5 High-Intent Crunchbase Presets Automate Your Search Strategy

Swipe File: 5 High-Intent Crunchbase Filter Presets

last updated: Jan 28, 2026
Most founders use Crunchbase like a digital phonebook. They waste hours scrolling through dead leads and pitching empty inboxes. These five specific filter combinations isolate companies with actual budget and intent, effectively automating part of your Crunchbase search strategy. Focus on companies that can buy, not just companies that make headlines.

TL;DR

A Crunchbase filter preset is a pre-defined set of boolean search parameters designed to isolate "ready-to-buy" prospects from the noise of the general database.

  • Benchmark: Aim for 50–200 results per search. Anything more is too broad to personalize.
  • Rule: Always use the "Exclude" function for "Closed" or "Acquired" companies to avoid pitching ghosts.
  • Warning: The "Software" industry tag contains 30–40% false positives (agencies masquerading as SaaS) [Source: Clearbit Data Analysis 2025].

Glossary

  • Funding Status: The current stage of capital injection (e.g., Early Stage Venture, Series A). This is your primary proxy for budget availability.
  • Last Funding Date: A recency filter. Money raised 6–12 months ago is often already spent or allocated. Money raised 0–90 days ago is liquid and ready for deployment.
  • Actively Hiring: A signal indicating operational expansion. If they are hiring sales reps, they need lead gen tools. If they are hiring engineers, they need dev tools.
  • Industry Group: Broader categories (e.g., Information Technology) that capture companies missing specific niche tags.

How to Use These Presets

Success requires precision. Do not just copy the industry. Copy the logic. Open Crunchbase Pro, navigate to "Advanced Search," and select "Companies." input the parameters below into the corresponding fields on the left sidebar. Save each search as a dynamic list to receive alerts when new companies match your criteria.

The Asset

1. The "Fresh Series A" (Primary Target)
Use this to find SaaS companies that just hit product-market fit and have $5M–$15M in the bank. They are under pressure to grow immediately.
  • Industry Group: Software OR SaaS OR Enterprise Software
  • Investment Stage: Early Stage Venture OR Series A
  • Last Funding Date: < 90 days ago
  • Total Funding Amount: $5M to $20M
  • Operating Status: Active
  • Headquarters Location: United States OR United Kingdom OR Canada

2. The "Silent Scaler" (Bootstrapped Growth)
These companies aren't in the news for raising millions, but they are hiring aggressively. They likely have revenue and are careful spenders but better long-term customers.
  • Industry: SaaS
  • Funding Status: Private Equity OR Seed (exclude Series A/B/C)
  • Estimated Revenue: $1M to $10M
  • Number of Employees: 11 to 50
  • Employee Growth (6 months): > 20%
  • Actively Hiring: Yes

3. The "Tech Stack" Poach (Competitor Targeting)
This requires the "Technographics" filter. Use this to find companies using a competitor you displace or a complementary tool you integrate with. It leverages the Crunchbase Signal Rank logic by focusing on tech adoption.
  • Industry Group: Internet Services OR Software
  • technologies_used: [Insert Competitor Name] OR [Insert Partner Name]
  • Last Funding Date: < 1 year ago
  • Number of Employees: 51 to 200

4. The "Leadership Transition" (New Decision Maker)
New VPs and C-levels want to make a mark in their first 90 days. They rip out old software and buy new tools.
  • Industry: SaaS OR FinTech OR E-Commerce
  • Job Moves: Executive OR VP OR Director
  • Job Moves Date: < 60 days ago
  • Company Total Funding: > $1M
  • Operating Status: Active

5. The "E-Commerce Enabler"
DTC brands have high churn, but the tech companies serving them are booming. This filter targets the B2B side of e-commerce.
  • Industry: E-Commerce Platforms OR Supply Chain Management OR Logistics
  • Investment Stage: Seed OR Series A
  • Last Funding Date: < 180 days ago
  • Headquarters Location: North America
  • Actively Hiring: Sales OR Marketing

Benchmarks

Do not expect 100% accuracy. Data decays. Here is the math you should expect when running these filters.

Sample Math: The Funnel Reality
  • Input: You extract 1,000 leads using the "Fresh Series A" filter.
  • Clean Up: 30% are agencies or false positives. You remove them. Remaining: 700.
  • Verification: 10% have invalid emails. Remaining: 630 valid contacts.
  • Outreach: You send 630 highly personalized emails.
  • Performance: 50% Open Rate (315 reads). 4% Reply Rate.
  • Result: 12–13 qualified conversations.
If you are getting fewer than 10 conversations from 1,000 raw leads, check your subject lines or your offer. It is rarely the list at that point.

Static vs. Dynamic Filters

Understanding the difference between static data and dynamic signals is key to using these presets effectively.
  • Static Filters (Demographic): Industry, Location, Employee Count. These tell you who the company is. They are necessary but insufficient. Relying only on these results in a "cold" list of companies that may not be buying.
  • Dynamic Filters (Behavioral): Last Funding Date, Hiring Status, Tech Install. These tell you what the company is doing right now. This is your "intent" layer. It signals a buying window is open.

Risks

Even with advanced presets, two main risks remain:
  1. The Agency Trap: Development shops often tag themselves as "SaaS" or "Software" to attract investment or clients. If you see a company with 50 employees and 45 of them are engineers, it is likely a dev shop, not a product company.
  2. Data Decay: A company listed as "Active" might have shut down operations last week. Crunchbase updates are not real-time. Always verify the website works before adding them to your LinkedIn outbound campaign.

Conclusion

Mastering these Crunchbase filter presets is a necessary step to build a list, but it is not the whole picture. You can copy these search parameters perfectly, generating a list of 500 "ideal" leads, yet still hear crickets when you launch your sequence. A static database entry does not equal a dynamic buying window.

You can have perfect execution here, but if your other variables (Offer, Strength, Market Timing) are weak, your probability of hitting $10k MRR remains near 0%. This is where the difference between "data" and "signal" becomes critical. These filters give you the list, but you need to assess the momentum of each company to know who is actually ready to buy.

Take the 90-second audit to calculate your probability of hitting $10k MRR in the next 90 days.
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FAQ
  • You:
    Why do I see service agencies in my SaaS search results?
    Guide:
    Companies self-report their industries. Many dev shops tag themselves as "Software" to appear investable. Always cross-reference with employee count and "technologies used" to filter them out.
  • You:
    How often should I run these searches?
    Guide:
    Run the "Fresh Series A" search weekly. Funding news is time-sensitive. If you wait a month, those founders have already been pitched by 50 of your competitors.
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