".

Repeat for each remaining CSV: Part 2 of Track A, and Track B (Jamie_CB_Founders_Clean.csv).

Expandi processes the lists in the background. Email enrichment happens automatically -- wait 1-4 hours for large lists.

When complete, export each list from Expandi as CSV. The export includes all original fields PLUS the enriched email, phone, location, and company data from LinkedIn.

Go to app.apollo.io and log in

Click "People" in the left sidebar

Click "Import" > "Upload CSV". Select your uncontacted list (leads WITHOUT email from Expandi).

Map columns: First Name, Last Name, Company, LinkedIn URL. Click "Import".

Once imported, select all contacts. Click "Enrich" or "Find Emails" (each lookup costs 1 Apollo credit -- you will NOT be charged if no email is found).

When enrichment completes, filter by contacts that have an email. Export as CSV: Jamie_Apollo_Found.csv.

Filter by contacts with NO email. Export: Jamie_Apollo_Missing.csv.

Go to app.prospeo.io and log in

Click "Enrich" in the top navigation

Click "Bulk Enrich" > "Upload CSV". Select your Jamie_Apollo_Missing.csv file (1,374 leads without email).

Map the "LinkedIn URL" column. Prospeo uses LinkedIn URLs as the primary lookup method. If a lead has no LinkedIn URL, it falls back to "First Name" + "Last Name" + "Company Website".

Click "Start". Processing takes 15-30 minutes for ~1,400 leads.

When complete, click "Download Results". The CSV will have an "Email" column.

Split the results: rows WITH email = Jamie_Prospeo_Found.csv. Rows WITHOUT = Jamie_No_Email_Final.csv.

The API endpoint is POST https://api.prospeo.io/bulk-enrich-person with header X-KEY: your_api_key.

Sends up to 50 leads per batch. The script at 7-Scripts/waterfall_enrich.py handles batching, rate limiting, and output automatically.

Run: python3 7-Scripts/waterfall_enrich.py --prospeo-only

Disqualify leads with bad titles: intern, student, retired, former, freelance, consultant, professor, advisor, board member, volunteer, assistant, coordinator, analyst, associate, recruiter

Disqualify leads in wrong industries: staffing, recruiting, real estate, construction, healthcare, banking, insurance, airline, mining, oil, gas, agriculture, food, restaurant, hospitality, retail, fashion, fitness, entertainment, government, military, nonprofit, legal, accounting, architecture

Disqualify leads at large companies: 500+ employees (Jamie targets 11-100)

Keep everyone else -- even partial matches go to T2/T3.

Go to app.heyreach.io and log in

Click "Lists" > "Create List" > "Upload CSV"

Upload Jamie_LinkedIn_Only_T1_Personalized.csv first. Name it: Jamie - LinkedIn Only T1 - Mar 2026

Column mapping:

Important: When uploading, click "Add custom variable" at the bottom of the column mapping screen. Map the personalization_line column to a new custom variable called PERSONALIZATION_LINE. This becomes {PERSONALIZATION_LINE} in the message editor alongside the built-in variables ({FIRST_NAME}, {COMPANY}, {POSITION}, etc.).

Repeat for T2 (without personalization) and T3 as separate lists.

Create a new campaign. Name: Jamie - LinkedIn Only T1 - [Month]

Add the T1 list. Set campaign type to connection request + follow-up.

Sequence: Connection request with note > Wait 3 days > Follow-up message 1 (after accept) > Wait 5 days > Follow-up message 2

Daily limit: 20-25 connection requests per sender account.

Take your merged Jamie_All_Emails_For_Verification.csv (from the Claude Code step above).

Go to millionverifier.com and log in

Click "Bulk Verifier" in the top menu

Click "Upload File". Select your merged CSV.

MillionVerifier will ask which column contains the email addresses. Select the email column. Click "Start Verification".

Verification takes 5-30 minutes. When complete, you will see a breakdown: OK, Catch-All, Risky, Unknown, Invalid, Disposable.

Click "Download Results". The CSV will have a new "Result" column next to each email.

Open the results CSV. Filter the "Result" column to show ONLY "ok". Delete every other row.

DO NOT keep "catch-all" (spam traps hide here). DO NOT keep "risky" or "unknown." Only "ok" status. No exceptions.

Save as Jamie_Verified_Master.csv.

The API endpoint is GET https://api.millionverifier.com/api/v3/?api=YOUR_KEY&email=EMAIL

Single email verification -- loop through your CSV, 0.1s between calls to be polite.

The response JSON has a quality field: "good", "risky", "bad", or "unknown".

Keep "good" only. "risky" with result: "catch_all" can be kept for LinkedIn-aware domains but monitor bounce rates.

1. Map the site -- FireCrawl's /map endpoint gets all pages on the domain in one call (1 credit). This finds the about, careers, blog, and team pages automatically.

2. Scrape key pages -- From the sitemap, it picks the 2-3 most useful pages (about/team, careers/jobs, blog/news) and scrapes them as markdown (1 credit each).

3. Extract signals -- Claude reads the scraped content and extracts: current team size, open job postings (hiring = growth), blog last updated date (stale = plateau), product launches, and any "refocusing" language.

4. Write to CSV -- Adds columns to your T1 file: Hiring_Active (yes/no/unknown), Blog_Last_Updated, Team_Size_Estimate, Website_Signals (free text summary).

1. Search for the founder -- Exa neural search for "[Founder Name] [Company Name]" finds podcast episodes, interviews, LinkedIn posts, and press mentions.

2. Search for the company -- Second search for "[Company Name] launch OR funding OR pivot OR growth" finds recent news, product announcements, and pivot signals.

3. Extract hooks -- Claude reads the Exa results (titles + URLs + text snippets) and pulls out the best personalization angles: "I heard your episode on [podcast]", "Saw [Company] just launched [feature]", "Congrats on the Series A".

4. Write to CSV -- Adds columns: Podcast_Appearances, Recent_Press, Personalization_Hook (the best opening line), Hook_Source_URL (link to the source).

Matthew Peters / Envive AI (ICP 8.3/10): Corrected CEO title (he's Chief Architect), found ELMo paper (18,000+ citations), identified "invisible co-founder" pain signal. 14 sources, 12/15 searches.

Pratap Ranade / Arena (ICP 8.5/10): Discovered $62M double-raise pivot, Palantir acquisition backstory, ~$25.7M revenue (not in our data), active Substack. 15/15 searches.

Ben Borton / PodPlay (ICP 8.0/10): $8M Series A, spun out of PingPod ($19M Sequoia Heritage). 1M+ users, 200+ venues. Done 4+ niche podcasts but zero general founder shows -- media gap flagged.

Rob Hayden / Renew (ICP 8.8/10): $33M raised, created "retention management" category. Only 2 media appearances despite funding -- enormous media gap. Soundbite identified: "Renters don't churn from renting, they churn from relationships."

1. Feed Sherlock the enriched lead data -- All CSV columns (name, company, title, funding, headcount, industry) PLUS the FireCrawl signals (hiring, website intel) PLUS the Exa signals (press, podcasts, hooks, LinkedIn posts). Sherlock starts from a strong position.

2. Sherlock investigates independently -- Using web_search (Brave API), web_fetch, and browser tools, Opus decides what to research. It might search for a founder's podcast appearance, scrape the episode page, read what they said, then search for their company's recent pivot. Each lead gets a unique research path.

3. Sherlock writes the brief -- A full intelligence memo saved as markdown: executive summary, ICP fit score table, company profile with pivot history, decision-maker profile with career timeline, pain signals with confidence levels, podcast fit assessment with objection reframes, recommended approach with specific hooks.

4. Batch script collects results -- Extracts summary columns (Email_Opening, Outreach_Angle, ICP_Fit_Score, Plateau_Score, Pain_Signal) from each brief and writes them back to the CSV.

1. Claude Haiku + Sherlock Dossiers (69 leads): generate_hooks.py sends each dossier's executive summary to Claude Haiku, returns subject_hook + personalization_line pairs saved to dossier_hooks.json.

2. Rule-Based Pattern Matching (383 leads): Regex patterns extract hooks from funding rounds, industry, company stage, and title keywords for leads without dossiers.

3. No Hook / Generic Template (370 leads): Email uses generic Approach B/C template -- no subject_hook or personalization_line columns populated.

1. ASCII sanitization: Em dashes to hyphens, smart quotes to straight quotes, accented characters to ASCII equivalents, emojis stripped. Non-ASCII in subject lines triggers spam filters.

2. Name cleaning: Strips LinkedIn profile emojis, country flags, event tags ("[Speaker]", "(Hiring)"), parenthetical aliases.

3. Company cleaning: Removes taglines after dashes/pipes, truncates descriptions over 50 chars at word boundary.

4. Garbage hook filter: 25+ rules catch LinkedIn artifacts ("Name's Post"), dossier note fragments, truncated text, hashtag spam, URL-only content. Failed hooks are removed so the lead falls back to generic template.

5. Cross-file email dedup: T1 emails processed first; any T1 email appearing in T2/T3 files is removed from T2/T3 (lead keeps highest tier placement).

1. Instantly (Email): Upload 8 email CSVs. Create one campaign per CSV file. Map columns automatically (camelCase names match Instantly fields). Set sequences per the Campaign Playbook -- Approach A for T1 (uses {{subject_hook}} + {{personalization_line}}), Approach B/C for T2/T3.

2. HeyReach (LinkedIn): Upload 5 LinkedIn CSVs. Create one campaign per CSV. T1 campaigns are multi-channel (LinkedIn connection request fires first, email starts 2-3 days later). T2 campaigns are LinkedIn-only. Max 20 connection requests/day. All templates in Campaign Playbook.

3. Airtable (Master Database): Push all leads to Airtable at the same time as Instantly/HeyReach uploads. Airtable serves as the master lead database for tracking status, replies, and pipeline progression across both channels. Include all columns from the email CSVs plus a channel field (email, linkedin, or both).

Email templates -- T1 personalized (subject_hook + personalization_line), T2/T3 generic, follow-up sequences

LinkedIn scripts -- blank connection request, follow-up messages after accept

Spam-safe rules -- no links in Email 1, under 100 words, under 50 char subjects, ASCII only

Campaign operations -- 30/account/day hard cap, 6-campaign structure, account allocation, ramp schedule

Email + LinkedIn coordination -- parallel pacing, weekly send plan, channel offset timing

Subject line A/B tests -- personalized subject_hook vs generic variants, split test framework