Your existing book of business can be a useful starting point for finding new prospective clients. By looking at the clients and trips you already book, you can identify patterns among your highest-value clients and use those insights to find similar people within your LinkedIn network.
This workflow uses Claude (you can use ChatGPT as well) to analyze your Fora booking data, build an ideal client profile, and compare that profile with your existing first-degree LinkedIn connections. From there, you can refine the results and create manageable weekly outreach lists.
Keep everything in one continuous Claude project so each step builds on the information you’ve already provided.
Before you start
You’ll need three files. All of them come from information you already have in Fora or LinkedIn.
Your Bookings export
In your Fora dashboard, go to Bookings → Download all bookings
This export includes guest names, trip values, nights, destinations, and hotels or suppliers. Claude will use this information to understand the types of travel you typically book.
Your Contacts export
In your Fora dashboard, go to Contacts → Actions → Download all contacts.
This file is mainly used to identify people who are already clients or leads. That way, your prospect list can focus on net-new outreach rather than people you already work with.
Your LinkedIn data export
You’ll also need a copy of your LinkedIn connections.
To export your LinkedIn data:
On desktop, go to LinkedIn and select your profile photo (Me) in the top navigation, then select Settings & Privacy.
In the left sidebar, select Data privacy.
Under How LinkedIn uses your data, select Download your data.
Select Download larger data archive. This can take upto 24–48 hours.
When LinkedIn emails you, select Download archive. You may need to re-enter your password.
Save the downloaded .zip file somewhere you can easily find it, such as your Downloads folder.
Once you have all three files, you’re ready to start the workflow.
Build your ideal client profile
Step 1: Add your Fora data to Claude
Start a new Claude conversation and attach your Bookings and Contacts CSV files.
You don’t need to enter a prompt yet—just upload both files so Claude has them available for the next step..
Step 2: Identify your client segments
Next, ask Claude to analyze your existing clients and bookings.
Keep this first request open-ended rather than defining the client segments yourself. This gives Claude room to identify patterns based on your actual book of business.
Use this prompt:
"Review my list of clients and my list of bookings, and identify the type of client I typically book. Segment my clients by revenue, booking frequency, average nightly rate, and type of traveler.
For each segment, tell me: how many clients, what share of my total revenue, typical trip style (destinations, hotel caliber, solo/couple/family), and 3-5 representative clients.
Then summarize the ideal client profiles that emerge from my highest-value segments.”
This gives you an ideal client profile based on the clients and bookings already driving your business.
Find prospective clients on LinkedIn
Step 3: Add your LinkedIn connections
Once Claude has created your ideal client profile, attach your LinkedIn .zip file to the same conversation. You will need to unzip the file to add the file details. The most important file in the folder is your connections file.
If you uploaded the full LinkedIn archive, use this prompt:
“Unzip this LinkedIn export and find Connections.csv — that's the file with First Name, Last Name, Company, Position, and Connected On for everyone in my network. Don't worry about the other files in the export.”
Step 4: Score your LinkedIn connections
Next, ask Claude to compare your first-degree LinkedIn connections with the ideal client profile it created from your Fora data.
The prompt below includes two important exclusions: people who are already in your Fora Contacts and people who work as travel advisors, host agencies, or recruiters. This helps keep your prospect list focused on net-new outreach.
Use this prompt:
“Score every person in Connections.csv — against the ideal client profile we just built. Reserve Tier 1 for the strongest-matching first-degree connections; don't pull in anyone from outside Connections.csv (no pending invitations, no one you find by searching the web — only people I'm already directly connected to).
Weight seniority in their title (founder, owner, C-suite, partner, managing director scores highest; VP/head-of next; individual-contributor titles lowest) and industry fit with my top client segments. Identify any that would be good opportunities for Group bookings as well (Sales Kickoffs, Corporate Events, etc…).
Exclude anyone who's already in my Contacts export — I want net-new outreach, not people I already work with. Also exclude other travel advisors, host agencies, and recruiters, even if their title looks senior.
Rank the rest and give me the top 100 with a one-line reason for each match.”
Your first list doesn’t need to be the final one. Think of it as a starting point—you’ll refine the results in the next step so they better reflect the clients who are actually a strong fit for your business.
Refine your results and start outreach
Step 5: Fine-tune your prospect list
Your first ranked list may lean toward broad signals, such as job seniority. You can give Claude additional context to make the results more specific to your business.
Calibrate the results using your real clients
If you have five clients who represent the type of business you’d like more of, use them as examples:
“Here are the LinkedIn titles and companies of five of my best clients: [paste 5]. Use these as calibration examples — re-rank my connections by how similar they are to this specific profile, not just general seniority.”
Give more weight to an important industry
If an industry appears frequently among your strongest clients but isn’t showing up enough in the results:
“Looking at my top segment again, [industry] shows up more than the scoring reflects. Increase the weight for that industry and re-rank.”
Review people who were excluded
If you want to make sure the filters aren’t removing potentially strong prospects:
“Show me 20 people you excluded or scored low, with the reason for each. I want to check the filters aren't accidentally cutting good prospects.”
Flag connections with limited profile information
Sparse LinkedIn profiles can otherwise receive low scores simply because there isn’t enough information available:
“For anyone with a missing or very sparse title/company, flag them as "insufficient data" in a separate list instead of scoring them zero, so I can review them manually.”
Look for warmer paths through existing clients
You can also identify prospects who work at the same company as one of your existing clients:
“Cross-check the top 300 candidates against my Contacts export by company name — flag anyone who works at the same company as an existing client, since that's a warmer path in.”
Check whether 100 prospects is the right cutoff
Rather than relying on an arbitrary number, you can ask Claude to show where the quality of the matches naturally starts to drop:
“Before finalizing, show me the score distribution across all candidates. Is there a natural break where the fit drops off, rather than an arbitrary top 100?”
These adjustments can help move your results from a broad list of senior LinkedIn connections toward people who more closely resemble the clients already booking with you.
Step 6: Create your outreach plan
Once you’re comfortable with your prospect list, break it into smaller weekly batches. This gives you a clear, manageable place to start instead of trying to tackle the entire list at once. You’ll want to do the original outreach on LinkedIn, given you won’t have their emails.
Use this prompt:
“Split the top 100 into weekly outreach batches of 20, ordered by tier. For each person, draft a one-line, non-salesy LinkedIn message opener referencing something specific from their profile — no generic "I help people book travel" pitches.”
You’ll now have a prioritized list of existing LinkedIn connections, along with weekly outreach batches to help you put the research into action.