Every venture capital firm wants to get in at the beginning of the next unicorn to skyrocket to a $1 billion+ company, but they frequently run into two major problems...
The first is that they don't have a vast and rich dataset of companies with various metrics like employee growth, founder movements, and other investment signals.
So, it's hard for many VC firms to sufficiently source new deals when they can't consistently identify new potential startups.
You need to be able to see clearly with a strong data foundation to do that.
The second problem is that they don't have optimized deal-sourcing processes to sift through different datasets.
Something that automatically finds the right startups for you so that you're not out there wasting time at yet another conference.
So when VC firms run into these two problems, instead of finding prime investment opportunities; their competitors do.
I don't think I have to tell you...
Finding the right startup at the right time is everything.
That's exactly why this article is all about showing you a new strategy to gain an edge over your competition.
But first, it's important we talk about:
The venture capital process
Your fund investors want to continually see high returns, and you want to keep bringing in more money.
What's the only and best way to do that?
Well, first you need to keep a steady deal flow. You have to keep your metaphorical doors rotating, as it's the lifeblood of every VC firm.
If you're not actively out there doing research every day and finding new leads or identifying new potential investments; your competition is.
Even with the most efficient deal-sourcing process ever, you'll still be investing in less than 1% of the meetings you book.
Deal sourcing is very much a numbers game
You think you find a good business, and then you start screening them and realize it'd be a disaster to invest in that idea, business, or person.
If you do find the right idea, business, or person that's gone through your extensive process of qualification and due diligence?
Well then, the second part of the job starts. It's time to nurture your investment into fruition.
More or less, VC funding is all about commercializing innovation.
You want to find a startup just barely established that's shown a proof of concept, and you want to help them nurture that idea and product until it reaches a large enough size it can be sold for a much larger amount later on.
You take on quite a bit more risk than traditional investments, but it can pay off significantly - and as I mentioned earlier, everyone wants to see their finances growing.
In the nature of high-risk, high-reward, many of your investments do not pay off...
Some markets, such as Fintech, have extremely high failure rates. The National Venture Capital Association puts an average estimated failure rate of 25% to 30% of all VC-funded businesses failing.
But, providing you're getting into these investments at the right time (so that you have leverage), that's fine, because the investment in the right startup will make up for, and beyond, all of your failures.
Inbound vs. outbound deal flow
Outbound is what you could consider the proactive approach. You go out and hunt for your investment opportunities.
Usually, the goal is to contact startups before they're ready to take on funds. That way, they have a little more time to show proof of concept and then come back later when they're ready for funding.
It's important to know how to outbound deal flow, because often however successful your VC firm is at doing it, particularly in the beginning stages of the fund, has an impact on your VC firm's reputation, therefore, your inbound deal flow.
If your VC firm has a strong brand and reputation, your inbound deal flow will go way up. But you have to have a strong outbound deal flow first.
Often if you ask a VC firm if its deal flow is "good", they'll determine it by how many deals they're sourcing by inbound leads.
What does your investment thesis look like?
At Proxycurl, we work with a lot of VC firms of varying sizes.
It seems the common difference between smaller VC funds and larger VC funds is often a differentiation of focus.
Frequently a lot of the smaller VC firms that use us might have an investment thesis, but it's so broad, that they might as well not even have one.
For example: "We invest in growth-stage Singapore startups" - that's not an investment thesis. That's far too broad.
When it comes to thinking of a strong investment thesis that works for both attracting new investors for your fund and appealing to startups you want to invest in, you'll need to get specific.
Answer the following questions:
- What's your fund name?
- What size of fund are you?
- Who are you targeting? (Angel, pre-seed, seed, series A, etc.)
- What country or city are you targeting them in?
- What sector are they in?
- What do you do differently that works better than everyone else? (What's your edge?)
The clearer you get, the better
Here's a second example of an investment thesis using all of the points mentioned above:
"Unicorn VC fund is a $25 million dollar seed fund based out of San Francisco, California to uniquely help early-stage fintech companies scale using our specialized knowledge of the banking industry, as well as our founder's unique relationships and understanding of the industry considering their exit from Paypal back in 2002."
How much better does that sound than the first example? Quite a bit if you ask me.
Your investment thesis of course serves a huge purpose because it helps attract limited partners to your VC fund, but it serves a larger purpose than that:
Focus.
The very first step to optimizing your deal-sourcing processes is getting clear on what you do, and who you do it for. Don't be the VC firm for everyone.
Re-evaluate your investment thesis, and if it's broad, narrow it down, and get specific.
Before we get into our new deal sourcing strategy, we need to go over the typical deal sourcing strategies first, and the pros and cons of each:
Typical deal-sourcing strategies
Networking in general
Networking is going to all of the normal networking events. Meeting investors and founders in person. Kissing babies (just kidding), exchanging business cards, and following up via text and email.
You know: The old school way, building relationships slow and steady for both fund investors, and interesting founders to fund. It works, but it takes a serious level of time investment.
The lack of scale, and how slow it often takes to get a significant flow of deals sourced through networking is the biggest con.
The pro, on the other hand, is that building a network is a great source of organic deal flow; once you've established a strong VC portfolio.
Sourcing referrals from your network
Sourcing deals from your internal network is quite common. Especially because a referral in itself is a form of qualification.
Typically these companies might fit better with your investment thesis, too.
The main pro is that deals sourced from referrals are usually high quality in nature, and come pre-vetted.
The main con is the lack of scale. Especially for smaller VC funds. You're usually just not going to have referrals coming in constantly - it takes a very strong reputation to form a constant flow of deals sourced from networking alone.
Putting a focus on generating inbound leads
Alternatively, create a general level of awareness about your VC firm. Usually done through social media or blogging.
The goal is to release content that gets seen and represents your investment thesis so both startup founders and new fund investors become aware of your VC firm, and hopefully, part of your network.
The real benefit of this strategy is that it's scalable. You can outsource content creation much easier than you could in-person networking; that's very much individual to individual, and those relationships change when the individuals do.
The con is it takes a very long time to establish brand awareness, plus, plenty of other VC Funds are going to have established domains, and established rankings for many of the keywords you'd need to rank for.
It's scalable, but it's a long-term game and doesn't give you sustainable right now money.
Notice any similarities?
For starters, 2 out of 3 of the strategies mentioned above are as old as dinosaurs (maybe not that old, but close) and every other VC firm out there is doing the exact same thing.
The last strategy is a little bit more modernized but still takes a significant labor and time investment to see real results from it.
And none of the deal sourcing strategies above give you immediate deals and investment opportunities...
Plus, none of it is cutting-edge. Your competitors are doing the exact same thing.
How are you going to get to the best investment opportunities first by doing the same thing, the same way?
You aren't.
Have no fear, though, that's what we're here for.
Sourcing deals in 2023 and beyond
It's all about 4 things:
1) Using richer data
It used to be a very time-intensive process to manually do the research to find new investment opportunities.
With tools on the market like Proxycurl that can provide you incredibly rich data, fast, there's no reason for that.
Plus, you need to be able to identify investment signals with alternate data points like:
- A key person joining a startup
- Hiring velocity
- Beyond
2) Automating everything possible
If it doesn't require a human, you don't use a human.
You need to be able to have a rich data foundation and automate every part of the searching and screening process that you can by using tools like Proxycurl.
Ideally, you want to reserve your time for things that actually move the needle.
3) Reaching out first, and getting close
Once you piece together data and automation, direct deal sourcing can become quite effective.
You'll be able to skip wasted time and target ideal investment profiles right away. You're actively sourcing your best deals.
It's all about building relationships. Even if you reach out to a startup and they're not yet interested, you build your list of cold but ideal investment opportunities for later.
And last, but not least...
4) Finding the right startup at the right time
The key to finding the right startup at the right time is by using investment signals like mentioned above.
Imagine there's this tiny startup that nobody knows and suddenly your favorite seasoned and salty FAANG exec who's about to scale the company to the moon joins.
You're the first to know, and you congratulate them on the move. From that point forward, you occasionally exchange messages, and then eventually as the relationship forms, they ask you for funding.
That's an incredibly natural and easy example of direct deal sourcing. When it comes to the best way to reduce friction for direct deal sourcing, it's going to be using investment signals.
Using Proxycurl to find the right startups at the right time
Over here at Proxycurl, we've built a vast and rich database full of millions of profiles of people and companies. We call it LinkDB.
What that means for you is that you won't have to invest the time or resources into building a data science or web scraping team at your VC firm; we take care of that for you. We can provide your VC firm with the data it needs to source deals.
This article won't focus on LinkDB, however, it'll focus on our API, which is partially powered by LinkDB -- simply because it's faster to implement our API and easier to demonstrate.
But, LinkDB certainly can serve as a data foundation for your VC firm to build a custom in-house application
Anyways, first up:
Monitoring employee growth
Let's say you have a couple of startups on your radar, but you're waiting for them to really prove themselves before you make a move.
So you decide to sit on the idea for a while and monitor the growth of the company. One of the best ways to do this is to directly monitor employee growth itself.
Once you've identified a group of companies you want to monitor, you can use a little bit of Python, our Employee Count Endpoint, and the schedule library to automatically monitor their growth every 30 days.
Here's an example of using the Employee Count Endpoint:
import requests
import schedule
import time
# Your Proxycurl API key
api_key = 'Your_API_Key_Here'
headers = {'Authorization': 'Bearer ' + api_key}
api_endpoint = 'https://nubela.co/proxycurl/api/linkedin/company/employees/count'
# List of LinkedIn URLs for the 10 companies
companies = [
'https://www.linkedin.com/company/apple/',
'https://www.linkedin.com/company/microsoft/',
# ... add URLs for the other 8 companies
]
# Dictionary to store the employee count for each company
employee_counts = {}
def fetch_employee_count():
for company_url in companies:
params = {
'url': company_url,
'use_cache': 'if-present',
'linkedin_employee_count': 'include',
'employment_status': 'current',
}
response = requests.get(api_endpoint, params=params, headers=headers)
data = response.json()
# Store the employee count in the dictionary
employee_counts[company_url] = data.get('linkedin_employee_count')
# Print the results (or store in a database)
for company_url, count in employee_counts.items():
print(f"Company: {company_url} | Employee Count: {count}")
# Call the function immediately upon script start
fetch_employee_count()
# Schedule the function to run every 30 days thereafter
schedule.every(30).days.do(fetch_employee_count)
# Keep the script running
while True:
schedule.run_pending()
time.sleep(1)
```
It will immediately return their employee count, and then rerun the Python script exactly 30 days after.
Now let's say you haven't identified a group of companies to keep an eye out for and need to source entirely new startups to keep an eye on.
Finding new startups worthy of investing in automatically
Using our Company Search Endpoint, we can search for companies that meet different parameters.
Using human resources to manually look for notable startups to potentially invest in is no fun. Let's automate the search process.
Going based on our example given above, let's say our VC firm is looking for a financial service-based startup located in San Francisco -- one that has received little to no funding already. Early stage.
We can accomplish this using a little bit of Python:
import requests
import csv
# API endpoint
endpoint = "https://nubela.co/proxycurl/api/search/company"
# API headers
headers = {
"Authorization": "Bearer Your_API_Key_Here"
}
# Parameters for the API request
params = {
"country": "us",
"city": "(?i)San Francisco",
"funding_amount_max":"100000",
"employee_count_min":"10",
"industry": "(?i)Financial Services",
"enrich_profiles": "enrich",
"page_size": 10
}
# Make the API request
response = requests.get(endpoint, headers=headers, params=params)
data = response.json()
# Check if 'results' key exists in the data
if 'results' in data:
# Extract the results
results = data['results']
# Print the companies matching the criteria
print("Companies matching the criteria:")
print("--------------------------------")
# Prepare data for CSV export
csv_data = [["Company Name", "LinkedIn URL", "HQ", "Industry", "Description"]]
for result in results:
profile = result.get('profile', {})
company_name = profile.get('name', "N/A")
linkedin_url = result.get('linkedin_profile_url', "N/A")
hq_value = profile.get('hq', {})
hq = hq_value.get('city', "N/A") if hq_value else "N/A"
industry = profile.get('industry', "N/A")
description = profile.get('description', "N/A")
print(f"Company Name: {company_name}")
print(f"LinkedIn URL: {linkedin_url}")
print(f"HQ: {hq}")
print(f"Industry: {industry}")
print(f"Description: {description}")
print("")
# Append to CSV data
csv_data.append([company_name, linkedin_url, hq, industry, description])
# Export to CSV
with open("sanfran_startups.csv", "w", newline="", encoding="utf-8") as file:
writer = csv.writer(file)
writer.writerows(csv_data)
else:
print("No companies found matching the criteria.")
```What that script does is search our vast database for financial service-based startups located in San Francisco -- that have more than 10 employees, and have received less than $100,000 in funding.
If it finds any, which it did, it then returns it back:
As well as exporting the list to a .CSV named sanfran_startups.csv:
You could also add funding data and employee count to that printout and export.
But it perfectly found a valid company:
Identify and track prospective founders
Using our Employee Listing Endpoint, you can get a list of employees for any given LinkedIn company URL, and you can filter it by role, too.
Being the first to notice big changes from key people is a huge part of finding the right startup at the right time.
Before we can track, we must first identify, though...
Here's an example of searching for the founder or CEO of the popular email marketing platform, ConvertKit, with some simple Python:
import json,requests
api_key = 'Your_API_Key_Here'
headers = {'Authorization': 'Bearer ' + api_key}
api_endpoint = 'https://nubela.co/proxycurl/api/linkedin/company/employees/'
params = {
'url': 'https://www.linkedin.com/company/convertkit/',
'country': 'us',
'enrich_profiles': 'enrich',
'role_search': 'Founder|CEO',
'page_size': '10',
'employment_status': 'current',
'sort_by': 'oldest',
'resolve_numeric_id': 'false',
}
response = requests.get(api_endpoint, params=params, headers=headers)
result = response.json()
print(json.dumps(result, indent=2))
That returns an enriched result of Nathan Berry, the founder and CEO of ConvertKit:
Once you've identified a notable founder you want to track, it's also entirely possible to track job changes with Proxycurl -- you know, to see if there are any new startups they've joined recently, and be the first one to take notice.
However, we just published an entirely new blog post all about tracking job changes, so I'll refer you there instead of explaining it here -- since it already does a great job at it.
You can see a live demo of recent job changes on this page.
Are you starting to get the value here?
I think you are.
With Proxycurl, you're gaining access to several different data points, and we give you several different ways of using it with our different endpoints.
It's a big edge for your VC firm to be able to:
- Identify and track hiring velocity
- Be the first to notice key people leaving or joining startups
- Tracking prospective founders
- Automatically search and filter startups with different parameters like location, funding, employee count, and beyond through a dataset of millions of different companies
- More (view all of our endpoints here)
There are several different ways that you could build our API into your existing workflow, but it's entirely possible to automate a large portion of your outbound deal-sourcing process.
So instead of attending yet another networking conference just to not find a single notable startup; you click a button.
Sounds nice, huh?
Here's what to do next
All you have to do to get started is click this link right here to create your free Proxycurl account and then integrate the data our API provides with your deal-sourcing processes.
Thanks for reading and we look forward to helping your VC firm land its next unicorn (preferably... you know, on the ground floor).
P.S. If you don't have any software engineers employed at your VC firm, or you simply just don't want to do it, that's fine -- our engineers can integrate Proxycurl with your existing application(s) for you.
Simply reach out to us at "[email protected]".
